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Build the 
Workforce 
You Need
The Best of HBR
Insights on: 
Better People Analytics, 
Desirable Benefi ts, 
Adapting Your 
Workforce, 
and More!
How to Hire the 
Right People and 
Keep Them 
Engaged
Fall 2019 
HBR.org
2 HBR Special Issue | FALL 2019
Winning the War 
for Talent
FROM THE EDITORS
Your organization’s success has never 
been more dependent on people—
those with the technical and 
leadership skills to carry you into 
the future. How will you compete? 
Companies are rushing to reinvent their talent 
management to become more responsive and 
flexible. In “HR Goes Agile,” Peter Cappelli 
and Anna Tavis describe where we’re seeing 
the biggest changes, such as performance 
appraisals, which many companies now 
conduct on a project basis rather than on 
an annual cycle. HR’s growing investment in 
data and analytics also means that at many 
companies these changes are being measured 
and honed in real time. But beware the limits 
of what your data can tell you, especially about 
diversity, Facebook’s Maxine Williams reminds 
us in “Numbers Take Us Only So Far.”
In a hot talent market, recruiting the most 
sought-after employees requires creativity—
and the newest technologies. From social 
media channels to bespoke talent pools, Erica 
Dhawan suggests approaches for targeting 
skeptical Millennials in “Recruiting Strategies 
for a Tight Talent Market.” And while machine 
learning offers big promises of personalized and 
efficient talent screening, Ben Dattner and his 
coauthors warn of the pitfalls in “The Legal and 
Ethical Implications of Using AI in Hiring.”
Your hiring situation becomes more dire if you 
can’t also retain—and retrain—the workforce 
you have. Employees don’t necessarily require 
ever-more-expensive benefits, though: They’re 
also looking for flexible hours, paid vacation, 
and other more-accessible perks. And reskilling 
also helps keep employees engaged and loyal. 
In “Your Workforce Is More Adaptable Than 
You Think,” HBS professor Joseph Fuller and 
his colleagues describe the many benefits that 
accrue to companies that work together to 
retrain the talent pool. 
Finally, the massive shift to gig work has 
employers worried about what employment 
itself will look like in the future. Will 
organizations lose top talent—and valuable 
institutional knowledge—as employees choose 
to come and go? Will they find it increasingly 
hard to hire emerging leaders as Millennials 
eschew traditional jobs and flit between 
part-time roles? In “Myths of the Gig Economy, 
Corrected,” David Jolley offers a more nuanced 
view on whether we’re all about to go freelance 
(hint: we aren’t).
Whether you’re a CEO, a hiring manager, or 
a team leader, understanding how the talent 
market is evolving will help you attract and 
keep the people you need.
—The Editors
Responsibility.
One of
our natural
resources.
Geneva Zurich Luxembourg London Amsterdam 
Brussels Paris Stuttgart Frankfurt Madrid Milan Dubai 
Montreal Hong Kong Singapore Taipei Osaka Tokyo
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4 HBR Special Issue | FALL 2019
TODAY’S TALENT 
MANAGEMENT
HR Goes Agile | 10
Peter Cappelli and Anna Tavis
One Bank’s Agile 
Team Experiment | 18
Dominic Barton, Dennis Carey, and 
Ram Charan 
Reinventing Performance 
Management | 22
Marcus Buckingham and Ashley Goodall
Better People Analytics | 30
Paul Leonardi and Noshir Contractor
“ Numbers Take Us 
Only So Far” | 40
 Maxine Williams
Is HR the Most Analytics-
Driven Function? | 46
Thomas H. Davenport
How to Develop a Data-Savvy 
HR Department | 47
Nigel Guenole and Sheri L. Feinzig
HOW RECRUITING 
WORKS NOW
Your Approach to Hiring 
Is All Wrong | 50
Peter Cappelli 
Navigating 
Talent Hot Spots | 58
William Kerr
Data Science 
Can’t Fix Hiring (Yet) | 66
Peter Cappelli
The Legal and 
Ethical Implications 
of Using AI in Hiring | 67
Ben Dattner, Tomas Chamorro-Premuzic, 
Richard Buchband, and Lucinda Schettler
Expanding the Pool | 70
Dane E. Holmes
Recruiting Strategies 
for a Tight Talent Market | 72
Erica Dhawan
How Recruiters 
Can Stay Relevant 
in the Age of LinkedIn | 74
Atta Tarki and Ken Kanara
COVER ILLUSTRATION BY GETTY IMAGES
Culled by the editors of Harvard Business Review from 
the magazine’s rich archives, these articles are written by 
some of the world’s leading management scholars and 
practitioners. To help busy leaders apply the concepts, 
they are accompanied by “Idea in Brief” summaries.
Contents
JO
AN
N
A 
ŁA
W
N
IC
ZA
K
FALL 2019
SOME CHEFS
COOK THEIR BEST
AT 30,000 FEET
Products and services are subject to change depending on flight duration and aircra� .
G
ET
TY
 IM
AG
ES
RETAINING THE BEST
Your Workforce Is More 
Adaptable Than You Think | 76
Joseph B. Fuller, Judith K. Wallenstein, 
Manjari Raman, and Alice de Chalendar 
Talent Management and 
the Dual-Career Couple | 82
Jennifer Petriglieri
The Most Desirable 
Employee Benefits | 90
Kerry Jones
Co-Creating the 
Employee Experience | 93
A conversation with Diane Gherson 
by Lisa Burrell
Your Company Needs 
a Better Retention Plan 
for Working Parents | 96
Daisy Wademan Dowling
Why I Encourage My Best 
Employees to Consider 
Outside Job Offers | 97
Ryan Bonnici
Never Say Goodbye 
to a Great Employee | 99
Tammy Erickson
UNDERSTANDING 
THE GIG ECONOMY
Thriving in the 
Gig Economy | 100
Gianpiero Petriglieri, Susan Ashford, 
and Amy Wrzesniewski
Myths of the Gig 
Economy, Corrected | 106
David Jolley
What Motivates 
Gig Economy Workers | 107
Alex Rosenblat
Performance Management 
in the Gig Economy | 109
Jon Younger and Norm Smallwood
Executive Summaries | 112
6 HBR Special Issue | FALL 2019
FALL 2019
B O C H E N G
President, Altovista Technology Inc.
Innovation isn’t new to Michigan. Our state hosts some of the world’s 
top engineering and tech talent as they build the future. And they’re 
having a lot of fun living here while doing it. If Michigan doesn’t 
come to mind when you think of the future, think again. Get here or 
get left behind. 
Visit michiganbusiness.org/pure-opportunity
WHAT EXCITES ME 
THE MOST ABOUT 
THE FUTURE OF 
MICHIGAN IS THE 
INNOVATION HERE.
“
”
EDITOR IN CHIEF Adi Ignatius
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Originally published in 
March–April 2018
ILLUSTRATION BY LLOYD MILLER
A GILE ISN’T JUST for tech any-
more. It’s been working its way 
into other areas and functions, 
from product development to 
manufacturing to marketing—
and now it’s transforming 
how organizations hire, develop, and manage 
their people. 
You could say HR is going “agile lite,” applying 
the general principles without adopting all the 
tools and protocols from the tech world. It’s 
a move away from a rules- and planning-based 
approach toward a simpler and faster model 
driven by feedback from participants. This new 
paradigm has really taken off in the area of perfor-
mance management. (In a 2017 Deloitte survey, 
79% of global executives rated agile performance 
management as a high organizational priority.) But 
other HR processes are starting to change too. 
In many companies that’s happening gradually, 
almost organically, as a spill over from IT, where 
more than 90% of organizations already use agile 
practices. At the Bank of Montreal (BMO), for 
example, the shift began as tech employees joined 
cross-functional product-development teams to 
HR Goes 
Agile
by Peter Cappelli and Anna Tavis
TODAY’S TALENT MANAGEMENT
12 HBR Special Issue | FALL 2019
TODAY’S TALENT MANAGEMENT HR GOES AGILE
make the bank more customer focused. The busi-
ness side has learned agile principles from IT col-
leagues, and IT has learned about customer needs 
from the business. One result isthat BMO now 
thinks about performance management in terms 
of teams, not just individuals. Elsewhere the move 
to agile HR has been faster and more deliberate. 
GE is a prime example. Seen for many years as a 
paragon of management through control systems, 
it switched to FastWorks, a lean approach that cuts 
back on top-down financial controls and empow-
ers teams to manage projects as needs evolve.
The changes in HR have been a long time 
coming. After World War II, when manufacturing 
dominated the industrial landscape, planning was 
at the heart of human resources: Companies re-
cruited lifers, gave them rotational assignments to 
support their development, groomed them years 
in advance to take on bigger and bigger roles, and 
tied their raises directly to each incremental move 
up the ladder. The bureaucracy was the point: 
Organizations wanted their talent practices to be 
rules-based and internally consistent so that they 
could reliably meet five-year (and sometimes 15-
year) plans. That made sense. Every other aspect 
of companies, from core businesses to adminis-
trative functions, took the long view in their goal 
setting, budgeting, and operations. HR reflected 
and supported what they were doing. 
By the 1990s, as business became less predict-
able and companies needed to acquire new skills 
fast, that traditional approach began to bend—
but it didn’t quite break. Lateral hiring from the 
outside—to get more flexibility—replaced a good 
deal of the internal development and promo-
tions. “Broadband” compensation gave manag-
ers greater latitude to reward people for growth 
and achievement within roles. For the most part, 
though, the old model persisted. Like other func-
tions, HR was still built around the long term. 
Workforce and succession planning carried on, 
even though changes in the economy and in the 
business often rendered those plans irrelevant. 
Annual appraisals continued, despite almost uni-
versal dissatisfaction with them.
Now we’re seeing a more sweeping transforma-
tion. Why is this the moment for it? Because rapid 
innovation has become a strategic imperative 
for most companies, not just a subset. To get it, 
businesses have looked to Silicon Valley and to 
software companies in particular, emulating their 
agile practices for managing projects. So top-down 
planning models are giving way to nimbler, user-
driven methods that are better suited for adapting 
in the near term, such as rapid proto typing, itera-
tive feedback, team-based decisions, and task-
centered “sprints.” As BMO’s chief transformation 
officer, Lynn Roger, puts it, “Speed is the new 
business currency.” 
With the business justification for the old HR 
systems gone and the agile playbook available 
to copy, people management is finally getting its 
long-awaited overhaul too. In this article we’ll 
illustrate some of the profound changes com-
panies are making in their talent practices and 
describe the challenges they face in their transition 
to agile HR. 
Where We’re Seeing the 
Biggest Changes
Because HR touches every aspect—and every 
employee—of an organization, its agile transfor-
mation may be even more extensive (and more 
difficult) than the changes in other functions. 
Companies are redesigning their talent practices 
in the following areas: 
Performance appraisals. When businesses 
adopted agile methods in their core operations, 
they dropped the charade of trying to plan a 
year or more in advance how projects would go 
and when they would end. So in many cases the 
first traditional HR practice to go was the annual 
performance review, along with employee goals 
that “cascaded” down from business and unit 
objectives each year. As individuals worked on 
shorter-term projects of various lengths, often run 
by different leaders and organized around teams, 
the notion that performance feedback would come 
once a year, from one boss, made little sense. They 
needed more of it, more often, from more people. 
An early-days CEB survey suggested that people 
actually got less feedback and support when their 
employers dropped annual reviews. However, 
that’s because many companies put nothing in 
their place. Managers felt no pressing need to 
adopt a new feedback model and shifted their 
attention to other priorities. But dropping apprais-
als without a plan to fill the void was of course a 
recipe for failure. 
Since learning that hard lesson, many organi-
zations have switched to frequent performance 
assessments, often conducted project by project. 
This change has spread to a number of industries, 
FALL 2019 | HBR Special Issue 13
HBR.ORG
Idea 
in Brief
THE REASON FOR 
THE SHIFT
Companies’ core businesses and 
functions have largely replaced 
long-range planning models 
with nimbler methods that allow 
them to adapt and innovate 
more quickly. HR is starting to 
use agile talent practices to 
reflect and support what the rest 
of the organization is doing.
THE AREAS OF 
TRANSFORMATION
Organizations are radically 
changing how they manage 
performance and evaluate talent, 
what skills they emphasize and 
develop, how they approach 
recruitment and rewards, and 
what they do to facilitate learning.
including retail (Gap), big pharma (Pfizer), insur-
ance (Cigna), investing (OppenheimerFunds), 
consumer products (P&G), and accounting (all Big 
Four firms). It is most famous at GE, across the 
firm’s range of businesses, and at IBM. Overall, the 
focus is on delivering more-immediate feedback 
throughout the year so that teams can become 
nimbler, “course-correct” mistakes, improve 
performance, and learn through iteration—all 
key agile principles. 
In user-centered fashion, managers and em-
ployees have had a hand in shaping, testing, and 
refining new processes. For instance, Johnson & 
Johnson offered its businesses the chance to 
participate in an experiment: They could try out 
a new continual-feedback process, using a custom-
ized app with which employees, peers, and bosses 
could exchange comments in real time. 
The new process was an attempt to move away 
from J&J’s event-driven “five conversations” 
framework (which focused on goal setting, career 
discussion, a midyear performance review, a year-
end appraisal, and a compensation review) and 
toward a model of ongoing dialogue. Those who 
tried it were asked to share how well everything 
worked, what the bugs were, and so on. The 
experiment lasted three months. At first only 20% 
of the managers in the pilot actively participated. 
The inertia from prior years of annual appraisals 
was hard to overcome. But then the company used 
training to show managers what good feedback 
could look like and designated “change cham-
pions” to model the desired behaviors on their 
teams. By the end of the three months, 46% of 
managers in the pilot group had joined in, ex-
changing 3,000 pieces of feedback. 
Regeneron Pharmaceuticals, a fast-growing 
biotech company, is going even further with its 
appraisals overhaul. Michelle Weitzman-Garcia, 
Regeneron’s head of workforce development, 
argued that the performance of the scientists 
working on drug development, the product sup-
ply group, the field sales force, and the corporate 
functions should not be measured on the same 
cycle or in the same way. She observed that these 
employee groups needed varying feedback and 
that they even operated on different calendars.
So the company created four distinct appraisal 
processes, tailored to the various groups’ needs. 
The research scientists and postdocs, for example, 
crave metrics and are keen on assessing competen-
cies, so they meet with managers twice a year for 
competency evaluations and milestones reviews. 
Customer-facing groups include feedback from 
clients and customers in their assessments. Al-
though having to manage four separate processes 
adds complexity, they all reinforce the new norm 
of continual feedback. And Weitzman-Garcia says 
the benefits to the organization far outweigh thecosts to HR. 
Coaching. The companies that most effectively 
adopt agile talent practices invest in sharpening 
managers’ coaching skills. Supervisors at Cigna go 
through “coach” training designed for busy man-
agers: It’s broken into weekly 90-minute videos 
that can be viewed as people have time. The super-
visors also engage in learning sessions, which, like 
“learning sprints” in agile project management, 
are brief and spread out to allow individuals to 
reflect and test-drive new skills on the job. Peer-to-
peer feedback is incorporated in Cigna’s manager 
training too: Colleagues form learning cohorts to 
share ideas and tactics. They’re having the kinds 
of conversations companies want supervisors to 
have with their direct reports, but they feel freer to 
share mistakes with one another, without the fear 
of “evaluation” hanging over their heads. 
DigitalOcean, a New York–based start-up 
focused on software as a service (SaaS) infrastruc-
ture, engages a full-time professional coach on- 
site to help all managers give better feedback 
to employees and, more broadly, to develop inter-
nal coaching capabilities. The idea is that once 
one experiences good coaching, one becomes 
a better coach. Not everyone is expected to 
become a great coach—those in the company 
who prefer coding to coaching can advance along 
a technical career track—but coaching skills are 
considered central to a managerial career. 
P&G, too, is intent on making managers better 
coaches. That’s part of a larger effort to rebuild 
training and development for supervisors and 
enhance their role in the organization. By simpli-
fying the performance review process, separat-
ing evaluation from development discussions, 
and eliminating talent calibration sessions (the 
arbitrary horse trading between supervisors that 
often comes with a subjective and politicized 
ranking model), P&G has freed up a lot of time 
to devote to employees’ growth. But getting 
supervisors to move from judging employees 
to coaching them in their day-to-day work has 
been a challenge in P&G’s tradition-rich culture. 
So the company has invested heavily in training 
14 HBR Special Issue | FALL 2019
TODAY’S TALENT MANAGEMENT HR GOES AGILE
supervisors on topics such as how to establish 
employees’ priorities and goals, how to provide 
feedback about contributions, and how to align 
employees’ career aspirations with business 
needs and learning and development plans. 
The bet is that building employees’ capabilities 
and relationships with supervisors will increase 
engagement and therefore help the company 
innovate and move faster. Even though the jury 
is still out on the companywide culture shift, 
P&G is already reporting improvements in these 
areas, at all levels of management. 
Teams. Traditional HR focused on individuals— 
their goals, their performance, their needs. But 
now that so many companies are organizing their 
work project by project, their management and 
talent systems are becoming more team focused. 
Groups are creating, executing, and revising their 
goals and tasks with scrums—at the team level, in 
the moment, to adapt quickly to new information 
as it comes in. (“Scrum” may be the best-known 
term in the agile lexicon. It comes from rugby, 
where players pack tightly together to restart play.) 
They are also taking it upon themselves to track 
their own progress, identify obstacles, assess their 
leadership, and generate insights about how to 
improve performance.
In that context, organizations must learn to 
contend with:
Multidirectional feedback. Peer feedback is 
essential to course corrections and employee 
development in an agile environment, because 
team members know better than anyone else what 
each person is contributing. It’s rarely a formal 
process, and comments are generally directed 
to the employee, not the supervisor. That keeps 
input constructive and prevents the undermining 
of colleagues that sometimes occurs in hypercom-
petitive workplaces. 
But some executives believe that peer feedback 
should have an impact on performance evalua-
tions. Diane Gherson, IBM’s head of HR, explains 
that “the relationships between managers and 
employees change in the context of a network 
[the collection of projects across which employees 
work].” Because an agile environment makes it 
practically impossible to “monitor” performance 
in the old sense, managers at IBM solicit input 
from others to help them identify and address 
issues early on. Unless it’s sensitive, that input 
is shared in the team’s daily stand-up meetings 
and captured in an app. Employees may choose 
whether to include managers and others in their 
comments to peers. The risk of cutthroat behavior 
is mitigated by the fact that peer comments to the 
supervisor also go to the team. Anyone trying to 
undercut colleagues will be exposed. 
In agile organizations, “upward” feedback 
from employees to team leaders and supervi-
sors is highly valued too. The Mitre Corporation’s 
not-for-profit research centers have taken steps to 
encourage it, but they’re finding that this requires 
concentrated effort. They started with periodic 
confidential employee surveys and focus groups 
to discover which issues people wanted to discuss 
with their managers. HR then distilled that data 
for supervisors to inform their conversations with 
direct reports. However, employees were initially 
hesitant to provide upward feedback—even 
though it was anonymous and was used for de-
velopment purposes only—because they weren’t 
accustomed to voicing their thoughts about what 
management was doing.
Mitre also learned that the most critical factor 
in getting subordinates to be candid was having 
managers explicitly say that they wanted and 
appreciated comments. Otherwise people might 
worry, reasonably, that their leaders weren’t really 
open to feedback and ready to apply it. As with any 
employee survey, soliciting upward feedback and 
not acting on it has a diminishing effect on partici-
pation; it erodes the hard-earned trust between 
employees and their managers. When Mitre’s new 
performance-management and feedback process 
began, the CEO acknowledged that the research 
centers would need to iterate and make improve-
ments. A revised system for upward feedback will 
roll out this year.
Because feedback flows in all directions on 
teams, many companies use technology to man-
age the sheer volume of it. Apps allow supervisors, 
coworkers, and clients to give one another imme-
diate feedback from wherever they are. Crucially, 
supervisors can download all the comments later 
on, when it’s time to do evaluations. In some apps, 
employees and supervisors can score progress on 
goals; at least one helps managers analyze con-
versations on project management platforms like 
Slack to provide feedback on collaboration. Cisco 
uses proprietary technology to collect weekly raw 
data, or “breadcrumbs,” from employees about 
their peers’ performance. Such tools enable man-
agers to see fluctuations in individual performance 
over time, even within teams. The apps don’t pro-
FALL 2019 | HBR Special Issue 15
HBR.ORG
rewards reinforce instant feedback in a powerful 
way. Annual merit-based raises are less effective, 
because too much time goes by.
Patagonia has actually eliminated annual raises 
for its knowledge workers. Instead the company 
adjusts wages for each job much more frequently, 
according to research on where market rates are 
going. Increases can also be allocated when em-
ployees take on more-difficult projects or go above 
and beyond in other ways. The company retains 
a budget for the top 1% of individual contributors, 
and supervisors can make a case for any contri-
bution that merits that designation, including 
contributions to teams.
vide an official record of performance, of course, 
and employees may want to discuss problems 
face-to-face to avoid having them recorded in a file 
that can be downloaded. We knowthat companies 
recognize and reward improvement as well as 
actual performance, however, so hiding problems 
may not always pay off for employees. 
Frontline decision rights. The fundamental shift 
toward teams has also affected decision rights: 
Organizations are pushing them down to the front 
lines, equipping and empowering employees to 
operate more independently. But that’s a huge 
behavioral change, and people need support to 
pull it off. Let’s return to the Bank of Montreal 
example to illustrate how it can work. When BMO 
introduced agile teams to design some new cus-
tomer services, senior leaders weren’t quite ready 
to give up control, and the people under them 
were not used to taking it. So the bank embedded 
agile coaches in business teams. They began by 
putting everyone, including high-level executives, 
through “retrospectives”—regular reflection and 
feedback sessions held after each iteration. These 
are the agile version of after-action reviews; their 
purpose is to keep improving processes. Because 
the retrospectives quickly identified concrete suc-
cesses, failures, and root causes, senior leaders at 
BMO immediately recognized their value, which 
helped them get on board with agile generally and 
loosen their grip on decision making. 
Complex team dynamics. Finally, since the su-
pervisor’s role has moved away from just manag-
ing individuals and toward the much more compli-
cated task of promoting productive, healthy team 
dynamics, people often need help with that, too. 
Cisco’s special Team Intelligence unit provides that 
kind of support. It’s charged with identifying the 
company’s best-performing teams, analyzing how 
they operate, and helping other teams learn how 
to become more like them. It uses an enterprise-
wide platform called Team Space, which tracks 
data on team projects, needs, and achievements to 
both measure and improve what teams are doing 
within units and across the company. 
Compensation. Pay is changing as well. A 
simple adaptation to agile work, seen in retail com-
panies such as Macy’s, is to use spot bonuses to 
recognize contributions when they happen rather 
than rely solely on end-of-year salary increases. 
Research and practice have shown that compensa-
tion works best as a motivator when it comes as 
soon as possible after the desired behavior. Instant 
The financial services division at Intuit began shifting to agile in 2009—but 
four years went by before that became standard operating procedure across 
the company. 
What took so long? Leaders started with a “waterfall” approach to change 
management, because that’s what they knew best. It didn’t work. Spotty sup-
port from middle management, part-time commitments to the team leading 
the transformation, scarce administrative resources, and an extended plan-
ning cycle all put a big drag on the rollout. 
Before agile could gain traction throughout the organization, the transition 
team needed to take an agile approach to becoming agile and managing the 
change. Looking back, Joumana Youssef, one of Intuit’s strategic-change 
leaders, identifies several critical discoveries that changed the course— 
and the speed—of the transformation: 
• Focus on early adopters. Don’t waste time trying to convert naysayers.
• Form “triple-S” (small, stable, self-managed) teams, give them ownership 
of their work, and hold them accountable for their commitments. 
• Quickly train leaders at all levels in agile methods. Agile teams need to 
be fully supported to self-manage. 
• Expect that changing frontline and middle management will be hard, 
because people in those roles need time to acclimate to “servant leader-
ship,” which is primarily about coaching and supporting employees rather 
than monitoring them.
• Stay the course. Even though agile change is faster than a waterfall 
approach, shifting your organization’s mindset takes persistence.
WHY INTUIT’S TRANSITION TO 
AGILE ALMOST STALLED OUT
16 HBR Special Issue | FALL 2019
TODAY’S TALENT MANAGEMENT HR GOES AGILE
latest engagement survey, via Culture Amp, ranks 
DigitalOcean 17 points above the industry bench-
mark in satisfaction with compensation. 
Recruiting. With the improvements in the 
economy since the Great Recession, recruiting 
and hiring have become more urgent—and more 
agile. To scale up quickly in 2015, GE’s new digital 
division pioneered some interesting recruiting 
experiments. For instance, a cross-functional 
team works together on all hiring requisitions. 
A “head count manager” represents the interests 
of internal stakeholders who want their positions 
filled quickly and appropriately. Hiring managers 
rotate on and off the team, depending on whether 
they’re currently hiring, and a scrum master over-
sees the process. 
To keep things moving, the team focuses on 
vacancies that have cleared all the hurdles—no 
req’s get started if debate is still ongoing about 
the desired attributes of candidates. Openings are 
ranked, and the team concentrates on the top-
priority hires until they are completed. It works on 
several hires at once so that members can share 
information about candidates who may fit better 
in other roles. The team keeps track of its cycle 
time for filling positions and monitors all open req-
uisitions on a kanban board to identify bottlenecks 
and blocked processes. IBM now takes a similar 
approach to recruitment. 
Companies are also relying more heavily on 
technology to find and track candidates who are 
well suited to an agile work environment. GE, IBM, 
and Cisco are working with the vendor Ascen-
dify to create software that does just this. The IT 
recruiting company HackerRank offers an online 
tool for the same purpose. 
Learning and development. Like hiring, L&D 
had to change to bring new skills into organiza-
tions more quickly. Most companies already have 
a suite of online learning modules that employees 
can access on demand. Although helpful for those 
Compensation is also being used to reinforce 
agile values such as learning and knowledge 
sharing. In the start-up world, for instance, the 
online clothing-rental company Rent the Runway 
dropped separate bonuses, rolling the money into 
base pay. CEO Jennifer Hyman reports that the bo-
nus program was getting in the way of honest peer 
feedback. Employees weren’t sharing constructive 
criticism, knowing it could have negative finan-
cial consequences for their colleagues. The new 
system prevents that problem by “untangling the 
two, ” Hyman says. 
DigitalOcean redesigned its rewards to promote 
equitable treatment of employees and a culture 
of collaboration. Salary adjustments now happen 
twice a year to respond to changes in the outside 
labor market and in jobs and performance. More 
important, DigitalOcean has closed gaps in pay 
for equivalent work. It’s deliberately heading off 
internal rivalry, painfully aware of the problems 
in hypercompetitive cultures (think Microsoft and 
Amazon). To personalize compensation, the firm 
maps where people are having impact in their 
roles and where they need to grow and develop. 
The data on individuals’ impact on the business is 
a key factor in discussions about pay. Negotiating 
to raise your own salary is fiercely discouraged. 
And only the top 1% of achievement is rewarded 
financially; otherwise, there is no merit-pay 
process. All employees are eligible for bonuses, 
which are based on company performance rather 
than individual contributions. To further support 
collaboration, DigitalOcean is diversifying its port-
folio of rewards to include nonfinancial, meaning-
ful gifts, such as a Kindle loaded with the CEO’s 
“best books” picks. 
How does DigitalOcean motivate people to per-
form their best without inflated financial rewards? 
Matt Hoffman, its vice president of people, says it 
focuses on creating a culture that inspires purpose 
and creativity. So far that seems to be working. The 
“ Upward” feedback from employees to team 
leaders is valued inagile organizations. But 
it takes work—people aren’t used to voicing 
opinions about management. 
FALL 2019 | HBR Special Issue 17
HBR.ORG
model (which is linear rather than flexible and 
adaptive), and some of them are hardwired into 
information systems, job titles, and so forth. The 
move toward cloud-based IT, which is happen-
ing independently, has made it easier to adopt 
app-based tools. But people issues remain a 
sticking point. Many HR tasks, such as traditional 
approaches to recruitment, onboarding, and pro-
gram coordination, will become obsolete, as will 
expertise in those areas. 
Meanwhile, new tasks are being created. Help-
ing supervisors replace judging with coaching 
is a big challenge not just in terms of skills but 
also because it undercuts their status and formal 
authority. Shifting the focus of management from 
individuals to teams may be even more difficult, 
because team dynamics can be a black box to 
those who are still struggling to understand how 
to coach individuals. The big question is whether 
companies can help managers take all this on and 
see the value in it. 
The HR function will also require reskilling. It 
will need more expertise in IT support—especially 
given all the performance data generated by the 
new apps—and deeper knowledge about teams 
and hands-on supervision. HR has not had to 
change in recent decades nearly as much as have 
the line operations it supports. But now the pres-
sure is on, and it’s coming from the operating level, 
which makes it much harder to cling to old talent 
practices. 
HBR Reprint R1802B
Peter Cappelli is the George W. Taylor Professor of 
Management at the Wharton School and the director 
of its Center for Human Resources. His most recent 
book is Will College Pay Off? A Guide to the Most 
Important Financial Decision You’ll Ever Make 
(PublicAffairs, 2015). Anna Tavis is a clinical associ-
ate professor of human capital management at New 
York University and the Perspectives editor at People + 
Strategy, a journal for HR executives.
who have clearly defined needs, this is a bit like 
giving a student the key to a library and telling 
her to figure out what she must know and then 
learn it. Newer approaches use data analysis to 
identify the skills required for particular jobs and 
for advancement and then suggest to individual 
employees what kinds of training and future jobs 
make sense for them, given their experience and 
interests. 
IBM uses artificial intelligence to generate such 
advice, starting with employees’ profiles, which 
include prior and current roles, expected career 
trajectory, and training programs completed. The 
company has also created special training for agile 
environments—using, for example, animated 
simulations built around a series of “personas” to 
illustrate useful behaviors, such as offering con-
structive criticism.
Traditionally, L&D has included succession 
planning—the epitome of top-down, long-range 
thinking, whereby individuals are picked years 
in advance to take on the most crucial leader-
ship roles, usually in the hope that they will 
develop certain capabilities on schedule. The 
world often fails to cooperate with those plans, 
though. Companies routinely find that by the time 
senior leadership positions open up, their needs 
have changed. The most common solution is to 
ignore the plan and start a search from scratch. 
But organizations often continue doing long-term 
succession planning anyway. (About half of large 
companies have a plan to develop successors for 
the top job.) Pepsi is one company taking a simple 
step away from this model by shortening the time 
frame. It provides brief quarterly updates on the 
development of possible successors—in contrast 
to the usual annual updates—and delays appoint-
ments so that they happen closer to when succes-
sors are likely to step into their roles. 
Ongoing Challenges 
To be sure, not every organization or group is in 
hot pursuit of rapid innovation. Some jobs must 
remain largely rules based. (Consider the work that 
accountants, nuclear control-room operators, and 
surgeons do.) In such cases agile talent practices 
may not make sense.
And even when they’re appropriate, they may 
meet resistance—especially within HR. A lot of 
processes have to change for an organization to 
move away from a planning-based, “waterfall” 
18 HBR Special Issue | FALL 2019
and the board envision a new agile, team-based 
system for deploying, developing, and assessing 
talent. (ING had already adopted agile and scrum 
methodologies in its Dutch IT unit, but those 
ways of working were new to other parts of the 
organization.) Hamers and his leadership team 
then met with people at tech companies they ad-
mired, learning how their talent systems enabled 
better customer service. By the spring of 2015 the 
headquarters of ING Netherlands, home to some 
3,500 full-time employees, had replaced most of 
its traditional structure with a fluid, agile organiza-
tion composed of tribes, squads, and chapters. 
Thirteen tribes were created to address specific 
domains, such as mortgage services, securities, 
and private banking. Each tribe contains up to 150 
people. (Employees in sales, service, and support 
functions work outside this structure—in smaller 
customer-loyalty teams, for instance—but they 
collaborate with the tribes.) And each has a lead 
who establishes priorities, allocates budgets, and 
ensures that knowledge and insights are shared 
both within and across tribes. 
The tribe lead has one other critical responsibil-
ity: to create, with input from tribe members, self-
steering squads of nine or fewer people to address 
specific customer needs by delivering and main-
taining new products and services. These squads 
are cross-disciplinary—typically, a mix of market-
ing specialists, data analysts, user-experience 
W HEN WEB AND mobile 
technologies disrupted 
the banking industry, 
consumers became 
more and more aware of 
what they could do for 
themselves. They quickly embraced what Ralph 
Hamers, CEO of the global banking group ING, 
calls “banking on the go.” 
By 2014 about 40% of all interactions with ING 
retail customers were coming in through mobile 
apps. (Now the figure is closer to 60%—and branch 
visits and calls to contact centers have dropped 
below 1%.)Even then mobile customers expected 
easy access to up-to-date information when-
ever and wherever they logged in. For instance, 
someone who started a loan transaction during 
the train ride home from work wanted to be able to 
continue it on a desktop that night. “Our custom-
ers were spending most of their online time on 
platforms like Facebook and Netflix,” says Hamers. 
“Those set the standard for user experience.” 
That meant ING needed to become nimbler and 
more user-focused to serve its 30 million–plus 
customers across the world at every point in their 
financial journeys. So Hamers worked with Nick 
Jue, then the CEO of ING’s Netherlands group, to 
launch a pilot transformation in the headquarters 
of ING’s largest unit, its Dutch retail operations. 
The first step was to help other senior leaders 
One Bank’s 
Agile Team 
Experiment
How ING revamped its retail operation 
by Dominic Barton, Dennis Carey, and Ram Charan
Originally published in 
March–April 2018
TODAY’S TALENT MANAGEMENT
FALL 2019 | HBR Special Issue 19
HBR.ORG
Agile coach
Works with individuals 
and squads on 
collaboration and 
iterative problem 
solving
Tribe lead
Establishes 
priorities, 
allocates budgets, 
and coordinates 
with other tribes to 
ensure knowledge 
sharing
Product owner
Squad member 
(but not leader); 
coordinates squad 
activities and 
sets priorities
Chapter lead
Oversees coaching 
and performance 
management; 
responsible for 
tracking and sharing 
best practices
Chapter
The members 
of a given 
discipline, 
such as UX or 
data analytics; 
they develop 
expertise and 
knowledge 
across squads
Tribe
A collection ofsquads focused on the same domain— 
for instance, private banking or mortgage services
Squad
A self-steering, cross-
functional group of 
nine or fewer people 
charged with meeting 
a specific customer 
need; either disbands 
when that need has 
been addressed or 
turns to a new one
ING’s new agile system for deploying talent and managing performance organizes 
people by domain, customer need, and function. After experimenting with this 
structure in its Dutch retail unit, the company decided to roll it out more broadly.
Tribes, Squads, and Chapters
SOURCE ING
20 HBR Special Issue | FALL 2019
continue to improve the product for our custom-
ers, or if they want to ‘fail fast.’” (Learning from 
failure is applauded.) Squads also do a thorough 
self-assessment after completing any engagement, 
and tribes perform quarterly business reviews 
(QBRs), looking at their biggest successes and 
failures, reviewing their most important learnings, 
and articulating goals for the next three months.
These safeguards help counter what Vincent 
van den Boogert, the current CEO of ING Nether-
lands (and part of the team that launched the new 
organizational structure), sees as the two biggest 
challenges of a squad-based system. One is the 
possibility that self-empowered squads respond-
ing primarily to the needs of customers might em-
bark on changes that aren’t in sync with company 
strategy. The QBRs mitigate that risk. The second 
challenge is somewhat counterintuitive. Self-
evaluating squads are sometimes content with the 
incremental improvements they make every two 
weeks. The QBRs help in that regard, too, because 
top management uses them to formulate and 
reinforce stretch goals. 
More than two years in, Hamers considers the 
talent experiment a big success. Customer satis-
faction and employee engagement are both up, 
and ING is quicker to market with new products. 
So the bank has started to roll out this new way of 
working to the roughly 40,000 employees outside 
its home country. For Hamers, the change can’t 
come soon enough. The apps for each of ING’s 
13 retail markets vary in appearance, design, and 
function. Hamers wants to make things much 
simpler so that any customer, anywhere, will en-
counter the same ING. “Tech companies have one 
platform across the globe,” he says. “No matter 
where you use Netflix, Facebook, or Google, you 
get the same service. ING must do the same. That 
is the only way we will bring all our customers 
along into the future of banking.” 
HBR Reprint R1802B
Dominic Barton is a senior partner at McKinsey & 
Company. Dennis Carey is the vice chairman of Korn 
Ferry. Ram Charan has been an adviser to the CEOs 
of some of the world’s biggest corporations and their 
boards. They are the coauthors of Talent Wins: The New 
Playbook for Putting People First (Harvard Business 
Review Press, 2018).
designers, IT engineers, and product specialists. 
One squad member is designated the “product 
owner,” responsible for coordinating activities and 
setting priorities. The squad stays together as long 
as is required to meet the customer need from 
start to finish—whether it is, for example, improv-
ing user experience on the mobile app or building 
a particular feature. Some tasks are completed in 
two weeks; others might take 18 months. Some-
times the squads disband and the members join 
other ones. Most often, however, squads that are 
working well stay together and move on to address 
other customer needs. 
By working in such small units and with 
colleagues from various disciplines, squad 
members can quickly resolve issues that might 
previously have bounced from department to 
department. Information sharing is encouraged 
through mechanisms such as scrums and daily 
stand-ups—the kinds of gatherings you’d find 
at a tech start-up. Seeing a project through from 
start to finish gives each squad a sense of owner-
ship and connection to the customer. 
Implementing an agile talent system doesn’t 
mean embracing chaos. In fact, a system that’s 
well designed observes clearly defined rules and 
safeguards to ensure institutional stability. Every 
tribe, for example, has a couple of agile coaches to 
help squads and individuals collaborate effectively 
in an environment where employees are encour-
aged to solve problems on the ground rather than 
pass them on to someone else. Although you 
might think adapting would be most difficult for 
long-term bank employees, that’s not so, accord-
ing to ING Netherlands CIO Peter Jacobs. Many of 
them “adapted even more quickly and more read-
ily than the younger generation,” he says, perhaps 
because their expertise now has more impact than 
in the past, when so many sign-offs were required. 
Then there are the chapters, which coordinate 
members of the same discipline—data analyt-
ics, say, or systems processes—who are scattered 
among squads. Chapter leads are responsible for 
tracking and sharing best practices and for such 
things as professional development and perfor-
mance reviews. Think of chapters as a way of 
retaining the helpful parts of traditional manage-
ment even while dispensing with time-consuming 
handoffs and bureaucracy.
Regular assessments are built into the system. 
Every two weeks squads review their work. Says 
Hamers, “They get to decide how they will 
Working in small, 
cross-functional 
units, squads can 
resolve issues far 
more quickly than 
in the past.
TODAY’S TALENT MANAGEMENT ONE BANK’S AGILE TEAM EXPERIMENT
© 2019 OPTUM, INC. ALL RIGHTS RESERVED.
At Optum, we collaborate and partner deeply, driven by a shared 
vision of health care that works better for everyone.
 OPTUM.COM
WE KNOW HOW. WE ARE THE HOW.
HOW DOES SHARED 
HEALTH CARE INTELLIGENCE 
 SPARK BRILLIANT SOLUTIONS?
ILLUSTRATION BY LLOYD MILLER FALL 2019 | HBR Special Issue 23
A T DELOITTE we’re redesigning 
our performance management 
system. This may not surprise 
you. Like many other compa-
nies, we realize that our current 
process for evaluating the work 
of our people—and then training them, promoting 
them, and paying them accordingly—is increas-
ingly out of step with our objectives. 
In a public survey Deloitte conducted recently, 
more than half the executives questioned (58%) 
believe that their current performance manage-
ment approach drives neither employee engage-
ment nor high performance. They, and we, are in 
need of something nimbler, real-time, and more 
individualized— something squarely focused on 
fueling performance in the future rather than as-
sessing it in the past. 
What might surprise you, however, is what 
we’ll include in Deloitte’s new system and what 
we won’t. It will have no cascading objectives, 
no once-a-year reviews, and no 360-degree-
feedback tools. We’ve arrived at a very different 
and much simpler design for managing people’s 
Reinventing 
Performance 
Management
How one company is rethinking peer feedback and the annual review, and trying to 
design a system to fuel improvement by Marcus Buckingham and Ashley Goodall
TODAY’S TALENT MANAGEMENT
Originally published in 
April 2015
24 HBR Special Issue | FALL 2019
TODAY’S TALENT MANAGEMENT REINVENTING PERFORMANCE MANAGEMENT
performance. Its hallmarks are speed, agility, 
one-size-fits-one, and constant learning, and it’s 
underpinned by a new way of collecting reliable 
performance data. This system will make much 
more sense for our talent-dependent business. But 
we might never have arrived at its design without 
drawing on three pieces of evidence: a simple 
counting of hours, a review of research in the sci-
ence of ratings, and a carefully controlled study 
of our own organization.
Counting and the Case for Change
More than likely, the performance manage-
ment system Deloitte has been using has some 
characteristics in common with yours. Objectives 
are set for each of our 65,000-plus people at the 
beginning of the year; after a project is finished, 
each person’s manager rates himor her on how 
well those objectives were met. The manager 
also comments on where the person did or didn’t 
excel. These evaluations are factored into a single 
year-end rating, arrived at in lengthy “consensus 
meetings” at which groups of “counselors” dis-
cuss hundreds of people in light of their peers. 
Internal feedback demonstrates that our people 
like the predictability of this process and the fact 
that because each person is assigned a counselor, 
he or she has a representative at the consensus 
meetings. The vast majority of our people believe 
the process is fair. We realize, however, that it’s 
no longer the best design for Deloitte’s emerging 
needs: Once-a-year goals are too “batched” for a 
real-time world, and conversations about year-end 
ratings are generally less valuable than conver-
sations conducted in the moment about actual 
performance. 
But the need for change didn’t crystallize until 
we decided to count things. Specifically, we tallied 
the number of hours the organization was spend-
ing on performance management—and found that 
completing the forms, holding the meetings, and 
creating the ratings consumed close to 2 million 
hours a year. As we studied how those hours were 
spent, we realized that many of them were eaten 
up by leaders’ discussions behind closed doors 
about the outcomes of the process. We wondered 
if we could somehow shift our investment of time 
from talking to ourselves about ratings to talk-
ing to our people about their performance and 
careers—from a focus on the past to a focus on 
the future. 
The Science of Ratings
Our next discovery was that assessing someone’s 
skills produces inconsistent data. Objective 
as I may try to be in evaluating you on, say, strate-
gic thinking, it turns out that how much strategic 
thinking I do, or how valuable I think strategic 
think ing is, or how tough a rater I am significantly 
affects my assessment of your strategic thinking. 
How significantly? The most comprehensive 
research on what ratings actually measure was 
conducted by Michael Mount, Steven Scullen, 
and Maynard Goff and published in the Journal of 
Applied Psychology in 2000. Their study—in which 
4,492 managers were rated on certain performance 
dimensions by two bosses, two peers, and two 
subordinates—revealed that 62% of the variance 
in the ratings could be accounted for by individual 
raters’ peculiarities of perception. Actual perfor-
mance accounted for only 21% of the variance. 
This led the researchers to conclude (in How People 
Evaluate Others in Organizations, edited by Manuel 
London): “Although it is implicitly assumed that 
the ratings measure the performance of the ratee, 
most of what is being measured by the ratings is 
the unique rating tendencies of the rater. Thus 
ratings reveal more about the rater than they do 
about the ratee.” This gave us pause. We wanted 
to understand performance at the individual level, 
and we knew that the person in the best position 
to judge it was the immediate team leader. But 
how could we capture a team leader’s view of 
performance without running afoul of what the 
researchers termed “idiosyncratic rater effects”?
Putting Ourselves 
Under the Microscope
We also learned that the defining characteristic 
of the very best teams at Deloitte is that they are 
strengths oriented. Their members feel that they 
are called upon to do their best work every day. 
This discovery was not based on intuitive judg-
ment or gleaned from anecdotes and hearsay; 
rather, it was derived from an empirical study 
of our own high-performing teams.
Our study built on previous research. Starting 
in the late 1990s, Gallup performed a multiyear 
examination of high-performing teams that even-
tually involved more than 1.4 million employees, 
50,000 teams, and 192 organizations. Gallup asked 
both high- and lower-performing teams questions 
on numerous subjects, from mission and purpose 
We tallied the 
number of hours 
the organization 
was spending 
on performance 
management 
and found that 
creating the ratings 
consumed close 
to 2 million hours 
a year.
FALL 2019 | HBR Special Issue 25
HBR.ORG
Idea 
in Brief
THE PROBLEM
Not just employees but their 
managers and even HR depart-
ments are by now questioning the 
conventional wisdom of perfor-
mance management, including its 
common reliance on cascading 
objectives, backward-looking as-
sessments, once-a-year rankings 
and reviews, and 360-degree-
feedback tools.
THE GOAL 
Some companies have ditched 
the rankings and even annual 
reviews, but they haven’t found 
better solutions. Deloitte 
resolved to design a system that 
would fairly recognize varying 
performance, have a clear view 
into performance anytime, and 
boost performance in the future.
THE SOLUTION 
Deloitte’s new approach sepa-
rates compensation decisions 
from day-to-day performance 
management, produces better 
insight through quarterly or per-
project “performance snapshots,” 
and relies on weekly check-ins 
with managers to keep perfor-
mance on course. 
to pay and career opportunities, and isolated the 
questions on which the high-performing teams 
strongly agreed and the rest did not. It found at the 
beginning of the study that almost all the variation 
between high- and lower-performing teams was 
explained by a very small group of items. The most 
powerful one proved to be “At work, I have the op-
portunity to do what I do best every day.” Business 
units whose employees chose “strongly agree” 
for this item were 44% more likely to earn high 
customer satisfaction scores, 50% more likely to 
have low employee turnover, and 38% more likely 
to be productive. 
We set out to see whether those results held at 
Deloitte. First we identified 60 high-performing 
teams, which involved 1,287 employees and repre-
sented all parts of the organization. For the control 
group, we chose a representative sample of 1,954 
employees. To measure the conditions within a 
team, we employed a six-item survey. When the 
results were in and tallied, three items correlated 
best with high performance for a team: “My 
coworkers are committed to doing quality work,” 
“The mission of our company inspires me,” and 
“I have the chance to use my strengths every day.” 
Of these, the third was the most powerful across 
the organization.
All this evidence helped bring into focus the 
problem we were trying to solve with our new de-
sign. We wanted to spend more time helping our 
people use their strengths—in teams characterized 
by great clarity of purpose and expectations—and 
we wanted a quick way to collect reliable and dif-
ferentiated performance data. With this in mind, 
we set to work.
Radical Redesign 
We began by stating as clearly as we could what 
performance management is actually for, at least 
as far as Deloitte is concerned. We articulated 
three objectives for our new system. The first was 
clear: It would allow us to recognize performance, 
particularly through variable compensation. Most 
current systems do this. 
But to recognize each person’s performance, 
we had to be able to see it clearly. That became 
our second objective. Here we faced two issues— 
the idiosyncratic rater effect and the need to 
streamline our traditional process of evaluation, 
project rating, consensus meeting, and final 
rating. The solution to the former requires a 
subtle shift in our approach. Rather than asking 
more people for their opinion of a team member 
(in a 360-degree or an upward-feedback survey, 
for example), we found that we will need to ask 
only the immediate team leader—but, critically, 
to ask a different kind of question. People may 
rate other people’s skills inconsistently, but they 
are highly consistent when rating their own feel-
ings and intentions. To see performance at the 
individual level, then, we will ask team leaders 
not about the skills of each team member but 
about their own future actions with respect to 
that person. 
At the end of every project(or once every quar-
ter for long-term projects) we will ask team leaders 
to respond to four future- focused statements 
about each team member. We’ve refined the word-
ing of these statements through successive tests, 
and we know that at Deloitte they clearly highlight 
differences among individuals and reliably mea-
sure performance. Here are the four:
1. Given what I know of this person’s performance, 
and if it were my money, I would award this person 
the highest possible compensation increase and 
bonus [measures overall performance and unique 
value to the organization on a five-point scale from 
“strongly agree” to “strongly disagree”].
2. Given what I know of this person’s perfor-
mance, I would always want him or her on my 
team [measures ability to work well with others 
on the same five-point scale].
3. This person is at risk for low performance 
[identifies problems that might harm the 
customer or the team on a yes-or-no basis].
4. This person is ready for promotion today 
[measures potential on a yes-or-no basis].
In effect, we are asking our team leaders what 
they would do with each team member rather 
than what they think of that individual. When we 
aggregate these data points over a year, weight-
ing each according to the duration of a given 
project, we produce a rich stream of information 
for leaders’ discussions of what they, in turn, will 
do—whether it’s a question of succession plan-
ning, development paths, or performance-pattern 
analysis. Once a quarter the organization’s leaders 
can use the new data to review a targeted subset 
In effect, we are 
asking our team 
leaders what they 
would do with 
each team member 
rather than what 
they think of that 
individual.
26 HBR Special Issue | FALL 2019
TODAY’S TALENT MANAGEMENT REINVENTING PERFORMANCE MANAGEMENT
course correction, coaching, or important new 
information. The conversations provide clarity 
regarding what is expected of each team member 
and why, what great work looks like, and how each 
can do his or her best work in the upcoming days—
in other words, exactly the trinity of purpose, 
expectations, and strengths that characterizes our 
best teams. 
Our design calls for every team leader to check 
in with each team member once a week. For us, 
these check-ins are not in addition to the work of a 
team leader; they are the work of a team leader. If 
a leader checks in less often than once a week, the 
team member’s priorities may become vague and 
aspirational, and the leader can’t be as helpful— 
and the conversation will shift from coaching for 
near-term work to giving feedback about past 
performance. In other words, the content of these 
conversations will be a direct outcome of their 
frequency: If you want people to talk about how to 
do their best work in the near future, they need to 
talk often. And so far we have found in our testing 
a direct and measurable correlation between the 
frequency of these conversations and the engage-
ment of team members. Very frequent check-ins 
(we might say radically frequent check-ins) are a 
team leader’s killer app.
That said, team leaders have many demands 
on their time. We’ve learned that the best way to 
ensure frequency is to have check-ins be initiated 
by the team member—who more often than not 
is eager for the guidance and attention they pro-
vide—rather than by the team leader. 
To support both people in these conversa-
tions, our system will allow individual members 
to understand and explore their strengths using 
a self-assessment tool and then to present those 
strengths to their teammates, their team leader, 
and the rest of the organization. Our reasoning 
is twofold. First, as we’ve seen, people’s strengths 
generate their highest performance today and 
the greatest improvement in their performance 
tomorrow, and so deserve to be a central focus. 
Second, if we want to see frequent (weekly!) use 
of our system, we have to think of it as a consumer 
technology—that is, designed to be simple, quick, 
and above all engaging to use. Many of the suc-
cessful consumer technologies of the past several 
years (particularly social media) are sharing 
technologies, which suggests that most of us 
are consistently interested in ourselves—our 
own insights, achievements, and impact. So 
of employees (those eligible for promotion, for 
example, or those with critical skills) and can 
debate what actions Deloitte might take to better 
develop that particular group. In this aggregation 
of simple but powerful data points, we see the 
possibility of shifting our 2-million-hour annual 
investment from talking about the ratings to talk-
ing about our people—from ascertaining the facts 
of performance to considering what we should do 
in response to those facts. 
In addition to this consistent—and countable—
data, when it comes to compensation, we want 
to factor in some uncountable things, such as the 
difficulty of project assignments in a given year 
and contributions to the organization other than 
formal projects. So the data will serve as the start-
ing point for compensation, not the ending point. 
The final determination will be reached either by a 
leader who knows each individual personally or by 
a group of leaders looking at an entire segment of 
our practice and at many data points in parallel.
We could call this new evaluation a rating, but 
it bears no resemblance, in generation or in use, 
to the ratings of the past. Because it allows us to 
quickly capture performance at a single moment 
in time, we call it a performance snapshot.
The Third Objective 
Two objectives for our new system, then, were 
clear: We wanted to recognize performance, 
and we had to be able to see it clearly. But all our 
research, all our conversations with leaders on the 
topic of performance management, and all the 
feedback from our people left us convinced that 
something was missing. Is performance manage-
ment at root more about “management” or about 
“performance”? Put differently, although it may 
be great to be able to measure and reward the per-
formance you have, wouldn’t it be better still 
to be able to improve it?
Our third objective therefore became to fuel 
performance. And if the performance snapshot 
was an organizational tool for measuring it, we 
needed a tool that team leaders could use to 
strengthen it.
Research into the practices of the best team 
leaders reveals that they conduct regular check-
ins with each team member about near-term 
work. These brief conversations allow leaders to 
set expectations for the upcoming week, review 
priorities, comment on recent work, and provide 
In the end, it’s 
not the particular 
number we assign 
to a person that’s 
the problem; rather, 
it’s the fact that 
there is a single 
number. 
FALL 2019 | HBR Special Issue 27
HBR.ORG
In an early proof of concept of the redesigned system, executives in one large practice area at Deloitte 
called up data from project managers to consider important talent-related decisions. In the charts below, 
each dot represents an individual; decision makers could click on a dot to see the person’s name and 
details from his or her “performance snapshots.”
 
 
HOW WOULD IT HELP ADDRESS
LOW PERFORMANCE?
This view was filtered to show individuals whose 
team leaders responded “yes” to the statement 
“This person is at risk of low performance.” As 
the upper right of this screen shows, even high 
performers can slip up—and it’s important that 
the organization help them recover.
 
 
HOW WOULD IT HELP
GUIDE PROMOTIONS?
This view was filtered to show individuals 
whose team leaders responded “yes” to
the statement “This person is ready for
promotion today.” The data supports
objectivity in annual executive discussions 
about advancement.
WHAT ARE TEAM LEADERS TELLING US?
First the group looked at the whole story. This 
view plotted all the members of the practice
according to how much their various project 
managers agreed with twostatements: “I would 
always want this person on my team” (y axis) 
and “I would give this person the highest
possible compensation” (x axis). The axes
are the same for the other three screens.
Level 6
Level 5
Level 4
Level 3
Level 2
Level 1
5
5
4
4
3
3
2
2
1
1
5
5
4
4
3
3
2
2
1
1
5
5
4
4
3
3
2
2
1
1
5
5
4
4
3
3
2
2
1
1
HOW WOULD THIS DATA
HELP DETERMINE PAY?
Next the data was filtered to look only at
individuals at a given job level. A fundamental 
question for performance management systems 
is whether they can capture enough variation 
among people to fairly allocate pay. A data
distribution like this offers a starting point
for broader discussion.
Level 4
Performance Intelligence
Candidate
for accelerated
promotion
But may
not be eligible
this year
Tracking toward
promotion
Confirm eligibility 
according to
work history and
other metrics
Team leaders’
scores vary
significantly
Investigate
discrepancies
Not performing
to expectations
Work style is
disruptive to
the team—start
remediation
A blip in otherwise
high performance 
May need clarity on 
new responsibilities—
address through 
coaching
SOURCE DELOITTE
28 HBR Special Issue | FALL 2019
TODAY’S TALENT MANAGEMENT REINVENTING PERFORMANCE MANAGEMENT
One of the most important tools in our redesigned performance management 
system is the “performance snapshot.” It lets us see performance quickly and 
reliably across the organization, freeing us to spend more time engaging with 
our people. Here’s how we created it.
1 The Criteria
We looked for measures that met 
three criteria. To neutralize the idiosyn-
cratic rater effect, we wanted raters to rate 
their own actions, rather than the qualities 
or behaviors of the ratee. To generate the 
necessary range, the questions had to be 
phrased in the extreme. And to avoid confu-
sion, each one had to contain a single, easily 
understood concept. We chose one about 
pay, one about teamwork, one about poor 
performance, and one about promotion. 
Those categories may or may not be right for 
other organizations, but they work for us. 
2 T he Rater
We were looking for someone with 
vivid experience of the individual’s 
performance and whose subjective judg-
ment we felt was important. We agreed that 
team leaders are closest to the performance 
of ratees and, by virtue of their roles, must 
exercise subjective judgment. We could have 
included functional managers, or even ratees’ 
peers, but we wanted to start with clarity 
and simplicity. 
3 Testing 
We then tested that our questions 
would produce useful data. Validity 
testing focuses on their difficulty (as revealed 
by mean responses) and the range of re-
sponses (as revealed by standard deviations). 
We knew that if they consistently yielded a 
tight cluster of “strongly agree” responses, 
we wouldn’t get the differentiation we were 
looking for. Construct validity and criterion-
related validity are also important. (That 
is, the questions should collectively test an 
underlying theory and make it possible to 
find correlations with outcomes measured in 
other ways, such as engagement surveys.) 
4 Frequency
At Deloitte we live and work in 
a project structure, so it makes 
sense for us to produce a performance snap-
shot at the end of each project. For longer-
term projects we’ve decided that quarterly 
is the best frequency. Our goal is to strike 
the right balance between tying the evalua-
tion as tightly as possible to the experience 
of the performance and not overburdening 
our team leaders, lest survey fatigue yield 
poor data. 
5 Transparency
We’re experimenting with this now. 
We want our snapshots to reveal the 
real-time “truth” of what our team leaders 
think, yet our experience tells us that if they 
know that team members will see every data 
point, they may be tempted to sugarcoat the 
results to avoid difficult conversations. We 
know that we’ll aggregate an individual’s 
snapshot scores into an annual composite. 
But what, exactly, should we share at year’s 
end? We want to err on the side of shar-
ing more, not less—to aggregate snapshot 
scores not only for client work but also for 
internal projects, along with performance 
metrics such as hours and sales, in the con-
text of a group of peers—so that we can give 
our people the richest possible view of where 
they stand. Time will tell how close to that 
ideal we can get. 
HOW DELOITTE BUILT A RADICALLY 
SIMPLE PERFORMANCE MEASURE
FALL 2019 | HBR Special Issue 29
HBR.ORG
consider your compensation or your career. And 
these conversations are best served not by a single 
data point but by many. If we want to do our best 
to tell you where you stand, we must capture as 
much of your diversity as we can and then talk 
about it.
We haven’t resolved this issue yet, but here’s 
what we’re asking ourselves and testing: What’s 
the most detailed view of you that we can gather 
and share? How does that data support a conversa-
tion about your performance? How can we equip 
our leaders to have insightful conversations? Our 
question now is not What is the simplest view of 
you? but What is the richest?
OVER THE PAST few years the debate about per-
formance management has been characterized as 
a debate about ratings—whether or not they are 
fair, and whether or not they achieve their stated 
objectives. But perhaps the issue is different: not 
so much that ratings fail to convey what the orga-
nization knows about each person but that as pre-
sented, that knowledge is sadly one- dimensional. 
In the end, it’s not the particular number we 
assign to a person that’s the problem; rather, it’s 
the fact that there is a single number. Ratings are 
a distillation of the truth—and up until now, one 
might argue, a necessary one. Yet we want our 
organizations to know us, and we want to know 
ourselves at work, and that can’t be compressed 
into a single number. We now have the technology 
to go from a small data version of our people to 
a big data version of them. As we scale up our 
new approach across Deloitte, that’s the issue 
we want to solve next. 
HBR Reprint R1504B
Marcus Buckingham is the head of People + 
Performance research at the ADP Research Institute. 
Ashley Goodall is the senior vice president of leader-
ship and team intelligence at Cisco Systems. They are 
the authors of Nine Lies About Work: A Freethinking 
Leader’s Guide to the Real World (Harvard Business 
Review Press, 2019).
we want this new system to provide a place for 
people to explore and share what is best about 
themselves.
Transparency
This is where we are today: We’ve defined 
three objectives at the root of performance 
management— to recognize, see, and fuel per-
formance. We have three interlocking rituals to 
support them—the annual compensation decision, 
the quarterly or per-project performance snap-
shot, and the weekly check-in. And we’ve shifted 
from a batched focus on the past to a continual 
focus on the future, through regular evaluations 
and frequent check-ins. As we’ve tested each 
element of this design with ever-larger groups 
across Deloitte, we’ve seen that the change can be 
an evolution over time: Different business units 
can introduce a strengths orientation first, then 
more-frequent conversations, then new ways of 
measuring, and finally new software for monitor-
ing performance. (See the exhibit “Performance 
Intelligence.”)
But one issue has surfaced again and again dur-
ing this work, and that’s the issue of transparency. 
When an organization knows something about us, 
and that knowledge is captured in a number, we 
often feel entitled to know it—to know where 
we stand. We suspect that this issue will need its 
own radical answer. 
In the first version of our design, we kept the 
results of performance snapshots from the team 
member. We did this because we knew from the 
past that when an evaluation is to be shared, 
the responses skew high—that is, they are sugar-
coated. Becausewe wanted to capture unfiltered 
assessments, we made the responses private. We 
worried that otherwise we might end up destroy-
ing the very truth we sought to reveal. 
But what, in fact, is that truth? What do we see 
when we try to quantify a person? In the world of 
sports, we have pages of statistics for each player; 
in medicine, a three-page report each time we get 
blood work done; in psychometric evaluations, 
a battery of tests and percentiles. At work, how-
ever, at least when it comes to quantifying perfor-
mance, we try to express the infinite variety and 
nuance of a human being in a single number. 
Surely, however, a better understanding comes 
from conversations—with your team leader about 
how you’re doing, or between leaders as they 
Our question now 
is not What is the 
simplest view of 
you? but What is 
the richest?
low performers. Other examples, such as Dell’s 
experiments with increasing the success of its 
sales force, also point to the power of people 
analytics.
But hype, as it often does, has outpaced real-
ity. The truth is, people analytics has made only 
modest progress over the past decade. A survey 
by Tata Consultancy Services found that just 5% 
of big-data investments go to HR, the group that 
typically manages people analytics. And a recent 
study by Deloitte showed that although people 
analytics has become mainstream, only 9% of 
companies believe they have a good understand-
ing of which talent dimensions drive perfor-
mance in their organizations. 
What gives? If, as the sticker says, people ana-
lytics teams have charts and graphs to back them 
up, why haven’t results followed? We believe 
it’s because most rely on a narrow approach 
to data analysis: They use data only about indi-
vidual people, when data about the interplay 
among people is equally or more important. 
People’s interactions are the focus of an emerg-
ing discipline we call relational analytics. By 
30 HBR Special Issue | FALL 2019 ILLUSTRATION BY LLOYD MILLER 
“ We have charts and graphs to back us up. 
So f *** off.” 
NEW HIRES in Google’s people 
analytics department began re-
ceiving a laptop sticker with that 
slogan a few years ago, when the 
group probably felt it needed to 
defend its work. Back then people 
analytics—using statistical insights from employee 
data to make talent management decisions—was 
still a provocative idea with plenty of skeptics who 
feared it might lead companies to reduce individu-
als to numbers. HR collected data on workers, 
but the notion that it could be actively mined 
to understand and manage them was novel— 
and suspect.
Today there’s no need for stickers. More than 
70% of companies now say they consider people 
analytics to be a high priority. The field even has 
celebrated case studies, like Google’s Project 
Oxygen, which uncovered the practices of the 
tech giant’s best managers and then used them 
in coaching sessions to improve the work of 
Better People 
Analytics
Measure who they know, not just who they are. 
by Paul Leonardi and Noshir Contractor
Originally published in 
November–December 2018
TODAY’S TALENT MANAGEMENT
32 HBR Special Issue | FALL 2019
TODAY’S TALENT MANAGEMENT BETTER PEOPLE ANALYTICS
incorporating it into their people analytics strate-
gies, companies can better identify employees 
who are capable of helping them achieve their 
goals, whether for increased innovation, influ-
ence, or efficiency. Firms will also gain insight into 
which key players they can’t afford to lose and 
where silos exist in their organizations. 
Fortunately, the raw material for relational 
analytics already exists in companies. It’s the 
data created by email exchanges, chats, and file 
transfers—the digital exhaust of a company. By 
mining it, firms can build good relational analytics 
models. 
In this article we present a framework for un-
derstanding and applying relational analytics. And 
we have the charts and graphs to back us up.
Relational Analytics: 
A Deeper Definition
To date, people analytics has focused mostly 
on employee attribute data, of which there are 
two kinds:
• Trait: facts about individuals that don’t 
change, such as ethnicity, gender, and work 
history. 
• State: facts about individuals that do change, 
such as age, education level, company tenure, 
value of received bonuses, commute distance, 
and days absent.
The two types of data are often aggregated 
to identify group characteristics, such as 
ethnic makeup, gender diversity, and average 
compensation. 
Attribute analytics is necessary but not suf-
ficient. Aggregate attribute data may seem like 
relational data because it involves more than 
one person, but it’s not. Relational data captures, 
for example, the communications between two 
people in different departments in a day. In short, 
relational analytics is the science of human social 
networks. 
Decades of research convincingly show that the 
relationships employees have with one another—
together with their individual attributes—can 
explain their workplace performance. The key is 
finding “structural signatures”: patterns in the 
data that correlate to some form of good (or bad) 
performance. Just as neurologists can identify 
structural signatures in the brain’s networks that 
predict bipolar disorder and schizophrenia, and 
chemists can look at the structural signatures of 
a liquid and predict its kinetic fragility, organiza-
tional leaders can look at structural signatures in 
their companies’ social networks and predict how, 
say, creative or effective individual employees, 
teams, or the organization as a whole will be.
The Six Signatures of 
Relational Analytics
Drawing from our own research and our consult-
ing work with companies, as well as from a large 
body of other scholars’ research, we have identi-
fied six structural signatures that should form the 
bedrock of any relational analytics strategy. 
Let’s look at each one in turn.
Ideation
Most companies try to identify people who are 
good at ideation by examining attributes like 
educational background, experience, personal-
ity, and native intelligence. Those things are 
important, but they don’t help us see people’s 
access to information from others or the diver-
sity of their sources of information—both of 
which are arguably even more important. Good 
Most people 
analytics teams 
rely on a narrow 
approach to data 
analysis. They use 
data only about 
individual people, 
when data about 
the interplay among 
people is equally or 
more important.
Ideation Signature
FOCUS: Individual 
PREDICTS: Which employees will come up with good ideas
Purple shows low constraint: He communicates with people in several other networks besides his 
own, which makes him more likely to get novel information that will lead to good ideas. Orange, who 
communicates only with people within his network, is less likely to generate ideas, even though he 
may be creative.
FALL 2019 | HBR Special Issue 33
HBR.ORG
Idea 
in Brief
THE CHALLENGE
To bring the performance of 
people analytics up—and in line 
with the hype—companies need 
to do more than analyze data on 
demographic attributes.
THE SOLUTION
Employ relational analytics, 
which examines data on how 
people interact, to find out who 
has good ideas, who is influential, 
what teams will get work done 
on time, and more.
THE RAW MATERIAL
Companies can mine their “digi-
tal exhaust”—data created by 
employees every day in their dig-
ital transactions, such as emails, 
chats, and file collaboration—for 
insights into their workforce.
idea generators often synthesize information 
from one team with information from another 
to develop a new product concept. Or they use 
a solution created in one division to solve a 
problem in another. In other words, they occupy 
a brokerage position in networks. 
The sociologist Ronald Burt has developed 
a measure that indicates whether someone is 
in a brokerage position. Known as constraint, itcaptures how limited a person is when gather-
ing unique information. Study after study, across 
populations as diverse as bankers, lawyers, 
analysts, engineers, and software developers, has 
shown that employees with low constraint—who 
aren’t bound by a small, tight network of people—
are more likely to generate ideas that management 
views as novel and useful. 
In one study, Burt followed the senior leaders 
at a large U.S. electronics company as they applied 
relational analytics to determine which of 600-
plus supply chain managers were most likely to 
develop ideas that improved efficiency. They used 
a survey to solicit such ideas from the managers 
and at the same time gather information on their 
networks. Senior executives then scored each 
of the submitted ideas for their novelty and poten-
tial value. 
The only attribute that remotely predicted 
whether an individual would generate a valuable 
idea was seniority at the company, and its correla-
tion wasn’t strong. Using the ideation signature—
low constraint—was far more powerful: Supply 
chain managers who exhibited it in their networks 
were significantly more likely to generate good 
ideas than managers with high constraint.
A study Paul did at a large software develop-
ment company bolsters this finding. The com-
pany’s R&D department was a “caveman world.” 
Though it employed more than 100 engineers, on 
average each one talked to only five other people. 
And those five people typically talked only to 
one another. Their contact with other “caves” 
was limited. 
Such high-constraint networks are quite com-
mon in organizations, especially those that do 
specialized work. But that doesn’t mean low-
constraint individuals aren’t hiding in plain sight. 
At the software company, relational analytics was 
able to pinpoint a few engineers who did span 
multiple networks. Management then generated 
a plan for encouraging them to do what they were 
naturally inclined to, and soon saw a significant 
increase in both the quantity—and quality—of 
ideas they proposed for product improvements.
Influence
Developing a good idea is no guarantee that people 
will use it. Similarly, just because an executive 
issues a decree for change, that doesn’t mean 
employees will carry it out. Getting ideas imple-
mented requires influence. 
But influence doesn’t work the way we might 
assume. Research shows that employees are not 
most influenced, positively or negatively, by the 
company’s senior leadership. Rather, it’s people in 
less formal roles who sway them the most.
If that’s the case, executives should just identify 
the popular employees and have them persuade 
their coworkers to get on board with new initia-
tives, right? Wrong.
A large medical device manufacturer that 
Paul worked with tried that approach when it 
was launching new compliance policies. Hoping 
to spread positive perceptions about them, the 
change management team shared the policies’ 
virtues with the workers who had been rated influ-
ential by the highest number of colleagues. But 
Influence Signature
FOCUS: Individual 
PREDICTS: Which employees will change others’ behavior
Though she connects to only two people, purple is more influential than orange, because purple’s 
connections are better connected. Purple shows higher aggregate prominence. Orange may spread 
ideas faster, but purple can spread ideas further because her connections are more influential.
34 HBR Special Issue | FALL 2019
TODAY’S TALENT MANAGEMENT BETTER PEOPLE ANALYTICS
to them as well as to the influencers who didn’t 
like the policies—and then waited for the results. 
Six months later more than 75% of the em-
ployees in those nine divisions had adopted 
the new compliance policies. In contrast, only 
15% of employees had adopted them in the 
remaining seven affected divisions, where rela-
tional analytics had not been applied.
Efficiency
Staffing a team that will get work done efficiently 
seems as if it should be simple. Just tap the people 
who have the best relevant skills. 
Attribute analytics can help identify skilled 
people, but it won’t ensure that the work gets done 
on time. For that, you need relational analytics 
measuring team chemistry and the ability to draw 
on outside information and expertise.
Consider the findings of a study by Ray 
Reagans, Ezra Zuckerman, and Bill McEvily, 
which analyzed more than 1,500 project teams 
at a major U.S. contract R&D firm. Hypothesiz-
ing that the ability to access a wide range of 
information, perspectives, and resources would 
improve team performance, the researchers 
compared the effect of demographic diversity on 
teams’ results with the effect of team members’ 
social networks. One issue was that diversity at 
the firm had only two real variables, tenure and 
function. (The other variables—race, gender, 
and education—were consolidated within func-
tions.) Nevertheless, the results showed that 
diversity in those two areas had little impact 
on performance. 
Turning to the relational data, though, of-
fered better insight. The researchers found that 
two social variables were associated with higher 
performance. The first was internal density, the 
amount of interaction and interconnectedness 
among team members. High internal density is 
critical for building trust, taking risks, and reaching 
agreement on important issues. The second was 
the external range of team members’ contacts. On 
a team that has high external range, each mem-
ber can reach outside the team to experts who 
are distinct from the contacts of other members. 
That makes the team better able to source vital 
information and secure resources it needs to meet 
deadlines. The structural signature for efficient 
teams is therefore high internal density plus high 
external range.
six months later employees still weren’t following 
the new procedures.
Why? A counterintuitive insight from relational 
analytics offers the explanation: Employees cited 
as influential by a large number of colleagues 
aren’t always the most influential people. Rather, 
the greatest influencers are people who have 
strong connections to others, even if only to a few 
people. Moreover, their strong connections in turn 
have strong connections of their own with other 
people. This means influencers’ ideas can spread 
further. 
The structural signature of influence is called 
aggregate prominence, and it’s computed by 
measuring how well a person’s connections are 
connected, and how well the connections’ con-
nections are connected. (A similar logic is used by 
search engines to rank-order search results.)
In each of nine divisions at the medical device 
manufacturer, relational analytics identified 
the five individuals who had the highest ag-
gregate prominence scores. The company asked 
for their thoughts on the new policies. About 
three- quarters viewed them favorably. The firm 
provided facts that would allay fears of the change 
Efficiency Signature
FOCUS: Team 
PREDICTS: Which teams will complete projects on time
The purple team members are deeply connected with one another—showing high internal density. 
This indicates that they work well together. And because members’ external connections don’t over-
lap, the team has high external range, which gives it greater access to helpful outside resources.
Influence doesn’t 
work the way we 
might assume. 
Research shows 
that employees are 
not most influenced 
by the company’s 
senior leadership. 
Rather, it’s people 
in less formal roles 
who sway them 
the most.
FALL 2019 | HBR Special Issue 35
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At the R&D firm the teams that had this sig-
nature completed projects much faster than 
teams that did not. The researchers estimated 
that if 30% of project teams at the firm had inter-
nal density and external range just one standard 
deviation above the mean, it would save more 
than 2,200 labor hours in 17 days—the equiva-
lent of completing nearly 200 additional 
projects.
Innovation
Teamswith the efficiency signature would most 
likely fail as innovation units, which benefit from 
some disagreement and strife.
What else makes for a successful team of 
innovators? You might think that putting your 
highest-performing employees together would 
produce the best results, but research suggests 
that it might have negative effects on perfor-
mance. And while the conventional wisdom is 
that teams are more creative when they comprise 
members with different points of view, research 
also indicates that demographic diversity is not a 
good predictor of team innovation success. In our 
experience, even staffing an innovation team with 
ideators often produces no better than average 
performance. 
But if you turn to relational analytics, you 
can use the same variables you use for team 
efficiency—internal density and external range— 
to create promising innovation teams. The 
formula is a bit different, though: The innovation 
signature is high external range and low internal 
density. That is, you still want team members 
with wide, non overlapping social networks 
(influential ones, if possible) to source diverse 
ideas and information. But you do not want 
a tight-knit team.
Why? Greater interaction within a team results 
in similar ways of thinking and less discord. That’s 
good for efficiency but not for innovation. The 
most innovative teams have disagreements and 
discussion—sometimes even conflict—that gener-
ate the creative friction necessary to produce 
breakthroughs. 
The high external range is needed not just 
to bring in ideas but also to garner support and 
buy-in. Innovation teams have to finance, build, 
and sell their ideas, so well-connected external 
contacts who become the teams’ champions can 
have a big impact on their success.
Innovation Signature
FOCUS: Team 
PREDICTS: Which teams will innovate effectively
Purple team members aren’t deeply interconnected; their team has low internal density. This sug-
gests they’ll have different perspectives and more-productive debates. The members also have high 
external range, or wide, diverse connections, which will help them gain buy-in for their innovations.
For several years, Paul worked with a large 
U.S.-based automobile company that was trying 
to improve its product- development process. 
Each of its global product- development centers 
had a team of subject-matter experts focused on 
that challenge. The program leader noted, “We 
are very careful about who we select. We get the 
people with the right functional backgrounds, 
who have consistently done innovative work, 
and we make sure there is a mix of them from 
different backgrounds and that they are different 
ages.” In other words, the centers used attribute 
analytics to form teams.
Managers at a new India center couldn’t build 
a demographically diverse team, however: All the 
center’s engineers were roughly the same age, had 
similar backgrounds, and were about the same 
rank. So the manager instead chose engineers who 
had worked on projects with different offices and 
worked in different areas of the center—creating 
a team that naturally had a higher external range. 
It so happened that such a team showed lower 
internal density as well. Its members felt free to 
debate, and they ran tests to resolve differences of 
opinion. Once they found a new procedure, they 
went back to their external connections, using 
36 HBR Special Issue | FALL 2019
TODAY’S TALENT MANAGEMENT BETTER PEOPLE ANALYTICS
communication is greater than 5:1, the group is 
detrimentally siloed.
One of the most strikingly siloed organiza-
tions we’ve encountered was a small not-for-
profit consumer advocacy group, which wanted 
to understand why traffic on its website had 
declined. The 60 employees at its Chicago office 
were divided among four departments: business 
development, operations, marketing and PR, 
and finance. Typical of silos, each department 
had different ideas about what was going on.
Analysis showed that all four departments ex-
ceeded the 5:1 ratio of internal to external contacts. 
The most extreme case was operations, with a 
ratio of 13:1. Of course, operations was the depart-
ment with its finger most squarely on the pulse of 
consumers who visited the site. It sat on a trove of 
data about when and why people came to the site 
to complain about or praise companies.
Other departments didn’t even know that op-
erations collected that data. And operations didn’t 
know that other departments might find it useful.
To fix the problem, the organization asked spe-
cific employees in each department to become li-
aisons. They instituted a weekly meeting at which 
managers from all departments got together to talk 
about their work. Each meeting was themed, so 
lower-level employees whose work related to the 
theme also were brought into the discussions.
In short, the not-for-profit engineered higher 
external range into its staff. As a result, operations 
learned that marketing and PR could make hay out 
of findings that linked a growing volume of com-
plaints in a specific industry to certain weather 
patterns and seasons. Because operations employ-
ees learned that such insights would be useful, 
they began to analyze their data in new ways.
Vulnerability
Although having people who can help move infor-
mation and insights from one part of the organiza-
tion to another is healthy, an overreliance on those 
individuals can make a company vulnerable. 
Take the case of an employee we’ll call Arvind, 
who was a manager in the packaging division at 
one of the world’s top consumer goods compa-
nies. He was a connector who bridged several 
divisions. He talked regularly with counterparts 
and suppliers across the world. But on the or-
ganizational chart, Arvind was nobody special: 
just a midlevel manager who was good at his job. 
them as influencers who could persuade others 
to validate their work.
After three years the India center’s team was 
producing more process innovations than any of 
the other teams. After five years it had generated 
almost twice as many as all the other teams com-
bined. In response, the company began supple-
menting its attribute analytics with relational 
analytics to reconfigure the innovation teams at 
its other locations.
Silos
Everyone hates silos, but they’re natural and 
unavoidable. As organizations develop deep areas 
of expertise, almost inevitably functions, depart-
ments, and divisions become less and less able to 
work together. They don’t speak the same techni-
cal language or have the same goals. 
We assess the degree to which an organiza-
tion is siloed by measuring its modularity. Most 
simply, modularity is the ratio of communica-
tion within a group to communication outside 
the group. When the ratio of internal to external 
Silo Signature
FOCUS: Organization 
PREDICTS: Whether an organization is siloed
Each color indicates a department. People within the departments are deeply connected, but 
only one or two people in any department connect with people in other departments. The groups’ 
modularity—the ratio of internal to external communication—is high.
If 30% of project 
teams at the firm 
had internal density 
and external range 
just one standard 
deviation above 
the mean, it would 
save more than 
2,200 labor hours 
in 17 days.
FALL 2019 | HBR Special Issue 37
HBR.ORG
the logs, e-trails, and contents of everyday digital 
activity. Every time employees send one another 
emails in Outlook, message one another on 
Slack, like posts on Facebook’s Workplace, form 
teams in Microsoft Teams, or assign people to 
project milestones in Trello, the platforms record 
the interactions. This information can be used to 
construct views of employee, team, and organi-
zational networks in which you can pick out the 
structural signatures we’ve discussed.
For several years we’ve been developing a dash-
board that captures digital exhaust in real time 
from these various platforms and usesrelational 
analytics to help managers find the right employ-
ees for tasks, staff teams for efficiency and innova-
tion, and identify areas in the organization that are 
siloed and vulnerable to turnover. Here are some 
of the things we’ve learned in the process: 
Passive collection is easier on employees. 
To gather relational data, companies typically 
survey employees about whom they interact with. 
Surveys take time, however, and the answers can 
Companies are at risk of losing employees like 
Arvind because no obvious attribute signals their 
importance, so firms don’t know what they’ve got 
until it’s gone.
Without Arvind, the packaging division would 
lack robustness. Networks are robust when 
connections can be maintained if you remove 
nodes—employees—from it. In this case, if 
Arvind left the company, some departments 
would lose all connection with other depart-
ments and with suppliers.
It wasn’t that Arvind was irreplaceable. He just 
wasn’t backed up. The company didn’t realize 
that no other nodes were making the necessary 
network connections he provided. That made it 
vulnerable: If Arvind was out sick or on vacation, 
work slowed. If Arvind decided that he didn’t like 
one of the suppliers and stopped interacting with 
it, work slowed. And if Arvind had too much on 
his plate and couldn’t keep up with his many con-
nections, work also slowed.
On the day Noshir came to show the company 
this vulnerability in the packaging division, he 
entered a boardroom filled with cakes and sweets. 
A senior executive happily told him that the firm 
was throwing a party for Arvind. He was retiring. 
Noshir’s jaw dropped. The party went on, but after 
learning how important Arvind was, the com-
pany worked out a deal to retain him for several 
more years and, in the meantime, used relational 
analytics to do some succession planning so that 
multiple people could take on his role.
Capture Your Company’s 
Digital Exhaust
Once you understand the six structural signa-
tures that form the basis of relational analytics, 
it’s relatively easy to act on the insights they 
provide. Often, the fixes they suggest aren’t com-
plex: Set up cross-functional meetings, enable 
influential people, retain your Arvinds.
Why, then, don’t most companies use relational 
analytics for performance management? There 
are two reasons. The first is that many network 
analyses companies do are little more than pretty 
pictures of nodes and edges. They don’t identify 
the patterns that predict performance. 
The second reason is that most organizations 
don’t have information systems in place to cap-
ture relational data. But all companies do have a 
crucial hidden resource: their digital exhaust—
Com
pany
Supplier
Vulnerability Signature
FOCUS: Organization 
PREDICTS: Which employees the organization can’t afford to lose
Green is a critical external supplier to company departments blue, purple, and orange. Six people 
at the company have relationships with green, but 30 people rely on those relationships—which 
puts the company at risk. If blue’s one connection to green leaves, for example, the department will 
be cut off from the supplier. While his title may not reflect his importance, that employee is vital to 
information flow.
38 HBR Special Issue | FALL 2019
TODAY’S TALENT MANAGEMENT BETTER PEOPLE ANALYTICS
Will we have to do it again at a cost of an additional 
$1 million in people hours?”
Company-collected relational data, however, 
creates new challenges. Although most employ-
ment contracts give firms the right to record 
and monitor activities conducted on company 
systems, some employees feel that the passive col-
lection of relational data is an invasion of privacy. 
vary in accuracy (some employees are just guess-
ing). Also, to be truly useful, relational data must 
come from everyone at the company, not just a 
few people. As an executive at a large financial ser-
vices company told us, “If I gave each of my 15,000 
employees a survey that takes half an hour to do, 
we’ve just lost a million dollars in productivity. 
And what if their relationships change in a month? 
Relational analytics changes the equation 
when it comes to the privacy of employee 
data. When employees actively provide 
information about themselves in hiring 
forms, surveys, and the like, they know their 
company has and can use it. But they may 
not even realize that the passive collection 
of relational data—such as whom they chat 
with on Slack or when they were copied on 
email—is happening or that such information 
is being analyzed.
Job one for companies is to be transpar-
ent. If they’re going to amass digital exhaust, 
they should ask employees to sign an agree-
ment indicating they understand that their 
patterns of interaction on company-owned 
tools will be tracked for the purposes of 
analyzing the organization’s social networks. 
Full disclosure with employee consent is the 
only option. 
We’ve found some additional moves 
leaders can make to get ahead of privacy 
concerns: 
First, give employees whatever relational 
data you collect about them. We recom-
mend providing it at least annually. The data 
can include a map of the employee’s own 
network and benchmarks. For example, a 
report could provide an employee with her 
constraint score (which shows how inbred 
someone’s social network is) and the average 
constraint score of employees in her depart-
ment. That score could then be at the center 
of a mentoring discussion. 
Second, be clear about the depth of 
relational analytics you intend to invest in. 
The level that is most basic—and the least 
prone to privacy concerns—is generic pattern 
analysis. The analysis might show, for exam-
ple, that marketing is a silo but not identify 
specific individuals that contribute to that 
silo. Or the analysis could show that a certain 
percentage of teams have the signature for 
innovation but not identify which teams. 
The second level identifies which spe-
cific employees in a company have certain 
kinds of networks. Scores may provide 
evidence-based predictions about employee 
behavior— such as who is likely to be an influ-
encer or whose departure would make an or-
ganization vulnerable. Although this level of 
analysis provides more value to the company, 
it singles particular employees out. 
The highest level pairs relational analyt-
ics with machine learning. In this scenario, 
companies collect data about whom employ-
ees interact with and about the topics they 
discuss. Firms examine the content of 
emails and posts on social-networking 
sites to identify who has expertise in what 
domains. This information provides the most 
specific guidance for leaders—for example, 
about who is likely to develop good ideas 
in certain areas. This most advanced level 
obviously also comes with the most privacy 
concerns, and senior leadership must de-
velop deeply considered strategies to deal 
with them.
WHAT ABOUT 
EMPLOYEE PRIVACY?
FALL 2019 | HBR Special Issue 39
HBR.ORG
moves analytic insights closer to the managers 
who need them. As one executive at a semi-
conductor chip firm told us, “I want my managers 
to have the data to make good decisions about 
how to use their employees. And I want them to be 
able to do it when those decision points happen, 
not later.”
PEOPLE ANALYTICS is a new way to make 
evidence- based decisions that improve organi-
zations. But in these early days, most companies 
have been focused on the attributes of individu-
als, rather than on their relationships with other 
employees. Looking at attributes will take firms 
only so far. If they harness relational analytics, 
however, they can estimate the likelihood that an 
employee, a team, or an entire organization will 
achieve a performance goal. They can also use 
algorithms to tailor staff assignments to changes 
in employee networks or to a particular mana-
gerial need. The best firms, of course, will use 
relational analytics to augment theirown decision 
criteria and build healthier, happier, and more- 
productive organizations. 
HBR Reprint R1806E
Paul Leonardi is the Duca Family Professor of Technol-
ogy Management at the University of California, 
Santa Barbara, and advises companies about how 
to use social network data and new technologies to 
improve performance and employee well-being. 
Twitter: @pleonardi1. Noshir Contractor is the Jane S. 
and William J. White Professor of Behavioral Sciences 
at Northwestern University, where he directs the 
Science of Networks in Communities (SONIC) group, 
which helps organizations understand and leverage 
networks. Twitter: @noshir.
This is not a trivial concern. Companies need clear 
HR policies about the gathering and analysis of 
digital exhaust that help employees understand 
and feel comfortable with it. (See the sidebar 
“What About Employee Privacy?”)
Behavioral data is a better reflection of 
reality. As we’ve noted, digital exhaust is less 
biased than data collected through surveys. For 
instance, in surveys people may list connections 
they think they’re supposed to interact with, 
rather than those they actually do interact with. 
And because every employee will be on at least 
several communication platforms, companies can 
map networks representing the entire workforce, 
which makes the analysis more accurate.
Also, not all behaviors are equal. Liking some-
one’s post is different from working on a team 
with someone for two years. Copying someone on 
an email does not indicate a strong relationship. 
How all those individual behaviors are weighted 
and combined matters. This is where machine-
learning algorithms and simulation models 
are helpful. With a little technical know-how 
(and with an understanding of which structural 
signatures predict what performance outcomes), 
setting up those systems is not hard to do. 
Constant updating is required. Relation-
ships are dynamic. People and projects come and 
go. To be useful, relational data must be timely. 
Using digital exhaust in a relational analytics 
model addresses that need. 
Additionally, collecting relational data over 
time gives analysts more choices about what to 
examine. For example, if an employee was out on 
maternity leave for several months, an analyst can 
exclude that time period from the data or decide 
to aggregate a larger swath of data. If a company 
was acquired in a particular year, an analyst can 
compare relational data from before and after the 
deal to chart how the company’s vulnerabilities 
may have changed. 
Analyses need to be close to decision 
makers. Most companies rely on data scientists 
to cull insights related to talent and performance 
management. That often creates a bottleneck, 
because there aren’t enough data scientists to ad-
dress all management queries in a timely manner. 
Plus, data scientists don’t know the employees 
they are running analyses on, so they cannot put 
results into context.
Dashboards are key. A system that identifies 
structural signatures and highlights them visually 
It wasn’t that Arvind 
was irreplaceable. 
He just wasn’t 
backed up. The 
company didn’t 
realize that no one 
else was making 
the network 
connections he 
provided. If Arvind 
was out sick or 
on vacation, work 
slowed.
ILLUSTRATION BY LLOYD MILLER FALL 2019 | HBR Special Issue 41
I WAS ONCE EVICTED from an apartment 
because I was black. I had secured a lovely 
place on the banks of Lake Geneva through 
an agent and therefore hadn’t met the 
owner in person before signing the lease. 
Once my family and I moved in and the 
color of my skin was clear to see, the landlady 
asked us to leave. If she had known that I was 
black, I was told, she would never have rented 
to me. 
Terrible as it felt at the time, her directness was 
useful to me. It meant I didn’t have to scour the 
facts looking for some other, nonracist rationale 
for her sudden rejection.
Many people have been denied housing, bank 
loans, jobs, promotions, and more because of their 
race. But they’re rarely told that’s the reason, as 
I was—particularly in the workplace. For one 
thing, such discrimination is illegal. For another, 
executives tend to think—and have a strong 
desire to believe—that they’re hiring and promot-
ing people fairly when they aren’t. (Research 
 shows that individuals who view themselves as 
Originally published in 
November–December 2017
“ Numbers 
Take Us 
Only So Far”
Facebook’s global director of diversity explains why 
stats alone won’t solve the problem of organizational 
bias. by Maxine Williams
TODAY’S TALENT MANAGEMENT
42 HBR Special Issue | FALL 2019
TODAY’S TALENT MANAGEMENT “NUMBERS TAKE US ONLY SO FAR”
objective are often the ones who apply the most 
unconscious bias.) Though managers don’t cite or 
(usually) even perceive race as a factor in their de-
cisions, they use ambiguous assessment criteria to 
filter out people who aren’t like them, research by 
Kellogg professor Lauren Rivera shows. People in 
marginalized racial and ethnic groups are deemed 
more often than whites to be “not the right 
cultural fit” or “not ready” for high-level roles; 
they’re taken out of the running because their 
“communication style” is somehow off the mark. 
They’re left only with lingering suspicions that 
their identity is the real issue, especially when de-
cision makers’ bias is masked by good intentions. 
I work in the field of diversity. I’ve also been 
black my whole life. So I know that under-
represented people in the workplace yearn for 
two things: The first is to hear that they’re not 
crazy to suspect, at times, that there’s a connec-
tion between negative treatment and bias. The 
second is to be offered institutional support.
The first need has a clear path to fulfillment. 
When we encounter colleagues or friends who 
have been mistreated and who believe that their 
identity may be the reason, we should acknowl-
edge that it’s fair to be suspicious. There’s no leap 
of faith here—numerous studies show how perva-
sive such bias still is.
But how can we address the second need? In an 
effort to find valid, scalable ways to counteract or 
reverse bias and promote diversity, organizations 
are turning to people analytics—a relatively new 
field in business operations and talent manage-
ment that replaces gut decisions with data-driven 
practices. People analytics aspires to be “evidence 
based.” And for some HR issues—such as figuring 
out how many job interviews are needed to assess 
a candidate, or determining how employees’ work 
commutes affect their job satisfaction—it is. Sta-
tistically significant findings have led to some big 
changes in organizations. Unfortunately, compa-
nies that try to apply analytics to the challenges of 
underrepresented groups at work often complain 
that the relevant data sets don’t include enough 
people to produce reliable insights—the sample 
size, the n, is too small. Basically they’re saying, 
“If only there were more of you, we could tell you 
why there are so few of you.”
Companies have access to more data than they 
realize, however. To supplement a small n, they 
can venture out and look at the larger context in 
which they operate. But data volume alone won’t 
give leaders the insight they need to increase 
diversity in their organizations. They must also 
take a closer look at the individuals from under-
represented groups who work for them—those 
who barely register on the analytics radar. 
Supplementing the N 
Nonprofit research organizations are doing im-
portant work that sheds light on how bias shapes 
hiring and advancement in various industries and 
sectors. For example, a study by the Ascend Foun-
dation showed that in 2013 white men and white 
women in five major Silicon Valley firms were 154% 
more likely to become executives than their Asian 
counterparts were. And though both race and gen-
der were factors in the glass ceiling for Asians, race 
had 3.7 times the impact that gender did.It took two more years of research and analysis— 
using data on several hundred thousand employ-
ees, drawn from the EEOC’s aggregation of all Bay 
Area technology firms and from the individual 
reports of 13 U.S. tech companies—before Ascend 
determined how bias affected the prospects of 
blacks and Hispanics. Among those groups it again 
found that, overall, race had a greater negative 
impact than gender on advancement from the 
professional to the executive level. In the Bay Area 
white women fared worse than white men but 
much better than all Asians, Hispanics, and blacks. 
Minority women faced the biggest obstacle to 
entering the executive ranks. Black and Hispanic 
women were severely challenged by both their low 
numbers at the professional level and their lower 
chances of rising from professional to executive. 
Asian women, who had more representation at the 
professional level than other minorities, had the 
lowest chances of moving up from professional 
to executive. An analysis of national data found 
similar results.
By analyzing industry or sector data on under-
represented groups—and examining patterns in 
hiring, promotions, and other decisions about 
talent—we can better manage the problems and 
risks in our own organizations. Tech companies 
may look at the Ascend reports and say, “Hey, let’s 
think about what’s happening with our competi-
tors’ talent. There’s a good chance it’s happen-
ing here, too.” Their HR teams might then add a 
layer of career tracking for women of color, for 
example, or create training programs for manag-
ing diverse teams.
Executives tend to 
think—and have 
a desire to believe—
they’re hiring 
and promoting 
people fairly when 
they’re not.
FALL 2019 | HBR Special Issue 43
HBR.ORG
Idea 
in Brief
THE PROBLEM
Despite executives’ belief that 
they hire and promote fairly, we 
know that people have been 
denied jobs and advancement 
because of their race. Managers 
often use ambiguous assessment 
criteria to filter out people who 
are not like them, and those in 
marginalized racial and ethnic 
groups are deemed more often 
than whites to be “not the right 
cultural fit” or “not ready” for 
high-level roles. Organizations 
need to find valid, scalable ways 
to counteract or reverse the 
biases behind these choices and 
to promote diversity. 
PEOPLE ANALYTICS
People analytics offers some 
help by replacing gut decisions 
with data-driven practices. But 
not everyone registers on this 
radar—particularly not under-
represented groups. Hence 
organizations are left basically 
saying: “If only there were more 
of you, we could tell you why 
there are so few of you.” 
THE SOLUTION
When the numbers for an under-
represented group are too small 
to study in your organization, 
the author suggests including 
research on that population from 
the larger industry or context, 
learning from the experiences of 
other firms, and doing qualitative 
research into individual cases 
within your company. Because no 
single research method captures 
all the layers of bias, companies 
like Facebook are building cross-
functional teams to face and 
address such challenges. 
Another approach is to extrapolate lessons from 
other companies’ analyses. We might look, for 
instance, at Red Ventures, a Charlotte-based digital 
media company. Red Ventures is diverse by several 
measures. (It has a Latino CEO, and about 40% of 
its employees are people of color.) But that doesn’t 
mean there aren’t problems to solve. When I met 
with its top executives, they told me they had 
recently done an analysis of performance reviews 
at the firm and found that internalized stereotypes 
were having a negative effect on black and Latino 
employees’ self-assessments. On average, mem-
bers of those two groups rated their performance 
30% lower than their managers did (whereas white 
male employees scored their performance 10% 
higher than their managers did). The study also 
uncovered a correlation between racial isolation 
and negative self-perception. For example, people 
of color who worked in engineering generally rated 
themselves lower than those who worked in sales, 
where there were more blacks and Latinos. These 
patterns were consistent at all levels, from junior 
to senior staff. 
In response, the HR team at Red Ventures 
trained employees in how to do self-assess-
ments, and that has started to close the gap for 
blacks and Latinos (who more recently rated 
themselves 22% lower than their managers did). 
Hallie Cornetta, the company’s VP of human 
capital, explained that the training “focused on 
the importance of completing quantitative and 
qualitative self-assessments honestly, in a way 
that shows how employees personally view their 
performance across our five key dimensions, 
rather than how they assume their manager or 
peers view their performance.” She added: “We 
then shared tangible examples of what ‘excep-
tional’ versus ‘solid’ versus ‘needs improvement’ 
looks like in these dimensions to remove some 
of the subjectivity and help minority—and all— 
employees assess with greater direction and 
confidence.”
Getting Personal 
Once we’ve gone broader by supplementing the n, 
we can go deeper by examining individual cases. 
This is critical. Algorithms and statistics do not 
capture what it feels like to be the only black or 
Hispanic team member or the effect that marginal-
ization has on individual employees and the group 
as a whole. We must talk openly with people, one-
on-one, to learn about their experiences with bias, 
and share our own stories to build trust and make 
the topic safe for discussion. What we discover 
through those conversations is every bit as impor-
tant as what shows up in the aggregated data.
An industry colleague, who served as a lead on 
diversity at a tech company, broke it down for me 
like this: “When we do our employee surveys, 
the Latinos always say they are happy. But I’m 
Latino, and I know that we are often hesitant to 
rock the boat. Saying the truth is too risky, so 
we’ll say what you want to hear—even if you sit 
us down in a focus group. I also know that those 
aggregated numbers where there are enough 
of us for the n to be significant don’t reflect the 
heterogeneity in our community. Someone who 
is light-skinned and grew up in Latin America in 
an upper-middle-class family probably is very 
happy and comfortable indeed. Someone who 
is darker- skinned and grew up working-class in 
America is probably not feeling that same sense 
of belonging. I’m going to spend time and effort 
trying to build solutions for the ones I know are 
at a disadvantage, whether the data tells me that 
there’s a problem with all Latinos or not.”
This is a recurring theme. I spoke with 10 
diversity and HR professionals at companies with 
head counts ranging from 60 to 300,000, all of 
whom are working on programs or interventions 
for the people who don’t register as “big” in big 
data. They rely at least somewhat on their own 
intuition when exploring the impact of margin-
alization. This may seem counter to the mission 
of people analytics, which is to remove personal 
perspective and gut feelings from the talent equa-
tion entirely. But to discover the effects of bias in 
our organizations— and to identify complicating 
factors within groups, such as class and colorism 
among Latinos and others—we need to collect and 
analyze qualitative data, too. Intuition can help 
us find it. The diversity and HR folks described 
using their “spidey sense” or knowing there is 
“something in the water”—essentially, under-
standing that bias is probably a factor, even though 
people analytics doesn’t always prove causes and 
predict outcomes. Through conversations with 
employees— and sometimes through focus groups, 
if the resources are there and participants feel it’s 
safe to be honest—they reality-check what their 
instincts tell them, often drawing on their own 
experiences with bias. One colleague said, “The 
combination of qualitativeand quantitative data 
44 HBR Special Issue | FALL 2019
TODAY’S TALENT MANAGEMENT “NUMBERS TAKE US ONLY SO FAR”
is ideal, but at the end of the day there is nothing 
that data will tell us that we don’t already know as 
black people. I know what my experience was as 
an African-American man who worked for 16 years 
in roles that weren’t related to improving diver-
sity. It’s as much heart as head in this work.” 
A Call to Action 
The proposition at the heart of people analytics 
is sound—if you want to hire and manage fairly, 
gut-based decisions are not enough. However, 
we have to create a new approach, one that also 
works for small data sets—for the marginalized 
and the underrepresented. 
Here are my recommendations:
First, analysts must challenge the traditional 
minimum confident n, pushing themselves to 
look beyond the limited hard data. They don’t 
have to prove that the difference in performance 
ratings between blacks and whites is “statistically 
significant” to help managers understand the 
impact of bias in performance reviews. We already 
know from the breadth and depth of social science 
research about bias that it is pervasive in the work-
place and influences ratings, so we can combine 
those insights with what we hear and see on the 
ground and simply start operating as if bias exists 
in our companies. We may have to place a higher 
value on the experiences shared by five or 10 em-
ployees—or look more carefully at the descriptive 
data, such as head counts for underrepresented 
groups and average job satisfaction scores cut by 
race and gender—to examine the impact of bias 
at a more granular level. 
In addition, analysts should frequently provide 
confidence intervals—that is, guidance on how 
much managers can trust the data if the n’s are 
too small to prove statistical significance. When 
managers get that information, they’re more likely 
to make changes in their hiring and management 
practices, even if they believe—as most do—that 
they are already treating people fairly. Suppose, 
for example, that as Red Ventures began collecting 
data on self- assessments, analysts had a 75% con-
fidence level that blacks and Latinos were under-
rating themselves. The analysts could then have 
advised managers to go to their minority direct re-
ports, examine the results from that performance 
period, and determine together whether the 
self-reviews truly reflected their contributions. It’s 
a simple but collaborative way to address implicit 
PHOTOGRAPHY BY ANASTASIIA SAPON
FALL 2019 | HBR Special Issue 45
HBR.ORG
the “why,” and pull out themes or lessons for other 
parts of the company. In other scenarios we might 
reverse the order of those steps. For example, 
if we repeatedly heard from members of one 
social group that they weren’t seeing their peers 
getting recognized at the same rate as people in 
other groups, we could then investigate whether 
numerical trends confirmed those observations, 
or conduct statistical analyses to figure out which 
organizational circumstances were associated 
with employees’ being more or less likely to get 
recognized. 
Cross-functional teams also help us reap the 
benefits of cognitive diversity. Working together 
stretches everyone, challenging team members’ 
own assumptions and biases. Getting to absolute 
“whys” and “hows” on any issue, from recruit-
ment to engagement to performance, is always 
going to be tough. But we believe that with this 
approach, we stand the best chance of making 
improvements across the company. As we analyze 
the results of Facebook’s Pulse survey, given twice 
a year to employees, and review Performance 
Summary Cycle inputs, we’ll continue to look for 
signs of problems as well as progress. 
EVIDENCE OF DISCRIMINATION or unfair outcomes 
may not be as certain or obvious in the workplace 
as it was for me the time I was evicted from my 
apartment. But we can increase our certainty, and 
it’s essential that we do so. The underrepresented 
people at our companies are not crazy to perceive 
biases working against them, and they can get 
institutional support. 
HBR Reprint R1706L
bias or stereotyping that you’re reasonably sure is 
there while giving agency to each employee. 
Second, companies also need to be more 
consistent and comprehensive in their qualitative 
analysis. Many already conduct interviews and fo-
cus groups to gain insights on the challenges of the 
underrepresented; some even do textual analysis 
of written performance reviews, exit interview 
notes, and hiring memos, looking for language 
that signals bias or negative stereotyping. But we 
have to go further. We need to find a viable way to 
create and process more-objective performance 
evaluations, given the internalized biases of both 
employees and managers, and to determine how 
those biases affect ratings. 
This journey begins with educating all employ-
ees on the real-life impact of bias and negative 
stereotypes. At Facebook we offer a variety of 
training programs with an emphasis on spotting 
and counteracting bias, and we keep reinforcing 
key messages post-training, since we know these 
muscles take time to build. We issue reminders 
at critical points to shape decision making and 
behavior. For example, in our performance evalu-
ation tool, we incorporate prompts for people 
to check word choice when writing reviews and 
self-assessments. We remind them, for instance, 
that terms like “cultural fit” can allow bias to creep 
in and that they should avoid describing women 
as “bossy” if they wouldn’t describe men who 
demonstrated the same behaviors that way. We 
don’t yet have data on how this is influencing the 
language used—it’s a new intervention—but we 
will be examining patterns over time.
Perhaps above all, HR and analytics depart-
ments must value both qualitative and quantitative 
expertise and apply mixed-method approaches 
everywhere possible. At Facebook we’re building 
cross-functional teams with both types of special-
ists, because no single research method can fully 
capture the complex layers of bias that everyone 
brings to the workplace. We view all research 
methods as trying to solve the same problem 
from different angles. Sometimes we approach 
challenges from a quantitative perspective first, to 
uncover the “what” before looking to the qualita-
tive experts to dive into the “why” and “how.” 
For instance, if the numbers showed that certain 
teams were losing or attracting minority employ-
ees at higher rates than others (the “what”), we 
might conduct interviews, run focus groups, or 
analyze text from company surveys to understand 
Algorithms and 
statistics do not 
capture what it feels 
like to be the only 
black or Hispanic 
member of a team.
46 HBR Special Issue | FALL 2019
from HR (61%), finance (28%), 
and general management (10%). 
I helped design, analyze, and 
report on the survey. All the ex-
ecutives were from companies 
with $100 million in revenue 
or more. 
While HR is obviously 
moving in an analytical direc-
tion, I did not expect the high 
level of sophisticated analytical 
activity in the survey. Here are 
some highlights:
• Fifty-one percent of HR re-
spondents said that they could 
perform predictive or prescrip-
tive analytics, whereas only 
37% of finance respondents 
could undertake these more 
advanced forms of analytics.
• Eighty-nine percent agreed 
or agreed strongly that “my 
HR function is highly skilled at 
using data to determine future 
workforce plans currently (for 
example, talent needed),” and 
only 1% disagreed.
• Ninety-four percent agreed 
that “we are able to predict the 
likelihood of turnover in criti-
cal roles with a high degree of 
confidence currently.”
• Ninety-four percent also 
agreed that “we have accu-
rate, real-time insight into our 
employees’ career development 
goals currently.”
• When asked “Which of the 
following analytics are you 
using?” artificial intelligence 
received the highest response, 
with31%. When asked for fur-
ther detail on how respondents H
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Quick Takes
Is HR the Most 
Analytics-Driven 
Function?
by Thomas H. Davenport 
HR is more comfortable 
with advanced analytics 
than finance.
TODAY’S TALENT MANAGEMENT
analytics capability we uncov-
ered was at Google and perhaps 
Harrah’s (now Caesars). There 
was a fair amount of reporting 
going on, but not much predic-
tion. Few HR organizations 
even had a dedicated analytics 
person. “HR analytics” typically 
meant a debate about how many 
employees the organization 
had or the best way to measure 
employee engagement.
Even before the new survey 
results came out, I suspected 
that things were different today. 
Most large companies have 
at least a small talent, people, 
workforce, or HR analytics 
group. Many conferences are 
devoted to the topic. It’s com-
mon for organizations today to 
model workforce growth, attri-
tion, engagement, and other key 
variables.
The survey involved 1,510 
respondents from 23 coun-
tries across five continents. 
It included senior managers, 
directors, and vice presidents 
I HAVE ARGUED over the past 
decade that the HR function 
has the potential to become 
one of the leaders in analytics. 
The key word, I thought, was 
potential. Not anymore. A recent 
global survey on which I col-
laborated with Oracle suggests 
that HR is right up there with 
the most analytical functions in 
business— and even a bit ahead 
of a quantitatively oriented 
function such as finance. Many 
HR departments are using 
advanced analytical methods 
like predictive and prescrip-
tive models, and even artificial 
intelligence.
This is a big change from a 
decade ago, when I began to 
study the use of talent analytics. 
(Jeanne Harris, Jeremy Shapiro, 
and I published the HBR article 
“Competing on Talent Analyt-
ics” in 2010.) At that time, the 
only really sophisticated HR 
HBR.ORG
FALL 2019 | HBR Special Issue 47
TO CREATE an analytical culture 
in your organization, you need 
to nurture the right mindset 
among your employees. And 
that starts with creating a 
culture of analytics in your HR 
department. How can senior 
leaders help HR develop a 
culture in which people think 
analytically? First, you need to 
understand the different levels 
of comfort with analytics in HR; 
then you need to decide your 
approach to hiring and building 
expertise at each of the differ-
ent levels.
Understanding Your 
Current Levels of 
HR Analytics Expertise
Our research for the book The 
Power of People showed that HR 
professionals can be broadly 
categorized into one of three 
mutual respect between HR and 
finance, and a growing need 
for collaboration. For example, 
82% of respondents agreed or 
strongly agreed, and only 5% 
disagreed, that “integrating HR 
and finance data is a top prior-
ity for us this year”; however, 
several interviews conducted 
after the survey revealed that 
there is still much opportunity 
for greater sharing of data and 
collaboration on analytics.
Of course, not everything is 
rosy in the world of HR analyt-
ics. I was quite interested to see 
that the function’s use of ana-
lytical tools surpasses the ability 
to interpret and act on them. 
When respondents were asked 
about the area of analytical skills 
for HR that “most needed to de-
velop or improve,” the highest-
ranking choice was “acting 
on data and analytics to solve 
issues.” “Cultivating quantitative 
analysis and reasoning skills” 
and “advising business leaders 
by telling a story with data” also 
ranked highly. My experience is 
that these skills are equally lack-
ing in other functions. Perhaps it 
is another sign of HR’s analyti-
cal maturity that it is facing the 
same human skill shortages that 
have long bedeviled analytics 
users across companies.
Originally published on HBR.org 
April 18, 2019
HBR Reprint H04WQI
Thomas H. Davenport is the President’s 
Distinguished Professor in Management 
and Information Technology at Babson 
College, a research fellow at the MIT 
Initiative on the Digital Economy, and a 
senior adviser at Deloitte Analytics. He 
is the author of 20 management books, 
most recently Only Humans Need Apply: 
Winners and Losers in the Age of Smart 
Machines (HarperBusiness, 2016) and 
The AI Advantage: How to Put the Artifi-
cial Intelligence Revolution to Work (MIT 
Press, 2018).
were using AI, the most com-
mon responses were “iden-
tifying at-risk talent through 
attrition modeling,” “predicting 
high-performing recruits,” and 
“sourcing best-fit candidates 
with résumé analysis.”
This level of self-assessed 
capability for HR analytics was 
high in almost every geography 
and every specific question, but 
it was somewhat lower in Asian, 
European, and Australian organi-
zations. It was generally highest 
in the U.S., the Middle East, and 
Latin America. Across indus-
tries, it was lowest in hospitality, 
travel, and leisure as well as me-
dia and entertainment. Particu-
larly high industries included 
financial services, energy and 
utilities, professional services, 
and wholesale distribution.
Why is HR more comfortable 
with advanced analytics than 
finance, which has always been 
a function based on numbers? 
I have noted for years that finan-
cial organizations and the CFOs 
who lead them have found it 
difficult to move past descriptive 
analytics and reporting—which 
they do very well—to more-
advanced analytics. There are 
certainly exceptions to this rule, 
but it helps explain why the 
growth of advanced analytics 
has been faster in HR.
But no business function 
stands alone with regard to data 
and analytics. One reason that 
Oracle surveyed both HR and 
finance executives is that those 
two functions have an increas-
ing need to collaborate. Work-
force expenditures are often 
among an organization’s highest 
costs, and a company’s financial 
situation will dictate fluctua-
tions in the size and makeup of 
the workforce. The survey found 
high levels of collaboration and 
groups with respect to their cur-
rent analytical capability:
Analytically savvy: formally 
trained in analytics techniques 
and adept at working with data 
and interpreting analyses
Analytically willing: open-
minded about analytics and 
ready, able, and willing to learn, 
though lacking formal training 
in data analysis
Analytically resistant: 
skeptical and dismissive of the 
value of a data-based approach, 
preferring instead to rely on 
intuition
You can gauge the comfort 
levels with analytics in HR 
by checking for specific skills 
when hiring and by monitor ing 
engagement with learning 
opportunities. Once you under-
stand the different levels of ana-
lytical comfort and expertise SO
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How to Develop a Data-Savvy 
HR Department
by Nigel Guenole and Sheri L. Feinzig
48 HBR Special Issue | FALL 2019
TODAY’S TALENT MANAGEMENT QUICK TAKES
ers to improve the content as 
they go. By monitoring and 
rewarding learner progress, 
firms can recompose the skills 
of their workforce. A good way 
to reward progress is via digital 
credentialing with a system like 
Credly, which allows workers 
to share their learning success 
with badges on social platforms 
such as LinkedIn.
A more data-savvy HR func-
tion is entirely achievable. By 
understanding the levels of 
analytics capability in your HR 
team today, hiring for critical 
skills to fill gaps, and providing 
ongoing, targeted, and engaging 
learning opportunities, organi-
zations will be well positioned 
to realize the promise of analyt-
ics in HR. 
Originally published on HBR.org 
October 11, 2018
HBR Reprint H04L1I
Nigel Guenole is the director of research 
for the Institute of Management at 
Goldsmiths, University of London; an ex-
ecutive consultant at IBM; and the chief 
science adviser to Podium Assessment 
Systems. He is a coauthor, with Sheri L. 
Feinzig and Jonathan Ferrar, of The Power 
of People: Learn How Successful Orga-
nizationsUse Workforce Analytics to Im-
prove Business Performance (Pearson FT 
Press, 2017). Sheri L. Feinzig is a direc-
tor at IBM Talent Management Consulting 
and Smarter Workforce Institute and has 
more than 20 years’ experience in HR 
research, organizational change manage-
ment, and business transformation. She 
is a coauthor, with Nigel Guenole and 
Jonathan Ferrar, of The Power of People: 
Learn How Successful Organizations Use 
Workforce Analytics to Improve Business 
Performance (Pearson FT Press, 2017).
them with analytically savvy 
colleagues to use data and 
analytics to solve a problem 
they are struggling with. If they 
decline these opportunities, ask 
them why they are reluctant or 
what they are struggling with. 
The ultimate goal is not neces-
sarily to transform the analyti-
cally resistant into data experts, 
but to have them see the value 
in analytics and ideally embrace 
it as a path to success.
Personalize Learning, 
and Deliver It at Scale
Analytically related learn-
ing opportunities for all HR 
professionals can be managed 
with a Netflix-style online 
learning system, such as IBM’s 
Your Learning platform. With 
platforms like Your Learning, 
you can curate content targeted 
at each level of comfort with 
analytics. HR departments can 
set learning goals for workers 
that suggest how many hours 
of learning they’re expected to 
complete in a given period. A 
good benchmark for this would 
be 60 hours per year, the aver-
age at IBM. You can designate 
analytical skills as “hot skills” 
for HR professionals, and as 
people acquire more of these 
skills, increase their compensa-
tion to reflect their enhanced 
capabilities.
It is important to pay close 
attention to the feedback 
learners provide and modify 
the content on the basis of 
what’s most effective. For in-
stance, learners can be encour-
aged to tag content, and tags 
should be visible to content 
designers and other learners. 
This enables social learning 
where new course participants 
learn from past participants’ 
experiences and allows design-
plexity enhances the chance 
that the analytically willing will 
be able to extract meaning from 
analytical information.
Developing 
Analytical Capability
The key to developing capabil-
ity among existing workers is 
to provide engaging learning 
opportunities to workers at all 
levels of expertise:
Analytically savvy. Keep 
these workers’ skills up-to-date 
by providing opportunities 
for advanced training; encour-
age participation in meet-
ups, online- user groups, and 
forums; and support partici-
pation in professional groups 
and conferences. Assign them 
responsibility for analytics 
evangelism, and reinforce this 
in performance objectives. Each 
evangelist should mentor one 
colleague who is less analyti-
cally capable. If you don’t have 
analytically savvy people on 
your team, hiring a few will help 
establish an analytical culture.
Analytically willing. Provide 
a foundational education on 
HR analytics by requiring 
all HR staff to complete an 
online course about the basics 
of workforce analytics, such 
as Wharton’s Coursera HR 
Analytics Module, which can 
be completed in just four weeks 
with a commitment of one to 
two hours per week. The ana-
lytically willing should then put 
their learning into practice by 
applying the techniques to their 
day-to-day work. These expec-
tations can be incorporated as 
explicit goals in performance 
management systems.
Analytically resistant. 
Focus on how analytics can 
enhance these employees’ 
personal effectiveness. Pair 
that exist within your HR team, 
you can determine how to hire 
and develop each type of HR 
professional.
Hiring for 
Analytical Capability
Roles that require producing 
analytical information demand 
analytically savvy workers, 
whereas roles that involve 
interpreting and working 
with analytical information 
require analytically willing 
workers.
You can assess whether 
workers are analytically savvy 
by examining formal quali-
fications and administering 
well-designed psychometric 
tests that measure general 
mental ability, which is a good 
predictor of performance 
because high scores indicate 
workers can acquire job-related 
knowledge more quickly. 
You should also consider less 
traditional evidence of learning 
beyond formal education, such 
as massive open online courses 
(MOOCs) provided by compa-
nies such as Coursera or edX.
For analytically willing work-
ers, consider personality tests 
that measure “investment” 
traits like openness to experi-
ence. Investment traits describe 
the tendency to engage in 
complex thinking. Because 
analytical information can be 
complex, comfort with com-
Assign workers 
responsibility for 
analytics evangelism, 
and reinforce this 
in performance 
objectives.
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“Th at moment I realized I was 
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experience transformation:
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Originally published in 
May–June 2019
ILLUSTRATION BY JOANNA ŁAWNICZAK
BUSINESSES HAVE NEVER done 
as much hiring as they do today. 
They’ve never spent as much 
money doing it. And they’ve never 
done a worse job of it. 
For most of the post–World 
War II era, large corporations went about hiring 
this way: Human resources experts prepared a 
detailed job analysis to determine what tasks the 
job required and what attributes a good candidate 
should have. Next they did a job evaluation to 
determine how the job fi t into the organizational 
chart and how much it should pay, especially 
compared with other jobs. Ads were posted, and 
applicants applied. Then came the task of sorting 
through the applicants. That included skills tests, 
reference checks, maybe personality and IQ tests, 
and extensive interviews to learn more about 
Your 
Approach 
to Hiring 
Is All Wrong
Outsourcing and algorithms won’t get you the people 
you need. by Peter Cappelli
HOW RECRUITING WORKS NOW
FALL 2019 | HBR Special Issue 51
52 HBR Special Issue | FALL 2019
HOW RECRUITING WORKS NOW YOUR APPROACH TO HIRING IS ALL WRONG
them as people. William H. Whyte, in The Organi-
zation Man, described this process as going on for 
as long as a week before the winning candidate 
was offered the job. The vast majority of non-
entry-level openings were filled from within.
Today’s approach couldn’t be more different. 
Census data shows, for example, that the majority 
of people who took a new job last year weren’t 
searching for one: Somebody came and got them. 
Companies seek to fill their recruiting funnel 
with as many candidates as possible, especially 
“passive candidates,” who aren’t looking to move. 
Often employers advertise jobs that don’t exist, 
hoping to find people who might be useful later 
on or in a different context. 
The recruiting and hiring function has been 
eviscerated. Many U.S. companies—about 40%, 
according to research by Korn Ferry—have out-
sourced much if not all of the hiring process to 
“recruitment process outsourcers,” which in turn 
use subcontractors, typically in India and the Phil-
ippines.The subcontractors scour LinkedIn and 
social media to find potential candidates. They 
sometimes contact them directly to see whether 
they can be persuaded to apply for a position and 
negotiate the salary they’re willing to accept. (The 
recruiters get incentive pay if they negotiate the 
amount down.) To hire programmers, for example, 
these subcontractors can scan websites that pro-
grammers might visit, trace their “digital exhaust” 
from cookies and other user-tracking measures 
to identify who they are, and then examine their 
curricula vitae. 
At companies that still do their own recruitment 
and hiring, managers trying to fill open positions 
are largely left to figure out what the jobs require 
and what the ads should say. When applications 
come—always electronically—applicant-tracking 
software sifts through them for key words that 
the hiring managers want to see. Then the process 
moves into the Wild West, where a new industry 
of vendors offer an astonishing array of smart-
sounding tools that claim to predict who will be 
a good hire. They use voice recognition, body 
language, clues on social media, and especially 
machine learning algorithms—everything but tea 
leaves. Entire publications are devoted to what 
these vendors are doing. 
The big problem with all these new practices is 
that we don’t know whether they actually produce 
satisfactory hires. Only about a third of U.S. com-
panies report that they monitor whether their hir-
ing practices lead to good employees; few of them 
do so carefully, and only a minority even track 
cost per hire and time to hire. Imagine if the CEO 
asked how an advertising campaign had gone, and 
the response was “We have a good idea how long 
it took to roll out and what it cost, but we haven’t 
looked to see whether we’re selling more.” 
Hiring talent remains the number one concern 
of CEOs in the most recent Conference Board 
Annual Survey; it’s also the top concern of the 
entire executive suite. PwC’s 2017 CEO survey 
reports that chief executives view the unavail-
ability of talent and skills as the biggest threat to 
their business. Employers also spend an enormous 
amount on hiring—an average of $4,129 per job in 
the United States, according to Society for Human 
Resource Management estimates, and many times 
that amount for managerial roles—and the United 
States fills a staggering 66 million jobs a year. Most 
of the $20 billion that companies spend on human 
resources vendors goes to hiring. 
Why do employers spend so much on some-
thing so important while knowing so little about 
whether it works?
Where the Problem Starts 
Survey after survey finds employers complaining 
about how difficult hiring is. There may be many 
explanations, such as their having become very 
picky about candidates, especially in the slack 
labor market of the Great Recession. But clearly 
they are hiring much more than at any other time 
in modern history, for two reasons.
The first is that openings are now filled more of-
ten by hiring from the outside than by promoting 
from within. In the era of lifetime employment, 
from the end of World War II through the 1970s, 
corporations filled roughly 90% of their vacan-
cies through promotions and lateral assignments. 
Today the figure is a third or less. When they hire 
from outside, organizations don’t have to pay 
to train and develop their employees. Since the 
restructuring waves of the early 1980s, it has been 
relatively easy to find experienced talent outside. 
Only 28% of talent acquisition leaders today report 
that internal candidates are an important source 
of people to fill vacancies—presumably because of 
less internal development and fewer clear career 
ladders.
Less promotion internally means that hiring 
efforts are no longer concentrated on entry-level 
FALL 2019 | HBR Special Issue 53
HBR.ORG
Idea 
in Brief
THE PROBLEM
Employers continue to hire at 
a high rate and spend enormous 
sums to do it. But they don’t 
know whether their approaches 
are effective at finding and 
selecting good candidates.
THE ROOT CAUSES 
Businesses focus on external 
candidates and don’t track the 
results of their approaches. They 
often use outside vendors and 
high-tech tools that are unprov-
en and have inherent flaws.
THE SOLUTION
Return to filling most posi-
tions by promoting from within. 
Measure the results produced by 
vendors and new tools, and be 
on the lookout for discrimination 
and privacy violations. 
jobs and recent graduates. (If you doubt this, go 
to the “careers” link on any company website and 
look for a job opening that doesn’t require prior ex-
perience.) Now companies must be good at hiring 
across most levels, because the candidates they 
want are already doing the job somewhere else. 
These people don’t need training, so they may 
 be ready to contribute right away, but they are 
much harder to find. 
The second reason hiring is so difficult is that 
retention has become tough: Companies hire from 
their competitors and vice versa, so they have 
to keep replacing people who leave. Census and 
Bureau of Labor Statistics data shows that 95% 
of hiring is done to fill existing positions. Most of 
those vacancies are caused by voluntary turnover. 
LinkedIn data indicates that the most common 
reason employees consider a position elsewhere 
is career advancement—which is surely related to 
employers’ not promoting to fill vacancies. 
The root cause of most hiring, therefore, is 
drastically poor retention. Here are some simple 
ways to fix that:
Track the percentage of openings filled 
from within. An adage of business is that we man-
age what we measure, but companies don’t seem 
to be applying that maxim to tracking hires. Most 
are shocked to learn how few of their openings are 
filled from within—is it really the case that their 
people can’t handle different and bigger roles? 
Require that all openings be posted in-
ternally. Internal job boards were created during 
the dot-com boom to reduce turnover by making 
it easier for people to find new jobs within their 
existing employer. Managers weren’t even allowed 
to know if a subordinate was looking to move 
within the company, for fear that they would try 
to block that person and he or she would leave. 
But during the Great Recession employees weren’t 
quitting, and many companies slid back to the 
old model whereby managers could prevent their 
subordinates from moving internally. JR Keller, of 
Cornell University, has found that when managers 
could fill a vacancy with someone they already 
had in mind, they ended up with employees who 
performed more poorly than those hired when 
the job had been posted and anyone could apply. 
The commonsense explanation for this is that few 
enterprises really know what talent and capabili-
ties they have.
Recognize the costs of outside hiring. In 
addition to the time and effort of hiring, my col-
league Matthew Bidwell found, outside hires take 
three years to perform as well as internal hires in 
the same job, while internal hires take seven years 
to earn as much as outside hires are paid. Outside 
hiring also causes current employees to spend 
time and energy positioning themselves for jobs 
elsewhere. It disrupts the culture and burdens 
peers who must help new hires figure out how 
things work. 
None of this is to suggest that outside hiring is 
necessarily a bad idea. But unless your company 
is a Silicon Valley gazelle, adding new jobs at a 
furious pace, you should ask yourself some serious 
questions if most of your openings are being filled 
from outside.
A different approach for dealing with reten-
tion (which seems creepy to some) is to try to 
determine who is interested in leaving and then 
intervene. Vendors like Jobvite comb social media 
and public sites for clues, such as LinkedIn profile 
updates. Measuring “flight risk” is one of the most 
common goals of companies that do their own so-
phisticated HR analytics. This is reminiscent of the 
earlydays of job boards, when employers would 
try to find out who was posting résumés and either 
punish them or embrace them, depending on 
leadership’s mood. 
Whether companies should be examining social 
media content in relation to hiring or any other 
employment action is a challenging ethical ques-
tion. On one hand, the information is essentially 
public and may reveal relevant information. On 
the other hand, it is invasive, and candidates are 
rarely asked for permission to scrutinize their 
information. Hiring a private detective to shadow 
a candidate would also gather public information 
that might be relevant, yet most people would 
view it as an unacceptable invasion of privacy. 
The Hiring Process 
When we turn to hiring itself, we find that employ-
ers are missing the forest for the trees: Obsessed 
with new technologies and driving down costs, 
they largely ignore the ultimate goal: making the 
best possible hires. Here’s how the process should 
be revamped: 
Don’t post “phantom jobs.” It costs nothing 
to post job openings on a company website, which 
are then scooped up by Indeed and other online 
companies and pushed out to potential job seekers 
around the world. Thus it may be unsurprising that 
54 HBR Special Issue | FALL 2019
HOW RECRUITING WORKS NOW YOUR APPROACH TO HIRING IS ALL WRONG
some of these jobs don’t really exist. Employers 
may simply be fishing for candidates. (“Let’s see 
if someone really great is out there, and if so, we’ll 
create a position for him or her.”) Often job ads stay 
up even after positions have been filled, to keep 
collecting candidates for future vacancies or just 
because it takes more effort to pull the ad down 
than to leave it up. Sometimes ads are posted by 
unscrupulous recruiters looking for résumés to 
pitch to clients elsewhere. Because these phantom 
jobs make the labor market look tighter than it 
really is, they are a problem for economic policy 
makers as well as for frustrated job seekers. Com-
panies should take ads down when jobs are filled.
Design jobs with realistic requirements. 
Figuring out what the requirements of a job should 
be—and the corresponding attributes candidates 
must have—is a bigger challenge now, because 
so many companies have reduced the number of 
internal recruiters whose function, in part, is to 
push back on hiring managers’ wish lists. (“That 
job doesn’t require 10 years of experience,” or “No 
one with all those qualifications will be willing to 
accept the salary you’re proposing to pay.”) My 
earlier research found that companies piled on 
job requirements, baked them into the applicant-
tracking software that sorted résumés according 
to binary decisions (yes, it has the key word; no, 
it doesn’t), and then found that virtually no ap-
plicants met all the criteria. Trimming recruiters, 
who have expertise in hiring, and handing the pro-
cess over to hiring managers is a prime example of 
being penny-wise and pound-foolish.
Reconsider your focus on passive candi-
dates. The recruiting process begins with a search 
for experienced people who aren’t looking to 
move. This is based on the notion that something 
may be wrong with anyone who wants to leave his 
or her current job. (Of the more than 20,000 talent 
professionals who responded to a LinkedIn survey 
in 2015, 86% said their recruiting organizations 
focused “very much so” or “to some extent” on 
passive candidates; I suspect that if anything, that 
number has since grown.) Recruiters know that 
the vast majority of people are open to moving 
at the right price: Surveys of employees find that 
only about 15% are not open to moving. As the 
economist Harold Demsetz said when asked by 
a competing university if he was happy working 
where he was: “Make me unhappy.” 
Fascinating evidence from the LinkedIn survey 
cited above shows that although self-identified 
“passive” job seekers are different from “active” 
job seekers, it’s not in the way we might think. The 
number one factor that would encourage the for-
mer to move is more money. For active candidates 
the top factor is better work and career opportuni-
ties. More active than passive job seekers report 
that they are passionate about their work, engaged 
in improving their skills, and reasonably satisfied 
with their current jobs. They seem interested in 
moving because they are ambitious, not because 
they want higher pay. 
Employers spend a vastly disproportionate 
amount of their budgets on recruiters who chase 
passive candidates, but on average they fill only 
11% of their positions with individually targeted 
people, according to research by Gerry Crispin 
and Chris Hoyt, of CareerXroads. I know of no 
evidence that passive candidates become better 
employees, let alone that the process is cost-
effective. If you focus on passive candidates, think 
carefully about what that actually gets you. Better 
yet, check your data to find out. 
Understand the limits of referrals. The 
most popular channel for finding new hires is 
through employee referrals; up to 48% come from 
them, according to LinkedIn research. It seems 
like a cheap way to go, but does it produce better 
hires? Many employers think so. It’s hard to know 
whether that’s true, however, given that they 
don’t check. And research by Emilio Castilla and 
colleagues suggests other wise: They find that 
when referrals work out better than other hires, it’s 
because their referrers look after them and essen-
tially onboard them. If a referrer leaves before the 
Obsessed with new technologies and driving 
down costs, employers largely ignore the 
ultimate goal: making the best possible hires.
FALL 2019 | HBR Special Issue 55
HBR.ORG
ing lots of applicants in a wide funnel means that 
a great many of them won’t fit the job or the com-
pany, so employers have to rely on the next step of 
the hiring process—selection—to weed them out. 
As we will see, employers aren’t good at that.
Once people are candidates, they may not be 
completely honest about their skills or interests—
because they want to be hired—and employers’ 
ability to find out the truth is limited. More than a 
generation ago the psychologist John Wanous pro-
posed giving applicants a realistic preview of what 
the job is like. That still makes sense as a way to 
head off those who would end up being unhappy 
in the job. It’s not surprising that Google has found 
a way to do this with gamification: Job seekers see 
what the work would be like by playing a game 
version of it. Marriott has done the same, even for 
low-level employees. Its My Marriott Hotel game 
targets young people in developing countries who 
may have had little experience in hotels to show 
them what it’s like and to steer them to the recruit-
ing site if they score well on the game. The key for 
any company, though, is that the preview should 
make clear what is difficult and challenging about 
the work as well as why it’s fun so that candidates 
who don’t fit won’t apply. 
It should be easy for candidates to learn about 
a company and a job, but making it really easy 
to apply, just to fill up that funnel, doesn’t make 
much sense. During the dot-com boom Texas 
Instruments cleverly introduced a preemployment 
test that allowed applicants to see their scores 
before they applied. If their scores weren’t high 
enough for the company to take their applications 
seriously, they tended not to proceed, and the 
company saved the cost of having to process their 
applications. 
If the goal is to get better hires in a cost-effective 
manner, it’s more important to scare away candi-
dates who don’t fit than to jam more candidates 
into the recruiting funnel. 
Test candidates’ standard skills. How 
to determine which candidates to hire—what 
predicts who will be a good employee—has been 
rigorously studied at least since World War I. The 
personnel psychologists who investigated this 
have learned much about predicting good hires 
that contemporary organizations have sinceforgotten, such as that neither college grades nor 
unstructured sequential interviews (hopping 
from office to office) are a good predictor, whereas 
past performance is. 
new hire begins, the latter’s performance is no bet-
ter than that of nonreferrals, which is why it makes 
sense to pay referral bonuses six months or so after 
the person is hired—if he or she is still there. 
A downside to referrals, of course, is that they 
can lead to a homogeneous workforce, because 
the people we know tend to be like us. This mat-
ters greatly for organizations interested in diver-
sity, since recruiting is the only avenue allowed 
under U.S. law to increase diversity in a workforce. 
The Supreme Court has ruled that demographic 
criteria cannot be used even to break ties among 
candidates. 
Measure the results. Few employers know 
which channel produces the best candidates at the 
lowest cost because they don’t track the out-
comes. Tata is an exception: It has long done what 
I advocate. For college recruiting, for example, it 
calculates which schools send it employees who 
perform the best, stay the longest, and are paid 
the lowest starting wage. Other employers should 
follow suit and monitor recruiting channels and 
employees’ performance to identify which sources 
produce the best results. 
Persuade fewer people to apply. The hiring 
industry pays a great deal of attention to “the 
funnel,” whereby readers of a company’s job 
postings become applicants, are interviewed, and 
ultimately are offered jobs. Contrary to the popular 
belief that the U.S. job market is extremely tight 
right now, most jobs still get lots of applicants. 
Recruiting and hiring consultants and vendors 
estimate that about 2% of applicants receive of-
fers. Unfortunately, the main effort to improve 
hiring—virtually always aimed at making it faster 
and cheaper—has been to shovel more applicants 
into the funnel. Employers do that primarily 
through marketing, trying to get out the word that 
they are great places to work. Whether doing this 
is a misguided way of trying to attract better hires 
or just meant to make the organization feel more 
desirable isn’t clear.
Much better to go in the other direction: Create 
a smaller but better-qualified applicant pool to 
improve the yield. Here’s why: Every applicant 
costs you money—especially now, in a labor market 
where applicants have started to “ghost” employ-
ers, abandoning their applications midway through 
the process. Every application also exposes a 
company to legal risk, because the company has 
obligations to candidates (not to discriminate, for 
example) just as it does to employees. And collect-
Finding out whether your 
practices result in good hires 
is not only basic to good 
management but the only real 
defense against claims of ad-
verse impact and discrimina-
tion. Other than white males 
under age 40 with no disabili-
ties or work-related health 
problems, workers have spe-
cial protections under federal 
and state laws against hiring 
practices that may have an 
adverse impact on them. As a 
practical matter, that means if 
members of a particular group 
are less likely to be recruited 
or hired, the employer must 
show that the hiring process is 
not discriminatory.
The only defense against 
evidence of adverse impact 
is for the employer to show 
that its hiring practices are 
valid—that is, they predict 
who will be a good employee 
in meaningful and statistically 
significant ways—and that 
no alternative would predict 
as well with less adverse 
impact. That analysis must be 
conducted with data on the 
employer’s own applicants 
and hires. The fact that the 
vendor that sold you the test 
you use has evidence that it 
was valid in other contexts is 
not sufficient. 
PROTECTING 
AGAINST 
DISCRIMINATION
56 HBR Special Issue | FALL 2019
HOW RECRUITING WORKS NOW YOUR APPROACH TO HIRING IS ALL WRONG
camera give help) is such a concern that eTeki and 
other specialized ven dors help employers figure 
out who is cheating in real time. 
Revamp your interviewing process. The 
amount of time employers spend on interviews 
has almost doubled since 2009, according to re-
search from Glassdoor. How much of that increase 
represents delays in setting up those interviews is 
impossible to tell, but it provides at least a partial 
explanation for why it takes longer to fill jobs now. 
Interviews are arguably the most difficult tech-
nique to get right, because interviewers should 
stick to questions that predict good hires—mainly 
about past behavior or performance that’s relevant 
to the tasks of the job—and ask them consistently 
across candidates. Just winging it and asking what-
ever comes to mind is next to useless. 
More important, interviews are where biases 
most easily show up, because interviewers do 
Since it can be difficult (if not impossible) to 
glean sufficient information about an outside 
applicant’s past performance, what other predic-
tors are good? There is remarkably little consensus 
even among experts. That’s mainly because a typi-
cal job can have so many tasks and aspects, and 
different factors predict success at different tasks.
There is general agreement, however, that test-
ing to see whether individuals have standard skills 
is about the best we can do. Can the candidate 
speak French? Can she do simple programming 
tasks? And so forth. But just doing the tests is not 
enough. The economists Mitchell Hoffman, Lisa 
B. Kahn, and Danielle Li found that even when 
companies conduct such tests, hiring managers 
often ignore them—and when they do, they get 
worse hires. The psychologist Nathan Kuncel 
and colleagues discovered that even when hiring 
managers use objective criteria and tests, applying 
their own weights and judgment to those criteria 
leads them to pick worse candidates than if they 
had used a standard formula. Only 40% of employ-
ers, however, do any tests of skills or general abili-
ties, including IQ. What are they doing instead? 
Seventy-four percent do drug tests, including for 
marijuana use; even employers in states where 
recreational use is now legal still seem to do so. 
Be wary of vendors bearing high-tech gifts. 
Into the testing void has come a new group of 
entrepreneurs who either are data scientists or 
have them in tow. They bring a fresh approach to 
the hiring process—but often with little under-
standing of how hiring actually works. John 
Sumser, of HRExaminer, an online newsletter 
that focuses on HR technology, estimates that 
on average, companies get five to seven pitches 
every day—almost all of them about hiring—from 
vendors using data science to address HR issues. 
These vendors have all sorts of cool-sounding 
assessments, such as computer games that can be 
scored to predict who will be a good hire. We don’t 
know whether any of these actually lead to better 
hires, because few of them are validated against 
actual job performance. That aside, these assess-
ments have spawned a counterwave of vendors 
who help candidates learn how to score well on 
them. Lloyds Bank, for example, developed a 
virtual-reality-based assessment of candidate 
potential, and JobTestPrep offers to teach poten-
tial candidates how to do well on it. Especially 
for IT and technical jobs, cheating on skills tests 
and even video interviews (where colleagues off 
Interviews are 
where biases 
most easily show 
up, because 
interviewers usually 
decide on the fly 
what to ask of 
whom and how 
to interpret the 
answer.
 
 
Organizations are much more interested in 
external talent than in their own employees 
to fill vacancies.
TOP CHANNELS FOR QUALITY HIRES
Based on a 2017 survey of 3,973 talent-acquisition decision makers 
who work in corporate HR departments and are LinkedIn members.
Source: LinkedIn
48%
46
40
34
28
Employee referrals
Third-party websites or online job boards
Social or professional networks
Third-party recruiters or staffing firms
Internal hires
The Grass IsAlways Greener...
FALL 2019 | HBR Special Issue 57
HBR.ORG
have only a trivial ability to predict who will be a 
good performer, particularly when many factors 
are involved. Machine learning, in contrast, can 
come up with highly predictive factors. Research 
by Evolv, a workforce analytics pioneer (now part 
of Cornerstone OnDemand), found that expected 
commuting distance for the candidate predicted 
turnover very well. But that’s not a question the 
psychological models thought to ask. (And even 
that question has problems.)
The advice on selection is straightforward: 
Test for skills. Ask assessments vendors to show 
evidence that they can actually predict who 
the good employees will be. Do fewer, more- 
consistent interviews.
The Way Forward
It’s impossible to get better at hiring if you can’t tell 
whether the candidates you select become good 
employees. If you don’t know where you’re going, 
any road will take you there. You must have a way 
to measure which employees are the best ones. 
Why is that not getting through to companies? 
Surveyed employers say the main reason they 
don’t examine whether their practices lead to bet-
ter hires is that measuring employee performance 
is difficult. Surely this is a prime example of mak-
ing the perfect the enemy of the good. Some as-
pects of performance are not difficult to measure: 
Do employees quit? Are they absent? Virtually all 
employers conduct performance appraisals. If 
you don’t trust them, try something simpler. Ask 
supervisors, “Do you regret hiring this individual? 
Would you hire him again?” 
Organizations that don’t check to see how well 
their practices predict the quality of their hires are 
lacking in one of the most consequential aspects 
of modern business. 
HBR Reprint R1903B
Peter Cappelli is the George W. Taylor Professor of 
Management at the Wharton School and the director 
of its Center for Human Resources. His most recent 
book is Will College Pay Off? A Guide to the Most 
Important Financial Decision You’ll Ever Make 
(PublicAffairs, 2015).
usually decide on the fly what to ask of whom 
and how to interpret the answer. Everyone knows 
some executive who is absolutely certain he 
knows the one question that will really predict 
good candidates (“If you were stranded on a desert 
island…”). The sociologist Lauren Rivera’s exami-
nation of interviews for elite positions, such as 
those in professional services firms, indicates that 
hobbies, particularly those associated with the 
rich, feature prominently as a selection criterion. 
Interviews are most important for assessing 
“fit with our culture,” which is the number one 
hiring criterion employers report using, according 
to research from the Rockefeller Foundation. It’s 
also one of the squishiest attributes to measure, 
because few organizations have an accurate and 
consistent view of their own culture—and even if 
they do, understanding what attributes represent 
a good fit is not straightforward. For example, 
does the fact that an applicant belonged to a 
fraternity reflect experience working with others 
or elitism or bad attitudes toward women? Should 
it be completely irrelevant? Letting someone 
with no experience or training make such calls is 
a recipe for bad hires and, of course, discrimina-
tory behavior. Think hard about whether your 
interviewing protocols make any sense and resist 
the urge to bring even more managers into the 
interview process.
Recognize the strengths and weaknesses 
of machine learning models. Culture fit is an-
other area into which new vendors are swarming. 
Typically they collect data from current employ-
ees, create a machine learning model to predict 
the attributes of the best ones, and then use that 
model to hire candidates with the same attributes. 
As with many other things in this new industry, 
that sounds good until you think about it; then it 
becomes replete with problems. Given the best 
performers of the past, the algorithm will almost 
certainly include white and male as key variables. 
If it’s restricted from using that category, it will 
come up with attributes associated with being a 
white male, such as playing rugby. 
Machine learning models do have the po-
tential to find important but previously uncon-
sidered relationships. Psychologists, who have 
dominated research on hiring, have been keen to 
study attributes relevant to their interests, such 
as personality, rather than asking the broader 
question “What identifies a potential good hire?” 
Their results gloss over the fact that they often 
Originally published in 
September–October 2018
IN 2016, General Electric announced that it 
was moving its longtime corporate head-
quarters from suburban Fairfield, Connecti-
cut, to downtown Boston. The company felt 
it needed to plug in to Boston’s high-tech 
young ventures and talent to become more 
innovative and digital—and ensure that it would 
be on the forefront of any emerging disrup-
tive technologies. Jeff Bornstein, then the CFO, 
summed up the advantage of Boston to the Wall 
Street Journal this way: “I can walk out my door 
and visit four start-ups. In Fairfield I couldn’t even 
walk out my door and get a sandwich.”
Leading cities have long had an outsize influence 
on the global economy, but today the impact that 
top talent clusters like Boston and San Francisco 
have on innovation is especially pronounced. In 
ILLUSTRATION BY JOANNA ŁAWNICZAK FALL 2019 | HBR Special Issue 59
2017, America’s 10 largest tech hubs accounted for 
58% of U.S. patents. Globally, cities such as Tokyo, 
Paris, Beijing, Shenzhen, and Seoul produced a 
similarly large proportion. The increased clout of 
these hubs poses a dilemma for companies that 
have historically located their leadership and 
talent in suburban industrial parks. Having a pres-
ence in innovation hotbeds is crucial, but it’s also 
extraordinarily expensive—especially in the nar-
row innovation districts within cities where most 
of the high-tech activity takes place. 
How can companies most effectively harness 
the benefits of these urban pools of knowledge and 
skills? In my work on global talent flows, I’ve seen 
corporations take three core approaches: At one ex-
treme, they relocate their headquarters, just as GE 
did. A less expensive and more easily reversible way 
Navigating 
Talent 
Hot Spots
How companies can benefit from innovation centers without necessarily relocating 
by William Kerr 
HOW RECRUITING WORKS NOW
60 HBR Special Issue | FALL 2019
HOW RECRUITING WORKS NOW NAVIGATING TALENT HOT SPOTS
to establish a brick-and-mortar foothold is to set up 
an innovation lab or corporate outpost in a talent 
cluster. The most conservative option is to organize 
executive retreats and immersive visits there. 
The three options are not mutually exclusive— 
especially since companies often need to keep 
in touch with several clusters—and each one 
involves substantial risks. But as the influence 
of a handful of global cities continues to grow, 
these approaches offer a playbook to companies 
that find themselves outside the action in today’s 
concentrated innovation geography. 
OPTION 1
Headquarters Moves 
While we tend to associate innovation hubs with 
entrepreneurs and start-ups, increasingly they’re 
the domain of incumbents, too. Twenty years ago 
inventors working in the top 10 cities for patenting 
activity accounted for fewer than half the patents 
filed by America’s 50 largest companies; their 
innovations were developed mostly in corporate 
labs in smaller cities. In 2017, by contrast, inven-
tors working in the top 10 cities accounted for 
almost 70% of the Fortune 50’s patent filings. Cor-
porations have gone from being underrepresented 
in tech hubs to exceeding the national average.
To some extent, this shift reflects the displace-
ment of legacy companies in the Fortune 50 by 
innovative firms such as Alphabet and Amazon. 
But other incumbents besides GE are moving 
resourcesto tech hubs. In 2016 packaged foods 
manufacturer Conagra, for instance, relocated its 
headquarters from Omaha, Nebraska, to Chicago 
in order to attract more Millennials and recruit 
senior talent with experience in consumer brands. 
While he praised Omaha, CEO Sean Connolly told 
the Omaha World-Herald, “Chicago is an envi-
ronment that offers us access to innovation and 
brand-building talent.” 
Though cross-state moves grab headlines, 
companies are also migrating out of less-dense 
areas surrounding talent clusters and into urban 
centers. In Boston, organizations relocating to the 
downtown area include Reebok, Converse, and 
much of the local venture capital industry. A local 
recruiting agency, WinterWyman, has reported 
that downtown Boston and Cambridge accounted 
for more than 60% of recent tech hires in the 
metropolitan area, compared with just 5% two 
decades ago. Conagra closed a suburban Chicago 
facility so that it could move more of its executive 
team into its downtown HQ. McDonald’s, Motorola 
Solutions, Kraft Heinz, and some 50 other com-
panies have also relocated to downtown Chicago 
from nearby suburbs. Greg Brown, the CEO of 
Motorola, noted that its HQ move would accelerate 
cultural change in the company and make recruit-
ing software developers and data scientists easier. 
The increased access to talent can be substan-
tial, since the share of the local college-educated 
workforce engaged in digital fields in hub cities is 
typically two to three times as high as the national 
average. Moreover, many talented young people 
want to work in hip downtown locations with 
sleek new offices, not aging suburban complexes 
with lots of parking. 
But a headquarters relocation poses several 
risks. For large incumbents it can be incredibly 
difficult, time-consuming, and expensive. The 
need to uproot an existing workforce, change 
legacy customer locations, and establish new local 
political connections and responsibilities means 
that any relocation will be disruptive, offsetting 
the advantages a talent cluster might offer. What’s 
more, HQ moves are hard to reverse. Because tal-
ent hot spots can rise and fall—in the 1950s, Silicon 
Valley was barely a dot on the economic map, 
and Detroit was the epicenter of rapidly growing 
industry—corporations may end up overinvesting 
in a temporary competitive advantage.
As the influence of 
a handful of global 
cities grows, these 
three approaches 
offer a playbook to 
companies that find 
themselves outside 
the action.
FALL 2019 | HBR Special Issue 61
HBR.ORG
Idea 
in Brief
THE SHIFT
Leading cities have long had an 
outsize influence on the global 
economy, but today the impact 
that top talent clusters such 
as Boston and San Francisco 
have on innovation is especially 
pronounced. 
THE CHALLENGE
Urban innovation hubs are 
extraordinarily expensive. How 
can companies harness the 
benefits of their dense pools of 
knowledge and skills in the most 
effective manner?
THE SOLUTION
Companies have three options: 
Relocate their headquarters to 
hubs; set up innovation labs or 
corporate outposts there; or run 
executive retreats and immer-
sions there.
One way to mitigate that risk is to build smaller 
headquarters that are focused on innovation and 
the key needs of top decision makers. GE is mov-
ing fewer than 800 people (out of a workforce of 
more than 300,000) to Boston; only those who are 
especially focused on innovation and digitization 
are being relocated. At some incumbents the top 
leaders already work mostly remotely, especially if 
they have heavy travel schedules. New corporate 
HQs are starting to look and operate more like 
the offices of unicorn start-ups than of industrial 
giants. Communication technologies and con-
nectivity allow corporate leadership to oversee 
operations with ever greater scope and scale from 
a small command post. 
This points to the second broad risk with 
headquarters moves: that ideas generated within 
the talent hub may fail to spread to the rest of the 
organization. Cutting-edge concepts picked up 
in Boston or Berlin will benefit a global company 
only if they improve the productivity of operations 
around the world. Moving key executives to talent 
clusters may distance leaders from other employ-
ees in the firm, whereas the older corporate HQs in 
suburban office parks tended to minimize internal 
distances. As a result, careful thought will have to 
go into diffusing acquired knowledge throughout 
the organization’s facilities.
Talent rotations can mitigate this risk. A study 
of an Indian R&D center at a leading multinational 
showed that short business trips to the firm’s U.S. 
headquarters boosted the productivity of the site’s 
scientists and engineers upon their return home, 
because they had gained technical knowledge and 
formed tighter personal relationships with leaders 
at headquarters and were better able to match peo-
ple’s skills to assignments. And as more companies 
are learning, communication technology is not a 
substitute for people flows but a complement. Yes, 
great videoconferencing technology helps, but 
there’s no better way than meeting in person to 
kick off or renew a relationship.
A third risk is negative press and the loss of 
political capital. No city wants a leading firm to 
leave, but the potential for ill will extends to new 
locations, too. Many companies seek tax breaks 
and other incentives for their new headquarters; 
it’s a delicate balancing act to secure preferential 
treatment but also be perceived as a partner in the 
new home city. Amazon has been criticized for the 
multiround bidding contest it held and the incen-
tives it sought when scouting sites for its second 
North American headquarters. As Apple began its 
search for the site of a fourth U.S. campus, CEO 
Tim Cook remarked that his company would not 
hold a beauty pageant like Amazon’s. “That’s not 
Apple,” he told Recode.
Headquarters moves must also deliver on high 
expectations. They must weather any changes 
in corporate leadership and the ups and downs 
of company performance. Shortly after John 
Flannery took over as CEO of GE, in 2017, the com-
pany announced that it would delay construction 
on its new $200 million building in Boston. And 
after GE announced job cuts, some of which would 
affect Boston workers, last fall, a local newspaper 
columnist wondered, “Was Boston sold a lemon?” 
GE remains committed to its new HQ but is also 
rethinking the role of the HQ as it works to 
realign itself.
A fourth risk that companies must guard against 
is a “leaky bucket.” Although they can recruit more 
easily in hubs, they can see ideas and talent flow 
out, too. In top clusters being an attractive local 
employer often means stacking up well against 
an Apple or a Spotify with competitive salaries 
and benefits.
Finally, there’s a risk of unintended and 
unforeseen consequences. Research shows that 
companies are more likely to close plants that 
are distant from HQs than plants close by, for 
instance. Headquarters moves permanently shift 
the internal workings of a firm in material ways. 
The company will also adopt more of the culture 
of the new home base—which was often the point 
of the move, after all—and executives will have a 
new peer group going forward. But for executives 
and directors looking to deeply transform their 
organizations, all those risks may be warranted.
OPTION 2
Creating Outposts and 
Innovation Labs
At many companies, moving the headquarters 
is not up for discussion. In September 2017, the 
same month that Amazon began its search for a 
second North American headquarters, Walmart 
announced the construction of a new head office 
in its longtime home of Bentonville, Arkansas. But 
even if Walmart remains forever rooted in Arkan-
sas, it has no intention of ceding the battle for the 
insights of talent clusters to the likes of Amazon 
(Seattle) and Alibaba (Hangzhou). Walmart Labs, 
62 HBR Special Issue | FALL2019
HOW RECRUITING WORKS NOW NAVIGATING TALENT HOT SPOTS
opened in 2011 in Silicon Valley, focuses on making 
advances, ranging from voice-enabled shopping 
to crowdsourced delivery, on the frontiers of 
e-commerce. 
Many companies a small fraction of Walmart’s 
size have opened similar corporate outposts in 
order to access important talent clusters in their 
industries. Such offices can serve a range of func-
tions. Some simply house a small team that listens 
to what’s going on locally and scouts out business 
development opportunities. Some establish an 
innovation lab like Walmart’s that works on new 
technology development. At others, companies 
focus on corporate venturing—partly to make a 
financial return on investments, but more to have 
a better vantage point on new advances. 
Companies benefit most from innovation when 
they acquire the best ideas, not when their average 
ideas are better. A physical presence in leading 
clusters helps companies connect with the most 
powerful concepts emerging in their sector. Corpo-
rate outposts are relatively inexpensive to launch, 
at least compared with HQ moves, and some com-
panies effectively buy one by acquiring a young 
tech start-up. An important step in the launch of 
Walmart Labs, for instance, was the retail giant’s 
purchase of Kosmix in 2011. 
Companies often want a presence in two or 
more clusters. One never knows where the next 
top idea will emerge, and firms can compete for 
talent better when they touch multiple clusters at 
once. Microsoft Research, for example, has built a 
network of labs outside Redmond, Washington, in 
locations that include Cambridge, Massachusetts; 
Cambridge, England; New York; Montreal; Beijing; 
and Bangalore. The Chinese white-goods giant 
Haier has five R&D centers—within and outside 
top clusters in the United States, Europe, Japan, 
Australia, and China—which are helping it stake 
out a role in the internet of things. 
One of the major risks with outposts is being 
“penny-wise and pound-foolish” when selecting 
real estate. Location matters even within cities. The 
costs of locating close to Sand Hill Road or Market 
Street are substantially higher than elsewhere in 
the San Francisco area—but so are the benefits. 
A study of advertising agencies in Manhattan is 
illustrative. Manhattan’s agencies create about a 
quarter of all advertising in the United States. They 
rely on personal networking to share proj ect work, 
splitting larger jobs into parts that can be indepen-
dently attacked by each firm. However, the study 
found that sharing declines rapidly with geographi-
cal distance, disappearing entirely when two firms 
are more than half a mile apart. To successfully tap 
into the market, an ad agency requires not only a 
New York address but an address within a few city 
blocks of Madison Avenue.
The good news is that real estate vendors that 
make it less costly for companies to launch out-
posts are emerging. The coworking company CIC, 
for example, located in the heart of Kendall Square 
in Cambridge, Massachusetts, offers high-end, 
flexible office space on a month-to-month basis. 
CIC has created packages suitable for the innova-
tion outposts of large companies, and its clients 
have included Amazon, Bayer, PwC, and Royal 
Dutch Shell. CIC even houses a “Captains of In-
novation” program that links corporations to local 
innovators. 
An advantage of outposts is that companies can 
experiment and start with a small team—keeping 
the option open for investment down the road. 
Five years before announcing its move to Boston, 
GE launched an outpost in Silicon Valley to accel-
erate its digital innovation efforts. The one-person 
Companies benefit most from innovation 
when they acquire the best ideas, not when 
their average ideas are better.
FALL 2019 | HBR Special Issue 63
HBR.ORG
One effective countermeasure is to promote 
international knowledge transfer by distributing 
collaborative teams across locations. That way, 
a company’s innovations are more likely to build 
on the patents filed in several locations. This 
approach is used extensively when companies 
first open new international facilities, either as 
a deliberate hedge to protect intellectual prop-
erty or simply as a needed prop for the fledgling 
operations. Cross-border collaborative teams now 
account for 13% of the patents of large U.S. compa-
nies, up from just 1% in 1975. Though these global 
teams need to be carefully managed (see Tsedal 
Neeley’s HBR article “Global Teams That Work,” 
October 2015), they’re likely to grow in importance 
as companies seek more access to talent clusters.
office initially housed just Bill Ruh, an executive 
recruited from Cisco to lead a new lab. Over the 
next three years, he grew the office to 150 people, 
hiring Silicon Valley talent almost exclusively. 
The launch strategy kept initial needs small and 
allowed Ruh to shape the effort to Silicon Val-
ley’s practices rather than being restricted by GE’s 
typical playbook. His group would grow to 1,800 
employees and ultimately become its own busi-
ness unit, now branded GE Digital.
If outposts aren’t working out, they can be 
closed, but this reversibility carries its own risk. 
Companies often pull the plug too quickly, believ-
ing an operation is failing because they have 
unrealistic expectations about how quickly they’ll 
see results. Leaders must understand that it takes 
time to build relationships; three to six months 
is rarely sufficient. What makes talent clusters 
special is an enormous volume and diversity of ac-
tivity. The investment in start-ups housed within 
CIC’s coworking space alone exceeds the venture 
investment made in most U.S. states, for instance. 
There is much to learn before a new outpost can be 
effective, and discovery processes take time. This 
is especially true when organizations invest in a 
cluster far from home.
Another risk is that small teams away from 
the corporate center will be viewed as impotent, 
rendering outpost executives less interesting to 
local entrepreneurs and innovators. Empowering 
the local staff to make modest deals on behalf of 
the company goes a long way toward boosting the 
stature of an outpost’s leaders at the watercooler.
Perhaps most critical is the choice of initial 
outpost directors. These executives lend their per-
sonal credibility both internally to the corporation 
and externally to the cluster. One approach is to 
seek a “best of both worlds” launch team by com-
bining a relocating executive from the parent’s HQ 
with a star already working in the cluster. When 
a foreign company enters the United States, this lo-
cal talent is often an ex-pat of the same nationality 
as the parent organization. 
A final risk with innovation outposts is that the 
best ideas and innovations will not flow back to 
the parent company effectively. Studies of patent 
data show that poor internal transfer is especially 
pronounced in cross-border settings. This may 
explain why many firms are disappointed with 
the returns from overseas innovation work—if 
the right conditions aren’t set, the output tends 
to be isolated.
 
Follow the Money
Where are the global talent hot spots? Data 
on venture capital investment and unicorn 
start-ups (those with billion-dollar evaluations) 
point to these locations: 
Metro areas 
with the greatest 
VC investment 
(since 2009)
Source: Calculations from 
Thomson One data on 
venture capital funding 
Source: Calculations 
from CB Insights data
1. SAN FRANCISCO 
2. BEIJING
3. SHANGHAI
4. NEW YORK
5. BOSTON
6. LOS ANGELES
7. LONDON
8. SHENZHEN
9. SAN DIEGO
10. SEATTLE
Metro areas 
with the most 
unicorns 
(since 2009)
1. SAN FRANCISCO 
2. BEIJING
3. NEW YORK
4. LOS ANGELES
5. SHANGHAI
6. BOSTON
7. LONDON
8. SEATTLE
9. HANGZHOU
10. CHICAGO
64 HBR OnPoint | FALL 2019
HOW RECRUITING WORKS NOW NAVIGATING TALENT HOT SPOTS
The global telecom giant Vodafone has also 
made executive immersions partof its innovation 
strategy. The company is based in London, 
a premier talent cluster, but outgoing CEO Vit-
torio Colao strongly feels that Vodafone must tap 
into other clusters to stay on the cutting edge in 
communication technologies and other 
advanced technologies that affect firm opera-
tions. Every year the top 50 Vodafone executives 
take a weeklong trip to Silicon Valley together to 
broaden their perspectives. Many other compa-
nies organize similar visits to New York, London, 
Boston, Shanghai, and other clusters for their 
executives or board members. (I myself have 
organized corporate immersions in Boston, and 
this article draws on those experiences. None 
of the companies mentioned in this article have 
been my clients, however.)
But many firms underinvest in immersions, 
for two reasons: Executives view the trip as a 
semi- vacation or, at the other extreme, can’t 
extract themselves from e-mails about daily 
operations to the team back home. The CEO must 
emphasize immersions’ high price—especially the 
opportunity costs related to executive time—to all 
participants. Mandates from the CEO regarding 
prework for the trip will set the tone, and nothing 
keeps executives off their smartphones the way 
the CEO’s mindful eye and visible passion do. An 
all-in mentality for leaders makes the immersion 
a success, and trips should be planned at times 
when that kind of dedication is realistic for the 
executive team.
A second risk is that participants in immersions 
won’t dig deep enough. Visits to local companies 
OPTION 3
Executive Retreats and Immersions
Executive visits to top talent clusters can be a 
cost-effective way to increase awareness and 
excitement about efforts to accelerate innovation 
and reshape business models and management 
approaches. Though a weeklong trip rarely pro-
vides the missing piece to a company’s innovation 
puzzle, it can help executives build a grounded 
understanding of what’s happening at the frontier 
and how their companies may need to react. 
In 2014 executives at the large European bank 
ING Netherlands felt that their organization, while 
profitable and seemingly stable, was not realizing 
its full potential in a financial services sector 
that was rapidly being revolutionized. So they 
embarked on visits to Spotify, Google, Netflix, 
Zappos, and other innovative companies to ex-
plore new possibilities. 
Those trips led the executives to reimagine 
ING Netherlands as a smaller, nimbler organiza-
tion with a stronger customer focus. To fulfill 
that new vision, the company would adopt agile 
team methodology throughout the organization, 
reduce head count at its Dutch headquarters by 
25%, and redesign its facilities to have open floor 
plans without offices (even for the CEO) in order 
to foster new team interactions. Every person 
at headquarters had to reapply for a job, and all 
positions would be quite different under the new 
system. The transformation went live in 2015. CEO 
Vincent van den Boogert has been very pleased 
with the gains ING Netherlands has made since 
then in product innovation, customer satisfaction, 
and digital talent acquisition. 
 
Starwood Hotels has moved its entire 
corporate headquarters from America to 
China, India, and the United Arab Emirates 
for monthlong immersions.
FALL 2019 | HBR Special Issue 65
HBR.ORG
many tech giants blind to a backlash on issues like 
privacy, data security, and surveillance. Executives 
participating in immersions may be dazzled by the 
wrong things, when they should be listening care-
fully and asking questions. 
A STRIKING FEATURE of today’s business land-
scape is the growing concentration of innovation 
activity— and the exceptional talent associated 
with it—into a small number of geographic 
clusters. As new technologies continue to disrupt 
industries, the fate of corporations will increas-
ingly be determined in these hot spots. By taking 
one or more of the approaches I’ve outlined here, 
companies can access the intelligence in these 
key locations and keep up with the fast pace 
of change. 
HBR Reprint R1805E
William Kerr is the Dimitri V. D’Arbeloff–MBA Class of 
1955 Professor of Business Administration at Harvard 
Business School and the author of The Gift of Global 
Talent: How Migration Shapes Business, Economy & 
Society (Stanford University Press, 2018).
can be informative and inspiring, but not if they 
don’t get past preset professional tours. ING’s 
visit to Spotify became much more effective, for 
instance, when people at the Swedish music com-
pany began to relate the costs and challenges of 
adopting agile methodology, not just the benefits. 
One (rare) route to deep immersion is to park 
the leadership team abroad for an extended time. 
To obtain insights on innovative technology and 
services in emerging regions, Starwood Hotels 
has moved its entire corporate headquarters from 
America to China, India, and the United Arab 
Emirates for monthlong immersions. With shorter 
trips, visiting companies need to organize tailored 
sessions with local experts (such as business lead-
ers and university faculty members) to achieve 
greater learning.
Companies also must ensure that the insights 
gathered are acted on back home. A one-off immer-
sion may deliver short-term change while it’s top of 
mind for executives, but its lessons may soon get 
crowded out by other priorities. Tying immersions 
to a regular strategy or leadership-building process 
is a good way to capture their benefits. Immersions 
that have clear links to important corporate work 
before and after the retreat will have the strongest 
power, and executives should spend time on the 
trip itself debating and applying insights. 
Vodafone offers a good example of how to 
leverage an immersion’s insights back home. The 
company invites its top 250 employees to London 
for three-day training sessions on the advanced 
technologies its top 50 leaders have studied. This 
program—which includes exercises like building a 
rudimentary chatbot for ordering coffee—pushes 
familiarity with the technologies into the organi-
zation’s second tier of leadership. To spread the 
insights throughout its vast organization, the com-
pany incorporates the emerging technology trends 
it has identified into personalized learning pro-
grams on its digital Vodafone University platform. 
(Vodafone also pairs leaders with young “digital 
ninjas” to provide ongoing upward mentoring on 
emerging technology trends and applications.) 
A final risk is that executives will bring the 
wrong insights home with them. Clusters excel 
when the local community buys into the same pri-
orities and perspectives, such as the deep respect 
given in Silicon Valley to people who launch game-
changing companies. But any tightly knit place can 
also suffer from groupthink. Silicon Valley’s “move 
fast and break things” ethos has arguably left 
66 HBR Special Issue | FALL 2019
observations—many years’ 
worth of job performance data 
even for a large employer.) As 
Amazon learned, the past may 
be very different from the fu-
ture you seek. It discovered that 
the hiring algorithm it had been 
working on since 2014 gave 
lower scores to women—even 
to attributes associated with 
women, such as participating 
in women’s studies programs—
because historically the best 
performers in the company had 
disproportionately been men. 
So the algorithm looked for 
people just like them. Unable to 
fix that problem, the company 
stopped using the algorithm in 
2017. Nonetheless, many other 
companies are pressing ahead.
The underlying challenge for 
data scientists is that hiring is 
simply not like trying to predict, 
say, when a ball bearing will 
fail—a question for which any 
predictive measure might do. 
Hiring is so consequential that 
it is governed not just by legal 
frameworks but by fundamen-
tal notions of fairness. The fact 
that some criteria are associated 
with good job performance is 
necessary butnot sufficient for 
using it in hiring. 
Take a variable that data 
scientists have found to have 
predictive value: commuting 
distance to the job. According 
to the data, people with longer 
commutes suffer higher rates of 
attrition. However, commuting M
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Quick Takes
Data Science Can’t Fix Hiring (Yet)
by Peter Cappelli 
All analytic approaches 
to picking candidates 
are backward looking —
they are based on 
outcomes that have 
already happened.
HOW RECRUITING WORKS NOW
by simply looking at attributes 
of the “best performers” in 
workplaces and then identify-
ing which job candidates have 
the same attributes. They use 
anything that’s easy to mea-
sure: facial expressions, word 
choice, comments on social me-
dia, and so forth. But a failure 
to check for any real difference 
between high-performing and 
low-performing employees on 
these attributes limits their use-
fulness. Furthermore, scooping 
up data from social media or the 
websites people have visited 
also raises important questions 
about privacy. True, the infor-
mation can be accessed legally, 
but the individuals who created 
the postings didn’t intend or 
authorize them to be used for 
such purposes. Furthermore, 
is it fair that something you 
posted as an undergrad can end 
up driving your hiring algorithm 
a generation later?
Another problem with 
machine learning approaches is 
that few employers collect the 
large volumes of data—number 
of hires, performance apprais-
als, and so on—that the algo-
rithms require to make accurate 
predictions. Although vendors 
can theoretically overcome that 
hurdle by aggregating data 
from many employers, they 
don’t really know whether 
individual company contexts 
are so distinct that predictions 
based on data from the many 
are inaccurate for the one.
Yet another issue is that all 
analytic approaches to pick-
ing candidates are backward 
looking—they are based on 
outcomes that have already 
happened. (Algorithms are 
especially reliant on past expe-
riences in part because building 
them requires lots and lots of 
RECRUITING MANAGERS desper-
ately need new tools, because 
the existing ones—unstructured 
interviews, personality tests, 
personal referrals—aren’t very 
effective. The newest develop-
ment in hiring, which is both 
promising and worrying, is 
the rise of data science–driven 
algorithms to find and assess job 
candidates. By my count, more 
than 100 vendors are creating 
and selling these tools to com-
panies. Unfortunately, data sci-
ence—which is still in its infancy 
when it comes to recruiting and 
hiring—is not yet the panacea 
employers hope for.
Vendors of these new tools 
promise they will help reduce 
the role that social bias plays in 
hiring. And the algorithms can 
indeed help identify good job 
candidates who would previ-
ously have been screened out 
for lack of a certain education or 
social pedigree. But these tools 
may also identify and promote 
the use of predictive variables 
that are (or should be) troubling. 
Because most data scientists 
seem to know so little about the 
context of employment, their 
tools are often worse than noth-
ing. For instance, an astonishing 
percentage build their models 
HBR.ORG
FALL 2019 | HBR Special Issue 67
ing millions of job candidates 
data-driven insights on their 
strengths, development needs, 
and potential career and orga-
nizational fit. In particular, we 
have seen the rapid growth (and 
corresponding venture capital 
investment) in game-based 
assessments, bots for scraping 
social media postings, linguistic 
analysis of candidates’ writing 
samples, and video-based in-
terviews that utilize algorithms 
to analyze speech content, tone 
of voice, emotional states, non-
verbal behaviors, and tempera-
mental clues.
DIGITAL INNOVATIONS and 
advances in AI have produced 
a range of novel talent identi-
fication and assessment tools. 
Many of these technologies 
promise to help organizations 
improve their ability to find 
the right person for the right 
job, and screen out the wrong 
people for the wrong jobs, faster 
and cheaper than ever before.
These tools put unprec-
edented power in the hands of 
organizations to pursue data-
based human capital decisions. 
They also have the potential 
to democratize feedback, giv-
distance is governed by where 
you live—which is governed 
by housing prices and relates 
to income and race. Picking 
whom to hire on the basis of 
where they live most likely has 
an adverse impact on protected 
groups such as racial minorities. 
Unless no other criterion 
predicts at least as well as the 
one being used—and that is ex-
tremely difficult to determine in 
machine learning algorithms—
companies violate the law if 
they use hiring criteria that 
have adverse impacts. Even 
then, to stay on the right side 
of the law, they must show 
why the criterion creates good 
performance. That might be 
possible in the case of com-
muting time, but—at least for 
the moment—it is not for facial 
expressions, social media post-
ings, or other measures whose 
significance companies cannot 
demonstrate. 
In the end, the drawback to 
using algorithms is that we’re 
trying to use them on the 
cheap: building them by looking 
only at best performers rather 
than all performers, using 
only measures that are easy to 
gather, and relying on vendors’ 
claims that the algorithms work 
elsewhere rather than observ-
ing the results with our own 
employees. Not only is there no 
free lunch here, but you might 
be better off skipping the cheap 
meal altogether.
Originally published in Harvard Business 
Review May–June 2019
HBR Reprint R1903B
Peter Cappelli is the George W. Taylor 
Professor of Management at the Wharton 
School and the director of its Center for 
Human Resources. His most recent book 
is Will College Pay Off? A Guide to the 
Most Important Financial Decision You’ll 
Ever Make (PublicAffairs, 2015).
Although these novel tools 
are disrupting the recruitment 
and assessment space, they 
leave many yet-unanswered 
questions about their ac-
curacy and the ethical, legal, 
and privacy implications they 
introduce. This is especially 
true when compared with more 
long-standing psychometric 
assessments—such as the NEO 
PI-R, the Wonderlic test, the 
Raven’s Progressive Matrices 
test, or the Hogan Personal-
ity Inventory—that have been 
scientifically derived and care-
fully validated vis-à-vis relevant 
jobs, identifying reliable as-
sociations between applicants’ 
scores and their subsequent 
job performance (publishing 
the evidence in independent, 
trustworthy, scholarly journals). 
Recently, there has even been 
interest and concern in the U.S. 
Senate about whether new 
technologies (specifically, facial 
analysis technologies) might 
have negative implications for 
equal opportunity among job 
candidates.
In this article, we focus on 
the potential repercussions 
of new technologies on the 
privacy of job candidates, as 
well as the implications for 
candidates’ protections under 
the Americans with Disabilities 
Act (ADA) and other federal 
and state employment laws. 
Employers recognize that 
they can’t or shouldn’t ask 
candidates about their family 
status or political orientation, 
or whether they are pregnant, 
straight, gay, sad, lonely, 
depressed, or physically or 
mentally ill; drinking too much; 
abusing drugs; or sleeping too 
little. However, new tech-
nologies may already be able to 
discern many of these factors 
The Legal and Ethical Implications 
of Using AI in Hiring
by Ben Dattner, Tomas Chamorro-Premuzic, 
Richard Buchband, and Lucinda Schettler
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68 HBR Special Issue | FALL 2019
HOW RECRUITING WORKS NOW QUICK TAKES
able to determine “proxy” vari-
ables for private, personal attri-
butes with increased accuracy. 
Today, for example, Facebook 
“likes” can be used to infer 
sexual orientation and race with 
considerable accuracy.Political 
affiliation and religious beliefs 
are just as easily identifiable. 
Might companies be tempted 
to use tools like these to screen 
candidates, believing that be-
cause decisions aren’t made di-
rectly on the basis of protected 
characteristics, they aren’t 
legally actionable? While an 
employer may not violate any 
laws in merely discerning an 
applicant’s personal informa-
tion, the company may become 
vulnerable to legal exposure 
if it makes adverse employ-
ment decisions by relying on 
any protected categories such 
as one’s place of birth, race, or 
native language—or on the basis 
of private information it doesn’t 
have the right to consider, such 
as possible physical illness or 
mental ailment. How the courts 
will handle situations where 
employers have relied on tools 
using these proxy variables is 
unclear, but the fact remains 
that it is unlawful to take an 
adverse action on the basis of 
certain protected or private 
characteristics—no matter how 
these were learned or inferred.
This might also apply to 
facial recognition software, as 
recent research predicts that 
face-reading AI may soon be 
able to discern candidates’ 
sexual and political orienta-
tion, as well as internal states 
like mood or emotion, with a 
high degree of accuracy. How 
might the application of the 
ADA change? In addition, the 
Employee Polygraph Protection 
Act generally prohibits employ-
to individual differences in 
job performance. If a tool 
shows a preference for speech 
patterns (such as consistent 
vocal cadence or pitch or a 
“friendly” tone of voice) that 
do not have an adverse impact 
on job candidates in a legally 
protected group, then there is 
no legal issue, but these tools 
may not have been scientifi-
cally validated and therefore 
are not controlling for poten-
tial discriminatory adverse 
impact—meaning the employer 
may incur liability for any blind 
reliance. In addition, there are 
yet no convincing hypotheses 
or defensible conclusions about 
whether it would be ethical 
to screen out people on the 
basis of their voices, which are 
physiologically determined, 
largely unchangeable personal 
attributes.
Likewise, social media 
activity—such as Facebook or 
Twitter usage—has been found 
to reflect people’s intelligence 
and personality, including their 
dark-side traits. But is it ethical 
to mine this data for hiring pur-
poses when users generally use 
such apps for different purposes 
and may not have provided 
their consent for data analysis 
to draw private conclusions 
from their public postings?
When used in the hiring 
context, new technologies raise 
a number of new ethical and 
legal questions around privacy, 
which we think should be 
publicly discussed and debated, 
namely:
1. What temptations will 
companies face in terms of 
candidate privacy relating 
to personal attributes?
As technology advances, big 
data and AI will continue to be 
is using an assessment that 
has been found to have such 
an adverse impact, which is 
defined by the relative scores 
of different protected groups, 
the employer has to prove that 
the assessment methodology 
is job-related and predictive of 
success in the specific jobs in 
question.
Personality assessments are 
less likely to expose employers 
to possible liability for dis-
crimination, because there is 
little to no correlation between 
personality characteristics and 
protected demographic vari-
ables or disabilities. It should 
also be noted that the relation-
ship between personality and 
job performance depends on 
the context (for example, type 
of role or job).
Unfortunately, there is far 
less information about the new 
generation of talent tools that 
are increasingly used in prehire 
assessment. Many of these tools 
have emerged as technological 
innovations, rather than from 
scientifically derived meth-
ods or research programs. As 
a result, it is not always clear 
what they assess, whether 
their underlying hypotheses 
are valid, or how they predict 
job candidates’ performance. 
For example, physical proper-
ties of speech and the human 
voice—which have long been 
associated with elements of 
personality—have been linked 
indirectly and without proper 
(or even any) consent.
Before delving into the cur-
rent ambiguities of the brave 
new world of job candidate 
assessment and evaluation, 
it’s helpful to look at the past. 
Psychometric assessments have 
been in use for more than 100 
years and became more widely 
used as a result of the U.S. 
military’s Army Alpha, which 
placed recruits into categories 
and determined their likelihood 
of being successful in various 
roles. Traditionally, psycho-
metrics fell into three broad 
categories: cognitive ability or 
intelligence, personality or tem-
perament, and mental health or 
clinical diagnosis.
Since the adoption of the 
ADA in 1990, employers are 
generally forbidden from 
inquiring about or using physi-
cal disability, mental health, or 
clinical diagnosis as a factor in 
preemployment candidate as-
sessments, and companies that 
have done so have been sued 
and censured. In essence, dis-
abilities—whether physical or 
mental—have been determined 
to be private information that 
employers cannot inquire about 
at the preemployment stage, 
just as employers shouldn’t ask 
applicants intrusive questions 
about their personal lives and 
can’t take private demographic 
information into account in hir-
ing decisions.
Cognitive ability and intel-
ligence testing are reliable and 
valid predictors of job success 
in many occupations; how-
ever, these kinds of assess-
ments can be discriminatory if 
they adversely impact certain 
protected groups, such as those 
defined by gender, race, age, or 
national origin. If an employer 
Many talent tools have 
emerged as technological 
innovations, rather 
than from scientifically 
derived methods or 
research programs.
HBR.ORG
FALL 2019 | HBR Special Issue 69
learning, employers will have 
greater access to candidates’ 
private lives, private attributes, 
and private challenges and 
states of mind. There are no 
easy answers to many of the 
new questions about privacy we 
have raised here, but we believe 
that they are all worthy of pub-
lic discussion and debate.
Originally published on HBR.org 
April 25, 2019
HBR Reprint H04X5S
Ben Dattner is an executive coach 
and organizational development 
consultant, and the founder of New 
York City–based Dattner Consulting. 
Follow him on Twitter: @bendattner. 
Tomas Chamorro-Premuzic is the chief 
talent scientist at ManpowerGroup, a 
professor of business psychology at 
University College London and Columbia 
University, and a cofounder of Deeper 
Signals and MetaProfiling. He’s also the 
author of Why Do So Many Incompetent 
Men Become Leaders? (And How to Fix It) 
(Harvard Business Review Press, 2019). 
Follow him on Twitter: @drtcp. Richard 
Buchband is the senior vice president, 
general counsel, and secretary at Man-
powerGroup and a member of the New 
York Stock Exchange Listed Company 
Advisory Board. Lucinda Schettler is 
a senior attorney for ManpowerGroup, 
specializing in employment law in the 
U.S. She focuses on the legal issues 
implicated in the ever-changing world 
of work, including AI and the use of 
technology. 
Opportunity Commission issued 
guidance to say that the expand-
ing list of personality disorders 
described in the psychiatric 
literature could qualify as men-
tal impairments, and the ADA 
Amendments Act made it easier 
for an individual to establish 
that he or she has a disability 
within the meaning of the ADA. 
As a result, the category of 
people protected under the ADA 
may now include those who 
have significant problems com-
municating in social situations, 
issues concentrating, or diffi-
culty interacting with others.
In addition to raising new 
questions about disabilities, 
technology also presents new 
dilemmas with respect to differ-
ences, whether demographic or 
otherwise. There have alreadybeen high-profile real-life 
situations where these systems 
have revealed learned biases, 
especially relating to race and 
gender. Amazon, for example, 
developed an automated tal-
ent search program to review 
résumés— which was aban-
doned after the company real-
ized that the program wasn’t 
rating candidates in a gender-
neutral way. To reduce such 
biases, developers are balanc-
ing the data used for training 
AI models to appropriately 
represent all groups. The more 
information the technology has 
and can account for and learn 
from, the better it can control 
for potential bias.
In conclusion, new technolo-
gies can already cross the lines 
between public and private 
attributes, traits, and states of 
mind in new ways, and there is 
every reason to believe that in 
the future they will be increas-
ingly able to do so. Using AI, big 
data, social media, and machine 
law. With regard to social media 
specifically, states began intro-
ducing legislation back in 2012 
to prevent employers from re-
questing passwords to personal 
internet accounts as a condition 
of employment. More than 20 
states have enacted these types 
of laws that apply to employers; 
however, in terms of general 
privacy in the use of new tech-
nologies in the workplace, there 
has been less specific guidance 
or action. In particular, legisla-
tion has passed in California 
that will potentially constrain 
employers’ use of candidate or 
employee data. In general, state 
and federal courts have yet to 
adopt a unified framework for 
analyzing employee privacy as 
related to new technology. 
The takeaway is that at least 
for now, employee privacy in 
the age of big data remains un-
settled. This puts employers in 
a conflicted position that calls 
out for caution: Cutting-edge 
technology is available that 
may be extremely useful, but 
it’s providing information that 
has previously been considered 
private. Is it legal to use in a hir-
ing context? And is it ethical to 
consider if the candidate didn’t 
consent?
3. What temptations will 
companies face in terms of 
candidate privacy relating 
to disabilities?
The ADA puts mental dis-
abilities squarely in its purview, 
alongside physical disabilities, 
and defines an individual as 
disabled if the impairment 
substantially limits a major life 
activity, the person has a record 
of such an impairment, or the 
person is perceived to have such 
an impairment. About a decade 
ago, the U.S. Equal Employment 
ers from using lie detector tests 
as a preemployment screening 
tool, and the Genetic Informa-
tion Nondiscrimination Act 
prohibits employers from using 
genetic information in employ-
ment decisions. But what if the 
exact same kind of information 
about truth, lies, or genetic at-
tributes could be determined by 
the above-mentioned techno-
logical tools?
2. What temptations will 
companies face in terms of 
candidate privacy relating 
to lifestyle and activities?
Employers can now access 
information such as one 
candidate’s online “check-in” 
to her church every Sunday 
morning, another candidate’s 
review of the dementia care 
facility into which he has placed 
his elderly parent, and a third’s 
divorce filing in civil court. All 
these things, and many more, 
are easily discoverable in the 
digital era. Big data is following 
us everywhere we go online 
and collecting and assembling 
information that can be sliced 
and diced by tools we can’t even 
imagine yet—tools that could 
possibly inform future employ-
ers about our fitness (or lack 
thereof) for certain roles. And 
big data is only going to get big-
ger; according to experts, 90% 
of the data in the world was 
generated just in the past two 
years alone. With the expan-
sion of data comes the poten-
tial expansion for misuse and 
resulting discrimination—either 
deliberate or unintentional.
Unlike the EU, which has har-
monized its approach to privacy 
under the General Data Protec-
tion Regulation, the U.S. relies 
on a patchwork approach to 
privacy driven largely by state 
70 HBR Special Issue | FALL 2019
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task force of senior business 
leaders, PhDs in industrial and 
organizational psychology, 
data scientists, and experts in 
recruiting. Some people asked, 
“Why overhaul a recruiting 
process that has proved so 
successful?” and “Don’t you 
already have many more quali-
fied applicants than available 
jobs?” These were reasonable 
questions. But often staying 
successful is about learning and 
changing rather than sticking to 
the tried-and-true.
Each year we hire up to 3,000 
summer interns and nearly as 
many new analysts directly 
from campuses. In our eyes, 
these are the firm’s future 
leaders, so it made sense to 
focus our initial reforms there. 
They involved two major addi-
tions to our campus recruiting 
strategy—video interviews and 
structured interviewing.
Asynchronous video inter-
views. Traditionally we had 
flown recruiters and business 
professionals to universities 
for first-round interviews. The 
schools would give us a set 
date and number of time slots 
to meet with students. That is 
most definitely not a scalable 
model. It restricted us to a 
smaller number of campuses 
and only as many students as 
we could squeeze into a limited 
schedule. It also meant that we 
tended to focus on top-ranked 
schools. How many qualified 
candidates were at a school 
became more important than 
who were the most talented 
students regardless of their 
school. However, we knew 
that candidates didn’t have to 
attend Harvard, Princeton, or 
Oxford to excel at Goldman 
Sachs—our leadership ranks 
were already rich with people 
GOLDMAN SACHS is a people-
centric business—every day 
our employees engage with our 
clients to find solutions to their 
challenges. As a consequence, 
hiring extraordinary talent is vi-
tal to our success and can never 
be taken for granted. In the 
wake of the 2008 financial crisis 
we faced a challenge that was, 
frankly, relatively new to our 
now 150-year-old firm. For de-
cades investment banking had 
been one of the most sought-
after, exciting, and fast-growing 
industries in the world. That 
made sense—we were grow-
ing by double digits and had 
high returns, which meant that 
opportunity and reward were 
in great supply. However, the 
crash took some of the sheen 
off our industry; both growth 
and returns moderated. And 
simultaneously, the battle for 
talent intensified—within and 
outside our industry. Many of 
the candidates we were pursu-
ing were heading off to Silicon 
Valley, private equity, or start-
ups. Furthermore, we were no 
longer principally looking for a 
specialized cadre of accounting, 
finance, and economics majors: 
New skills, especially coding, 
were in huge demand at Gold-
man Sachs—and pretty much 
everywhere else. The wind 
had shifted from our backs to 
our faces, and we needed to 
respond. 
Not long ago the firm relied 
on a narrower set of factors for 
identifying “the best” students, 
such as school, GPA, major, 
leadership roles, and relevant 
experience—the classic résumé 
topics. No longer. We decided 
to replace our hiring playbook 
with emerging best practices 
for assessment and recruit-
ment, so we put together a 
Expanding 
the Pool
How Goldman Sachs Changed 
the Way It Recruits
by Dane E. Holmes 
FALL 2019 | HBR Special Issue 71
HBR.ORG
our firm and our culture. Our 
structured interview questions 
are designed to assess candi-
dates on 10 core competencies, 
including analytical think-
ing and integrity, which we 
know correlate with long-term 
success at the firm. They are 
evaluated on six competen-
cies in the first round; if they 
progress, they’re assessed on 
the remaining four during in-
person interviews. 
We have a rotating library 
of questions for each compe-
tency, along with a rubric for 
interviewers that explains how 
to rate responses on a five-
point scale from “outstanding” 
to “poor.” We also trainour 
interviewers to conduct struc-
tured interviews, provide them 
with prep materials immedi-
ately before they interview a 
candidate, and run detailed 
calibration meetings using all 
the candidate data we’ve gath-
ered throughout the recruiting 
process to ensure that certain 
interviewers aren’t introducing 
grade inflation (or deflation). 
We’re experimenting with 
prehire assessment tests to be 
paired with these interviews; 
we already offer a technical 
coding and math exam for 
applicants to our engineering 
organization.
We decided not to pilot 
these changes and instead 
rolled them out en masse, 
because we realized that buy-in 
would come from being able 
to show results quickly—and 
because we know that no 
schedule. (Our data shows that 
they prefer Thursday or Sunday 
night—whereas our previ-
ous practice was to interview 
during working hours.) We 
suspected that if the process 
was a turnoff for applicants, 
we would see a dip in the 
percentage who accepted our 
interviews and our offers. That 
hasn’t happened.
Structured questioning and 
assessments. How can you cre-
ate an assessment process that 
not only helps select top talent 
but focuses on specific charac-
teristics associated with suc-
cess? Define it, structure it, and 
don’t deviate from it. Research 
shows that structured inter-
views are effective at assessing 
candidates and helping predict 
job performance. So we ask 
candidates about specific ex-
periences they’ve had that are 
similar to situations they may 
face at Goldman Sachs (“Tell 
me about a time when you 
were working on a project with 
someone who was not complet-
ing his or her tasks”) and pose 
hypothetical scenarios they 
might encounter in the future 
(“In an elevator, you overhear 
confidential information about 
a coworker who is also a friend. 
The friend approaches you and 
asks if you’ve heard anything 
negative about him recently. 
What do you do?”). 
Essentially, we are focused 
less on past achievements 
and more on understanding 
whether a candidate has quali-
ties that will positively affect 
the United States, where the 
majority of our student hires 
historically came from “target 
schools,” the opposite is now 
true. The top of our recruiting 
funnel is wider, and the output 
is more diverse.
Being a people-driven 
business, we have worked 
hard to ensure that the video 
interviews don’t feel cold and 
impersonal. They are only one 
component of a broader process 
that makes up the Goldman 
Sachs recruitment experience. 
We still regularly send Goldman 
professionals to campuses to 
engage directly with students at 
informational sessions, “coffee 
chats,” and other recruiting 
events. But now our goal is 
much more to share informa-
tion than to assess candidates, 
because we want people to 
understand the firm and what 
it offers before they tell us why 
they want an internship or a job.
We also want them to be as 
well prepared as possible for 
our interview process. Our 
goal is a level playing field. To 
help achieve it, we’ve created 
tip sheets and instructions on 
preparing for a video interview. 
Because the platform doesn’t 
allow videos to be edited once 
they’ve been recorded, we offer 
a practice question before the 
interview begins and a count-
down before the questions are 
asked. We also give students a 
formal channel for escalating is-
sues should technical problems 
arise, though that rarely occurs.
We’re confident that this 
approach has created a better 
experience for recruits. It uses a 
medium they’ve grown up with 
(video), and most important, 
they can do their interviews 
when they feel fresh and at 
a time that works with their 
from other schools. What’s 
more, as we’ve built offices in 
new cities and geographic loca-
tions, we’ve needed to recruit 
at more schools located in 
those areas. Video interviews 
allow us to do that.
At a time when companies 
were just beginning to experi-
ment with digital interviewing, 
we decided to use “asynchro-
nous” video interviews—in 
which candidates record 
their answers to interview 
questions—for all first-round 
interactions with candidates. 
Our recruiters record standard-
ized questions and send them 
to students, who have three 
days to return videos of their 
answers. This can be done on 
a computer or a mobile device. 
Our recruiters and business 
professionals review the videos 
to narrow the pool and then 
invite the selected applicants to 
a Goldman Sachs office for final-
round, in-person interviews. 
(To create the video platform, 
we partnered with a company 
and built our own digital solu-
tion around its product.)
This approach has had a 
meaningful impact in two 
ways. First, with limited effort, 
we can now spend more time 
getting to know the people 
who apply for jobs at Goldman 
Sachs. In 2015, the year before 
we rolled out this platform, we 
interviewed fewer than 20% 
of all our campus applicants; 
in 2018 almost 40% of the stu-
dents who applied to the firm 
participated in a first-round 
interview. Second, we now en-
counter talent from places we 
previously didn’t get to. In 2015 
we interviewed students from 
798 schools around the world, 
compared with 1,268 for our 
most recent incoming class. In 
We are focused less on past achievements and more 
on understanding whether a candidate has qualities 
that will positively affect our firm and our culture. Our 
structured interview questions are designed to assess 
10 core competencies.
72 HBR Special Issue | FALL 2019
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taking a quick Snapchat break 
might come across the targeted 
“Fly higher!” message and 
think, Hey, maybe it’s time for 
a change.
The fight for new recruits is 
intense—not just in the tech 
sector but across all industries. 
But as the Snapchat story 
establishes, connecting with 
today’s workforce no longer 
simply means going to the usual 
places and doing the usual 
things. These days, I advise 
Fortune 500 executives to treat 
talent as they would custom-
ers: Understand their behavior, 
and design recruiting strategies 
that meet them where they are. 
Here are three such innovative 
approaches for connecting with 
top talent.
Don’t keep relying on the 
same old social media plat-
forms. The Society for Human 
Resource Management reports 
that 84% of organizations use 
social media for recruiting, and 
“FEELING PINNED DOWN?” read 
the message targeted at Pinter-
est employees. “This place driv-
ing you mad?” asked the clever 
riff aimed at Uber workers. If 
any story demonstrates how 
far employers will go in today’s 
fierce war for talent, the tale of 
Snapchat’s geofilter recruiting 
campaign is it.
Last fall Forbes reported that 
Snapchat had begun using geo-
filters (overlays that Snapchat 
users can put on top of images) 
to poach employees from 
other top start-ups. Geofilters 
become available when a user 
is in a specific location—think 
Athens, Greece, or Morristown, 
New Jersey. Or, as it turns out, 
even the vicinity of 1455 Market 
Street, the address of Uber’s 
San Francisco headquarters. 
Snapchat’s geofilters combined 
amusing visuals and messages 
with the web address of the 
company’s job page, all in the 
hope that a Twitter engineer 
and in our industry. And we’re 
evaluating various tools and 
tests to bring even more data 
into the hiring decision process. 
Can I imagine a future in which 
companies rely exclusively on 
machines and algorithms to 
rate résumés and interviews? 
Maybe, for some. But I don’t see 
us ever eliminating the human 
element at Goldman Sachs; 
it’s too deeply embedded in 
our culture, in the work we do, 
and in what we believe drives 
success.
I’m excited to see where 
this journey takes us. Our 2019 
campus class is shaping up to 
be the most diverse ever—and 
it’s composed entirely of people 
who were selected through rig-
orous, objective assessments. 
There’s no way we aren’t better 
off as a result.
Originally published in HarvardBusiness 
Review May–June 2019
HBR Reprint R1903B
Dane E. Holmes is the global head 
of human capital management at 
Goldman Sachs.
process is perfect. Indeed, 
what I love most about our new 
approach is that we’ve turned 
our recruiting department into 
a laboratory for continuous 
learning and refinement. With 
more than 50,000 candidate 
video recordings, we’re now 
sitting on a treasure trove of 
data that will help us conduct 
insightful analyses and answer 
questions necessary to run our 
business: Are we measuring 
the right competencies? Should 
some be weighted more heav-
ily than others? What about 
the candidates’ backgrounds? 
Which interviewers are most 
effective? Does a top-ranked 
student at a state school cre-
ate more value for us than an 
average student from the Ivy 
League? We already have indi-
cations that students recruited 
from the new schools in our 
pool perform just as well as 
students from our traditional 
ones—and in some cases are 
more likely to stay longer at 
the firm.
What’s next for our recruit-
ing efforts? We receive almost 
500,000 applications each year. 
From this pool we hire ap-
proximately 3%. We believe that 
many of the other 97% could 
be very successful at Goldman 
Sachs. As a result, picking the 
right 3% is less about just the in-
dividual and increasingly about 
matching the right person to 
the right role. That match may 
be made straight out of college 
or years later. We’re experi-
menting with résumé-reading 
algorithms that will help can-
didates identify the business 
departments best suited to their 
skills and interests. We’re look-
ing at how virtual reality might 
help us better educate students 
about working in our offices 
Recruiting Strategies for 
a Tight Talent Market
by Erica Dhawan 
FALL 2019 | HBR Special Issue 73
HBR.ORG
one of the most effective ways 
to connect with this age group. 
In a 2012 online survey of 2,000 
people born after 1981, 88% of 
people reported that humor is 
essential to their sense of self. 
Tanya Giles, former executive 
vice president for research at 
MTV Networks, told the New 
York Times, “One big takeaway 
is that unlike previous genera-
tions, humor, and not music, 
is their number one form of 
self-expression.”
The What’s the Matter with 
Owen? campaign premiered 
on the first episode of The Late 
Show with Stephen Colbert, the 
perfect outlet to reach a demo-
graphic that prefers comedians 
to sports stars. Since then, the 
campaign has been viewed 
more than 800,000 times on 
YouTube.
As these examples show, 
connecting to top talent today is 
about reimagining the possi-
bilities of leveraging all kinds of 
networks. It’s about connecting 
in the right places and with the 
right attitude. And while pick-
ing through the dense online 
tapestry may be daunting, 
remember: You already employ 
a staff of experts. Current 
employees can tell you which 
sites they use to connect with 
like-minded individuals and 
help you launch networks that 
are organized to meet your 
company’s specific needs.
Originally published on HBR.org 
April 7, 2016
HBR Reprint H02SXU
Erica Dhawan is one of the world’s lead-
ing authorities on 21st-century collabora-
tion, the author of Get Big Things Done: 
The Power of Connectional Intelligence 
(St. Martin’s Press, 2015), the host of the 
Masters of Leadership podcast, and the 
CEO of Cotential. Follow her on Twitter: 
@edhawan.
In addition, Genesys began 
actively networking to build a 
talent pool and even organized 
a two-hour event to introduce 
high school students to the 
company’s products. Genesys 
staff plan to remain connected 
with these students, who may 
later return as interns or new 
hires upon graduation.
These efforts have definitely 
made a difference: In 2014 the 
average time to hire was 50 
days—half the time of the previ-
ous year. Just one year later, 
Glassdoor named Genesys one 
of the Best Places to Work.
Looking for Millenni-
als? Address their specific 
concerns—and make it 
funny. Poor Owen. In GE’s 
recent recruitment advertising 
campaign, What’s the Matter 
with Owen?, the fictional star 
can’t find anyone to share his 
excitement about his new job: 
a developer for GE. Everyone 
he knows is stuck in the same 
ideological rut: GE is a manu-
facturer, they all think, not a 
place to change the world.
At a surprise party, his 
friends struggle to maintain 
their masks of encouragement. 
At a backyard gathering, Owen 
is upstaged by a friend who will 
be working for an “app where 
you put fruit hats on animals.” 
In his family’s living room, his 
proud parents give him his 
“grandpappy’s” giant hammer.
GE knew that it had an 
image problem, one that was 
especially problematic for Mil-
lennials, who value purpose 
over paycheck. The company 
needed to spread the message 
that, in fact, GE is involved in 
fascinating projects that will af-
fect the world in positive ways. 
And what GE and its ad agency, 
BBDO, knew is that humor is 
demonstrated its “culture and 
the type of company we want 
to be in 1, 5, and 10 years.” 
By distributing this message 
through the Quora community, 
Highfive was “able to attract 
the type of people we want, and 
do it in an original way.” Such 
creative solutions have paid 
off: In 2016 Fortune magazine 
named Highfive to its list of the 
10 Best Small Workplaces in 
Technology.
Generate and nurture your 
own talent channels. Genesys, 
a pioneer of customer experi-
ence and call center software, 
has offices across the globe, 
and it’s growing quickly, having 
acquired 10 companies since 
2012. Part of its success is that 
the company supports a collab-
orative work environment and 
boasts transparent operations 
from the top down. But a few 
years ago, delays in signing new 
hires were impairing its expan-
sion; in 2013 the average time to 
hire was 100 days.
Merijn te Booij, Genesys’s 
chief marketing officer, decided 
to stop waiting for the perfect 
candidate to appear through 
established channels. He 
partnered with HR to start an 
associate program that put 
new college and experienced 
professionals through an inten-
sive three-week training, later 
pairing them with a mentor for 
ongoing counsel. Since 2014 
Genesys has graduated nearly 
70 associates from the United 
States, Africa, South Korea, 
Malaysia, and South America.
82% of them use it primarily 
in the hunt for passive candi-
dates. If so many companies 
are using social media, it must 
be effective, right? Well, not 
necessarily. What this high 
percentage means is that on 
the most popular social media 
platforms—LinkedIn, Facebook, 
and Twitter—you’re already 
vying with your competition for 
the same pool of expertise.
So venture out. Connect 
with other online platforms 
where people gather for the 
pleasure of sharing knowledge. 
For developers, that may be 
Stack Overflow, a question-
and-answer site specifically for 
programmers. For the medi-
cal field, it may be Doximity, 
which 60% of U.S. physicians 
are members of. For Millennial 
women, it might be Levo or 
The Muse. For people in other 
professions, it may be Quora, 
a website that hosts ques-
tions and answers on subjects 
ranging from programming 
languages to fashion to the 
outbreak of the Zika virus.
What’s the trick? It’s pretty 
straightforward: Go on a plat-
form connected to the industry 
you’re recruiting for, and then 
look for people who are using it 
to have smart, relevant conver-
sations. If you are impressed by 
someone’s questions, answers, 
or other posts, you may just 
have identified a potentially 
valuable employee.
At least one company has 
worked Quora specifically 
into its recruitment strategy. 
Highfive, a Silicon Valley–based 
video and web conferencing 
supplier, uses Quora to connect 
“with like-minded individu-
als.” The company was already 
developing content, targeted 
specifically at recruits, that 
Connecting to top talent 
today is about connecting 
in the right places and 
with the right attitude.
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ers will play a crucial role as 
thought partners in conversa-
tions with hiring managers, 
even if that means breaking 
the traditional transactional 
recruiter relationship. At a 
recent conference, Nellie 
Peshkov, Netflix’s vice presi-
dent of talent acquisition and 
one of the leading thinkers 
in the field, explained, “Our 
value in talent acquisition is 
really about coaching, guiding, 
providing creative thinking and 
strategies for that hiring man-
ager.” Michael Orozco Jr., one of 
Netflix’s recruiters, added that 
while some recruiters ask their 
hiring manager, “What do you 
want?” Netflix recruiters ask 
questions such as “Why are you 
looking for them?” and “How 
will they make an impact?”
THE ERA OF the specialized Rolo-
dex as the main way to differen-
tiate recruiters is over. LinkedIn 
killed it. This is not to say that 
talent-acquisition profession-
als can no longer add value. 
On the contrary, technological 
change has made it possible for 
recruiters to make themselves 
more critical to organizations 
than ever before. Recruiters, 
however, must adapt and focus 
their value proposition on five 
main areas to remain relevant 
in the new digital era of talent 
acquisition. They can do this by 
following these steps:
Help Hiring Managers Define 
the Correct Search Strategy
Asking insightful questions is 
essential to defining the correct 
search strategy. Strong recruit-
How Recruiters 
Can Stay 
Relevant in the 
Age of LinkedIn
by Atta Tarki and Ken Kanara 
FALL 2019 | HBR Special Issue 75
HBR.ORG
improve their methods. With-
out establishing this critical 
step, it is difficult to determine 
what is working, and what isn’t. 
For instance, job knowledge 
tests may be predictive of job 
performance at Google, but 
have they been as successful at 
your organization?
Our own testing underscores 
this point, as we have found 
that methods that were highly 
effective two years ago no lon-
ger work. One simple example 
is that by using a candidate’s 
first name in the email subject 
line, we used to get up to twice 
as many candidates to engage 
in our searches. Now, perhaps 
because this tactic has been 
overused, we have abandoned 
this approach as it no longer in-
creases candidate engagement.
CEOs who position their tal-
ent acquisition teams to follow 
these five steps will gain a sig-
nificant advantage in attracting 
the right talent in the new era of 
talent acquisition. 
Originally published on HBR.org 
February 8, 2019
HBR Reprint H04SED
Atta Tarki is the founder and CEO of 
specialized executive search and project-
based staffing firm Ex-Consultants 
Agency. He is also the author of Evidence 
Based Recruiting: How Google and 
Netflix Leverage Talent Acquisition to 
Gain a Competitive Edge (Ex-Consultants 
Agency, forthcoming). Ken Kanara is the 
president of Ex-Consultants Agency. He 
has more than a decade of experience in 
consulting and executive search, with a 
focus on private equity and PE portfolio 
companies. 
Select the Best of the Best
The next step is to help hiring 
managers better understand 
how to predict job performance. 
Google’s recruiting team is 
perhaps the best in the world at 
this: They help hiring manag-
ers understand what categories 
of questions they should ask 
candidates and even provide 
hiring managers with sample 
questions they can ask. In his 
book Work Rules! Insights from 
Inside Google That Will Trans-
form How You Live and Lead 
(Twelve, 2015), Laszlo Bock, 
former senior vice president of 
people operations at Google, 
described how he helped re-
duce bias in Google’s interview 
process by having an indepen-
dent committee make hiring 
decisions and incorporating 
structured interview questions 
and job knowledge tests into 
their process.
Get Candidates Over the 
Finish Line
Strong recruiters will help hir-
ing managers get candidates 
over the finish line by helping 
their companies create a posi-
tive candidate experience as 
well as organizing and manag-
ing the interview and offer 
process. One candidate we 
spoke with who had recently 
declined an offer cited how 
she had originally been excited 
about the company’s pitch 
about being entrepreneurial 
and fast-moving, but started 
doubting if this was true when 
their interview process dragged 
on for three months.
Evaluate
Finally, recruiters should evalu-
ate their hiring practices on an 
ongoing basis and apply an it-
erative process to continuously 
most popular way of hiring 
candidates. That is, 42% of 
hires came from posting roles 
on job boards and company 
websites. Recruiter-sourced 
candidates represented only 
10% of the hires.
While job postings have 
some benefits, hoping that star 
performers will fall into your 
lap, especially during the low-
est period of unemployment in 
almost 50 years, is not advis-
able. Successful recruiters help 
organizations by building a 
repeatable and scalable for-
mula for finding and engaging 
star performers. Recruiters can 
do this by experimenting with 
and increasing the efficiency 
of other sourcing channels.
At our firm, we have found 
the following through trial and 
error of thousands of mes-
sages when actively sourcing 
candidates:
• For some roles, emails to 
candidates that do not include 
a job description are 27% more 
efficient than those that do. 
This could be because candi-
dates have more trust in emails 
without a link or attachment 
or because emails with job 
descriptions are longer.
• Personalized emails are 
about 75% more effective than 
generic ones.
• LinkedIn messages are 
about six times (!) more effec-
tive than emails for parts of the 
candidate pool.
Recruiters often receive fran-
tic calls from hiring managers 
looking to fill roles. Convincing 
them to take a step back can 
be difficult but valuable. For 
example, one of our clients 
recently asked us to urgently 
hire him a vice president of 
new retail to support the large 
number of new stores their 
company planned to open. 
“Find me someone who did 
this at Starbucks,” he told us. 
Because the coffee chain had 
also rapidly opened new stores, 
our client believed a candidate 
with experience there would 
have the right skill set to man-
age a large number of building 
contractors while recruiting 
and training staff for the 
new stores.
Instead of leaping off into 
a search for executives at 
Starbucks or similar chains, 
we asked him to describe the 
main challenges his company’s 
new stores typically face. The 
discussion helped our client 
realize that contrary to his origi-
nal belief, attracting sufficient 
foot traffic due to his com-
pany’s weak brand recognition 
was their primary challenge. 
He therefore concluded that a 
background at Starbucks was 
quite likely to be the absolute 
wrong profile he needed. A 
few minutes invested up front 
in such discussions will allow 
recruiters to focus their efforts 
from the beginning of a search, 
target more-ideal profiles, and 
land candidates faster.
Get the Best Candidates 
to Apply
A 2016 SilkRoad study of 
13 million applicants and 
300,000 hires at 1,200 com-
panies revealed that the “post 
and pray” strategy is still the 
Convincing hiring 
managers to take a step 
back can be difficult but 
valuable.
United Kingdom, and the United States—we then 
surveyed at least 800 business leaders (whose 
companies diff ered from those of the workers we 
surveyed). In total we gathered responses from 
11,000 workers and 6,500 business leaders.
What we learned was fascinating: The two 
groups perceived the future in signifi cantly diff er-
ent ways. Given the complexity of the changes that 
companies are confronting today and the speed 
with which they need to make decisions, this gap 
in perceptions has serious and far-reaching conse-
quences for managers and employees alike.
Predictably, business leaders feel anxious 
as they struggle to marshaland mobilize the 
workforce of tomorrow. In a climate of perpetual 
disruption, how can they fi nd and hire employees 
who have the skills their companies need? And 
what should they do with people whose skills 
have become obsolete? The CEO of one multi-
national company told us he was so tormented 
by that last question that he had to seek counsel 
from his priest. 
The workers, however, didn’t share that sense 
of anxiety. Instead, they focused more on the 
opportunities and benefi ts that the future holds 
for them, and they revealed themselves to be much 
more eager to embrace change and learn new 
skills than their employers gave them credit for. 
76 HBR Special Issue | FALL 2019 ILLUSTRATION BY JOANNA ŁAWNICZAK
MANY MANAGERS have little 
faith in their employees’ ability 
to survive the twists and turns 
of a rapidly evolving economy. 
“The majority of people in 
disappearing jobs do not realize 
what is coming,” the head of strategy at a top 
German bank recently told us. “My call center 
workers are neither able nor willing to change.” 
This kind of thinking is common, but it’s 
wrong, as we learned after surveying thousands 
of employees around the world. In 2018, in an 
attempt to understand the various forces shap-
ing the nature of work, Harvard Business School’s 
Project on Managing the Future of Work and the 
Boston Consulting Group’s Henderson Institute 
came together to conduct a survey spanning 11 
countries—Brazil, China, France, Germany, India, 
Indonesia, Japan, Spain, Sweden, the United King-
dom, and the United States—gathering responses 
from 1,000 workers in each. In it we focused solely 
on the people most vulnerable to changing dy-
namics: lower-income and middle-skills workers. 
The majority of them were earning less than the 
average household income in their countries, and 
all of them had no more than two years of post-
secondary education. In each of eight countries—
Brazil, China, France, Germany, India, Japan, the 
Your Workforce Is 
More Adaptable 
Than You Think
Employees are eager to embrace retraining—and companies need to 
seize this as a competitive opportunity. by Joseph B. Fuller, Manjari Raman, 
Judith K. Wallenstein, and Alice de Chalendar
Originally published in 
May–June 2019
RETAINING THE BEST
78 HBR Special Issue | FALL 2019
RETAINING THE BEST YOUR WORKFORCE IS MORE ADAPTABLE THAN YOU THINK
The Nature of the Gap
When executives today consider the forces that 
are changing how work is done, they tend to think 
mostly about disruptive technologies. But that’s 
too narrow a focus. A remarkably broad set of 
forces is transforming the nature of work, and 
companies need to take them all into account. 
In our research we’ve identified 17 forces of dis-
ruption, which we group into six basic categories. 
(See the sidebar “The Forces Shaping the Future 
of Work.”) Our surveys explored the attitudes that 
business leaders and workers had toward each of 
them. In their responses, we were able to discern 
three notable differences in the ways that the two 
groups think about the future of work.
The first is that workers seem to recognize more 
clearly than leaders do that their organizations are 
contending with multiple forces of disruption, each 
of which will affect how companies work differently. 
When asked to rate the impact that each of the 
17 forces would have on their work lives, using a 
100-point scale, the employees rated the force with 
the strongest impact 15 points higher than the force 
with the weakest impact. In comparison, there was 
only a nine-point spread between the forces rated 
the strongest and the weakest by managers. 
In fact, the leaders seemed unable or unwilling 
to think in differentiated ways about the forces’ 
potential for disruption. When asked about each 
force, roughly a third of them described it as 
having a significant impact on their organization 
today; close to half projected that it would have a 
significant impact in the future; and about a fifth 
claimed it would have no impact at all. That’s a 
troubling level of uniformity, and it suggests that 
most leaders haven’t yet figured out which forces 
of change they should make a priority.
Interestingly, workers appeared to be more 
aware of the opportunities and challenges of 
several of the forces. Notably, workers focused 
on the growing importance of the gig economy, 
and they ranked “freelancing and labor-sharing 
platforms” as the third most significant of all 17 
forces. Business leaders, however, ranked that 
force as the least significant.
The second difference that emerged from our 
survey was this: Workers seem to be more 
adaptive and optimistic about the future than 
their leaders recognize. 
The conventional wisdom, of course, is that 
workers fear that technology will make their 
jobs obsolete. But our survey revealed that to be 
a misconception. A majority of the workers felt 
that advances such as automation and artificial 
intelligence would have a positive impact on their 
future. In fact, they felt that way about two-thirds 
of the forces. What concerned them most were the 
forces that might allow other workers—temporary, 
freelance, outsourced—to take their jobs. 
When asked why they had a positive outlook, 
workers most commonly cited two reasons: the 
prospect of better wages and the prospect of 
more interesting and meaningful jobs. Both 
auto mation and technology, they felt, heralded 
opportunity on those fronts—by contributing to 
the emergence of more-flexible and self-directed 
forms of work, by creating alternative ways to 
earn income, and by making it possible to avoid 
tasks that were “dirty, dangerous, or dull.” 
In every country workers described themselves 
as more willing to prepare for the workplace of 
the future than managers believed them to be 
(in Japan, though, the percentages were nearly 
equal). Yet when asked what was holding workers 
back, managers chose answers that blamed 
employees, rather than themselves. Their most 
common response was that workers feared 
significant change. The idea that workers might 
lack the support they needed from employers was 
only their fifth-most-popular response.
That brings us to our third finding: Workers are 
seeking more support and guidance to prepare them-
selves for future employment than management 
is providing.
In every country except France and Japan, 
significant majorities of workers reported that 
they—and not their government or their 
employer—were responsible for equipping 
themselves to meet the needs of a rapidly 
evolving workplace. That held true across age 
groups and for both men and women. But 
workers also felt that they had serious obstacles 
to overcome: a lack of knowledge about their 
options; a lack of time to prepare for the future; 
high training costs; the impact that taking time 
off for training would have on wages; and, in 
particular, insufficient support from their 
employers. All are barriers that management 
can and should help workers get past.
What Employers Can Do to Help
The gap in perspectives is a problem because it 
leads managers to underestimate employees’ 
A majority of 
workers felt that 
advances such as 
automation and 
artificial intelligence 
would have a 
positive impact 
on their future. 
FALL 2019 | HBR Special Issue 79
HBR.ORG
Idea 
in Brief
THE PROBLEM
As they try to build a workforce 
in a climate of perpetual disrup-
tion, business leaders worry that 
their employees can’t—or just 
won’t—adapt to the big changes 
that lie ahead. How can compa-
nies find people with the skills 
they will need?
WHAT THE 
RESEARCH SHOWS
Harvard Business School and 
the BCG Henderson Institute 
surveyed thousands of business 
leaders and workers around the 
world and discovered an impor-
tant gap in perceptions: Workers 
are far more willing and able 
to embrace change than their 
employers assume.
THE SOLUTION
This gap represents an oppor-
tunity. Companies need to start 
thinking of theiremployees as 
a reserve of talent and energy 
that can be tapped by providing 
smart on-the-job skills training 
and career development.
ambitions and underinvest in their skills. But it 
also shows that there’s a vast reserve of talent 
and energy companies can tap into to ready 
themselves for the future: their workers. 
The challenge is figuring out how best to do that. 
We’ve identified five important ways to get started.
1. Don’t just set up training programs—
create a learning culture. 
If companies today engage in training, they tend to 
do it at specific times (when onboarding new hires, 
for example), to prepare workers for particular 
jobs (like selling and servicing certain products), 
or when adopting new tech nologies. That worked 
well in an era when the pace of technological 
change was relatively slow. But advances are hap-
pening so quickly and with such complexity today 
that companies need to shift to a continuous-
learning model—one that repeatedly enhances 
employees’ skills and makes formal training 
broadly available. Firms also need to expand their 
portfolio of tactics beyond online and off-line 
courses to include learning on the job through 
project staffing and team rotations. Such an ap-
proach can help companies rethink traditional 
entry-level barriers (among them, edu cational 
credentials) and draw from a wider talent pool. 
Consider what happens at Expeditors, a For-
tune 500 com pa ny that provides global logistics 
and freight-forwarding services in more than 100 
countries. In vetting job candidates, Expeditors has 
long relied on a “hire for attitude, train for skill” 
approach. Educational degrees are appreciated 
but not seen as critical for success in most roles. 
Instead, for all positions, from the lowest level right 
up to the C-suite, the company focuses on tem-
perament and cultural fit. Once on staff, employees 
join an intensive program in which every member 
of the organization, no matter how junior or senior, 
undertakes 52 hours of incremental learning a year. 
This practice supports the company’s promote-
from-within culture. Expeditors’ efforts seem to be 
working: Turnover is low (which means substantial 
savings in hiring, training, and onboarding costs); 
retention is high (a third of the company’s 17,000 
employees have worked at the company for 10 
years or more); most senior leaders in the company 
have risen through the ranks; and several current 
vice presidents and senior vice presidents, along 
with the current and former CEOs, got their jobs 
despite having no college degree. 
2. Engage employees in the transition 
instead of herding them through it. 
As companies transform themselves, they often 
find it a challenge to attract and retain the type of 
talent they need. To succeed, they have to offer 
employees pathways to professional and personal 
improvement—and must engage them in the 
process of change, rather than merely inform them 
that change is coming.
That’s what ING Netherlands did in 2014, when 
it decided to reinvent itself. The bank’s goal was 
ambitious: to turn itself into an agile institution 
almost overnight. The company’s current CEO, 
Vincent van den Boogert, recalls that the com-
pany’s leaders began by explaining the why and 
the what of the transformation to all employees. 
Mobile and digital technologies were dramatically 
altering the market, they told everybody, and if 
ING wanted to meet the expectations of custom-
ers, improve operations, and deploy new techno-
logical capabilities, it would have to become faster, 
leaner, and more flexible. To do that, they said, the 
company planned to make investments that would 
reduce costs and improve service. But it would 
also eliminate a significant number of jobs—at 
least a quarter of the total workforce. 
Then came the how. Rather than letting the ax 
fall on select employees—a process that creates 
psychological trauma throughout a company—ING 
decided that almost everybody at the company, 
regardless of tenure or seniority, would be required 
to resign. After that, anybody who felt his or her 
attitude, capabilities, and skills would be a good fit 
at the “new” bank could apply to be rehired. That 
included Van den Boogert himself. Employees who 
did not get rehired would be supported by a pro-
gram that would help them find jobs out side ING.
None of this made the company’s transforma-
tion easy, of course. But according to Van den 
Boogert, the inclusive approach adopted by 
management significantly minimized the pain 
that employees felt during the transition, and it 
immediately set the new, smaller bank on the 
path to success. The employees who rejoined 
ING actively embraced its new mission, felt less 
survivor’s remorse, and devoted themselves with 
excitement to the job of transformation. “When 
you talk about the why, what, and how at the same 
time,” Van den Boogert told us, “people are going 
to challenge the why to prevent the how. But in 
this case, everyone had already been inspired 
by the why and what.”
80 HBR Special Issue | FALL 2019
RETAINING THE BEST YOUR WORKFORCE IS MORE ADAPTABLE THAN YOU THINK
3. Look beyond the “spot market” 
for talent. 
Most successful companies have adopted increas-
ingly aggressive strategies for finding critical 
high-skilled talent. Now they must expand that 
approach to include a wider range of employees. 
AT&T recognized that need in 2013, while develop-
ing its Workforce 2020 strategy, which focused on 
how the company would make the transition from 
a hardware-centric to a software-centric network. 
The company had undergone a major trans-
formation once before, in 1917, when it launched 
plans to use mech an ical switchboards rather than 
human operators. But it carried that transforma-
tion out over the course of five decades! The 
Workforce 2020 transformation was much more 
complex and had to happen on a much faster 
timeline. 
To get started, AT&T undertook a systematic 
audit of its quarter of a million employees to 
catalog their current skills and compare those 
with the skills it expected to need during and after 
its revamp. Ultimately, the company identified 
100,000 employees whose jobs were likely to 
disappear, and several areas in which it would 
face skills and competency shortages. Armed with 
those insights, the company launched an ambi-
tious, multiyear $1 billion initiative to develop an 
internal talent pipeline instead of simply playing 
the “spot market” for talent. In short, to meet its 
evolving needs, AT&T decided to make retrain-
ing available to its existing workforce. Since then, 
its employees have taken nearly 3 million online 
courses designed to help them acquire skills for 
new jobs in fields such as application develop-
ment and cloud computing. 
Already, this effort has yielded some unex-
pected benefits. The company now hires far fewer 
contractors to meet its needs for technical skills, 
for example. “We’re shifting to employees,” one 
of the company’s top executives told CNBC this 
past March, “because we’re starting to see the tal-
ent inside.”
4. Collaborate to deepen the talent pool. 
In a fast-evolving environment, competing for 
talent doesn’t work. It simply leads to a tragedy 
of the commons. Individual companies try to 
grab the biggest share of the skilled labor available, 
and these self-interested attempts just end up 
creating a shortage for all. 
THE FORCES SHAPING THE 
FUTURE OF WORK
ACCELERATING 
TECHNOLOGICAL CHANGE
• New technologies that replace 
human labor, threatening employ-
ment (such as driverless trucks)
• New technologies that augment 
or supplement human labor (for 
example, robots in health care)
• Sudden technology-based shifts 
in customer needs that result in 
new business models, new ways 
of working, or faster product 
innovation 
• Technology-enabled opportunities 
to monetize free services (such as 
Amazon web services) or under-
utilized assets (such as personal 
consumption data)
GROWING DEMANDFOR SKILLS
• General increase in the skills, 
technical knowledge, and formal 
education required to perform 
work
• Growing shortage of workers with 
the skills for rapidly evolving jobs
CHANGING EMPLOYEE 
EXPECTATIONS
• Increased popularity of flexible, 
self-directed forms of work that 
allow better work-life balance
• More widespread desire for work 
with a purpose and opportunities 
to influence the way it is deliv-
ered (for example, greater team 
autonomy) 
SHIFTING LABOR 
DEMOGRAPHICS
• Need to increase workforce 
participation of under represented 
populations (such as elderly 
workers, women, immigrants, and 
rural workers)
TRANSITIONING 
WORK MODELS
• Rise of remote work
• Growth of contingent forms of 
work (such as on-call workers, 
temp workers, and contractors)
• Freelancing and labor-sharing 
platforms that provide access to 
talent
• Delivery of work through complex 
partner ecosystems (involving 
multiple industries, geographies, 
and organizations of different 
sizes), rather than within a single 
organization
EVOLVING BUSINESS 
ENVIRONMENT
• New regulation aimed at control-
ling technology use (for example, 
“robot taxes”)
• Regulatory changes that affect 
wage levels, either directly (such 
as minimum wages or Social Se-
curity entitlements) or indirectly 
(such as more public income 
assistance or universal basic 
income)
• Regulatory shifts affecting cross-
border flow of goods, services, 
and capital
• Greater economic and political 
volatility as members of society 
feel left behind
FALL 2019 | HBR Special Issue 81
HBR.ORG
To avoid that problem, companies will have to 
fundamentally change their outlook and work to-
gether to ensure that the talent pool is constantly 
refreshed and updated. That will mean teaming 
up with other companies in the same industry or 
region to identify relevant skills, invest in develop-
ing curricula, and provide on-the-job training. 
It will also require forging new relationships 
for developing talent by, for instance, engaging 
with entrepreneurs and technology developers, 
partner ing with educational institutions, and col-
laborating with policy makers. 
U.S. utilities companies have already begun do-
ing this. In 2006 they joined forces to establish the 
Center for Energy Workforce Development. The 
mission of the center, which has no physical office 
and is staffed primarily by former employees from 
member companies, is to figure out what jobs and 
skills the industry will need most as its older work-
ers retire—and then how best to create a pipeline to 
meet those needs. “We’re used to working together 
in this industry,” Ann Randazzo, the center’s 
executive director, told us. “When there’s a storm, 
everybody gets in their trucks. Even if we compete 
in certain areas, including for workers, we’ve all got 
to work together to build this pipeline, or there just 
aren’t going to be enough people.”
The center quickly determined that three of 
the industry’s most critical middle-skills jobs— 
linemen, field operators, and energy technicians—
would be hit hard by the retirement of workers in 
the near future. Together, those three jobs make 
up almost 40% of a typical utility’s workforce. To 
make sure they wouldn’t go unfilled, CEWD imple-
mented a two-pronged strategy. It created detailed 
tool kits, curricula, and training materials for all 
three jobs, which it made available free to utility 
companies; and it launched a grassroots move-
ment to reach out to next-generation workers and 
promote careers in the industry. 
CEWD believes in connecting with promising 
talent early—very early. To that end, it has been 
working with hundreds of elementary, middle, 
and high schools to create materials and programs 
that introduce students to the benefits of work-
ing in the industry. These include a sense of larger 
purpose (delivering critical services to customers); 
stability (no offshoring of jobs, little technological 
displacement); the use of automation and technol-
ogy to make jobs less physically taxing and more 
intellectually engaging; and, last but not least, 
surprisingly high wages. Describing the program 
to us, Randazzo said, “You’re growing a workforce. 
We had to start from scratch to get students in 
the lower grades to understand what they need 
to do and to really be able to grow that all the way 
through high school to community colleges and 
universities. And it’s not a one-and-done. We have 
to continually nurture it.”
5. Find ways to manage chronic 
uncertainty. 
In today’s world, managers know that if they 
don’t swiftly identify and respond to shifts, their 
companies will be left behind. So how can firms 
best prepare? 
The office-furniture manufacturer Steelcase 
has come up with some intriguing ideas. One is 
its Strategic Workforce Architecture and Trans-
formation (SWAT) team, which tracks emerging 
trends and conducts real-time experiments in how 
to respond to them. The team has launched an 
internal platform called Loop, for example, where 
employees can volunteer to work on projects 
outside their own functions. This benefits both the 
company and its employees: As new needs arise, 
the company can quickly locate workers within 
its ranks who have the motivation and skills to 
meet them, and workers can gain experience and 
develop new capabilities in ways that their current 
jobs simply don’t allow. 
Employees at Steelcase have embraced Loop, 
and its success illustrates an idea that came through 
very clearly in our survey results. As Jill Dark, the 
director of the SWAT team, put it to us, “If you give 
people the opportunity to learn something new 
or to show their craft, they will give you their best 
work. The magic is in providing the opportunity.” 
That’s a lesson that all managers should 
heed. HBR Reprint R1903H
Joseph B. Fuller is a professor of management 
practice and a cochair of the Project on Managing the 
Future of Work at Harvard Business School. Judith K. 
Wallenstein is a senior partner and managing director 
at Boston Consulting Group, a BCG Fellow, and the 
director of the BCG Henderson Institute in Europe. 
Manjari Raman is a program director and senior 
researcher for Harvard Business School’s Project on 
U.S. Competitiveness and the Project on Managing the 
Future of Work. Alice de Chalendar is a consultant at 
BCG and a researcher at the BCG Henderson Institute.
Firms need to 
expand their 
portfolio of tactics 
beyond online and 
off-line courses to 
include learning 
on the job.
FALL 2019 | HBR Special Issue 83
HR—who was at the meeting—sensed his surprise. 
Though the offer may have come earlier than 
expected, she explained, his current boss had been 
consulted and supported the move. It was a golden 
opportunity for David, and everyone was rooting 
for him to succeed. He would have time to make 
all the necessary arrangements, the CHRO added, 
and the company would gladly help his family 
move to the other side of the country, where the 
business he would run was based. He would start 
in four weeks.
After asking a few questions and learning about 
the generous raise that would come with the 
ILLUSTRATION BY JOANNA ŁAWNICZAK
A S THE HEAD of a large manufac-
turing plant at a multinational 
conglomerate, an executive I’ll 
call David had proved himself 
a competent, trustworthy man-
ager. So when the presidency 
of one of the company’s key businesses unexpect-
edly became vacant, the CEO sat David down to 
share the good news that he had been chosen for 
the role. He had earned it.
Sudden career announcements like this are ac-
tually pretty common. Even so, David was caught 
off guard and didn’t know what to say. The head of 
Talent 
Management 
and the 
Dual-Career 
Couple
Rigid tours of duty are the wrong approach to development. 
by Jennifer Petriglieri
RETAINING THE BEST
Originally published in 
May–June 2018
84 HBR Special Issue | FALL 2019
RETAINING THE BEST TALENT MANAGEMENT AND THE DUAL-CAREERCOUPLE
promotion, David thanked the CEO and the CHRO 
warmly and promised to discuss the opportunity 
with his wife that evening. “Of course,” they 
replied, smiling.
They were shocked when David turned down 
the offer the next day. He was committed to the 
company and to his career, he said, but he was also 
committed to his wife’s career. She had a challeng-
ing final year to complete in her surgery residency 
program, and a move now would hurt her. David 
suggested various options—taking on the role at 
a later date, commuting for a period, or working 
remotely. The CEO rejected them all. “Leadership 
is about showing up,” he snapped.
A joyful occasion had turned sour in less than 
24 hours. The CEO was angry. The company had 
invested heavily in David. Where was his dedica-
tion when it counted, and how could he expect 
to advance if he was not willing to move for a 
leadership role? The CHRO was equally confused 
and upset by David’s response. After all, she had 
introduced work-family policies and generous mo-
bility allowances to support employees like him. 
David felt cornered. He had been presented with 
an untimely, rigid option, and now he was being 
punished for daring to try to negotiate it.
The company soon found another candidate 
for the job. David continued to perform well in 
his role, but things had changed. He felt that he 
was no longer on the top team’s talent radar. Nine 
months later, when his wife, Helen, completed her 
residency and was again mobile, she and David 
put out feelers for career opportunities. David 
was immediately headhunted by a rival com-
pany to lead its largest business, in a city where 
Helen found a position at a prestigious hospital. 
David’s career was back on track, and his wife’s 
was launched. And David’s old employer had lost 
a talented leader—after spotting him, grooming 
him, and offering him a plum role.
I learned about David from the CHRO, who 
told me that the company still had not figured 
out how best to manage the growing number of 
its employees who want to advance but also care 
deeply about their partners’ careers. I’ve seen this 
again and again in my work over the past several 
years. Otilia Obodaru, of Rice University, and I 
have studied more than 100 dual-career couples 
across generations and organizational settings 
(interviewing both members of each couple), and 
I have conducted in-depth interviews with the 
heads of people strategy at 32 large companies in 
tech, health care, professional services, and other 
industries. I also work closely with the heads of 
talent and learning at companies that send execu-
tives to the management program I codirect at 
INSEAD. Most talent VPs, I’ve found, are keenly 
aware of the rise of dual-career couples. Today, 
in almost half the two-parent households in the 
United States (compared with 31% in 1970), both 
parents work full-time. Still, companies struggle to 
anticipate and mitigate the effects on their talent 
pipelines. People in David’s predicament resign 
after their employers have invested in them, and 
those stories spread like wildfire in organizations, 
prompting other dual-career high potentials to 
look for the nearest exit.
The crux of the problem is that companies 
tend to have fixed paths to leadership roles, with 
set tours of duty and long-held ideas about what 
ambition looks like. That creates rigid barriers for 
employees—and recruitment and retention chal-
lenges for their employers, many of whom are fail-
ing to consider the whole person when mapping 
out high potentials’ career trajectories. To reap the 
benefits of their investments in human capital, 
organizations must adopt new strategies for man-
aging and developing talent. I’ll describe them, 
but first let’s take a closer look at why traditional 
approaches often fail.
The Trouble with the Usual 
Talent Strategies
Although most companies deny having traditional 
career ladders, executives in midsize and large 
organizations are widely expected to cycle through 
a variety of divisions and functions en route to the 
executive suite. This talent-development model 
usually involves multiple relocations. It originated 
in the early 1980s, before technology had opened 
the door to efficient, productive virtual work. 
For the most part, talent was “unbounded” (my 
term). That is, spouses didn’t have competing 
careers, so they managed home and family life, 
freeing up executives to meet their companies’ 
demands.
Times have changed, of course, but most tal-
ent management programs are still designed as 
if every couple had a dedicated homemaker and 
the inter net didn’t exist. For executives whose 
partners have full careers, such programs create 
two major challenges (and, my research suggests, 
two top reasons to resign). They are:
Companies tend to 
have fixed paths 
to leadership roles, 
with set tours of 
duty and long-held 
ideas about what 
ambition looks like.
FALL 2019 | HBR Special Issue 85
HBR.ORG
Idea 
in Brief
THE PROBLEM
High potentials are increasingly 
committed to their partners’ 
careers as well as their own, but 
most companies haven’t figured 
out how to accommodate that 
commitment. They invest heavily 
in grooming star performers for 
leadership roles, only to have 
them resign when confronted 
with flexibility and mobility 
challenges.
That’s wreaking havoc on 
recruitment and retention.
THE SOURCE
Because “future leaders” are 
usually expected to advance in 
a certain way—often through set 
tours of duty around the globe—
it can be difficult for members 
of dual-career couples to move 
ahead at work.
THE SOLUTION
Organizations can remove barri-
ers to advancement by allowing 
people to develop in more-
creative ways—through brief “job 
swaps,” for example, or “com-
muter” roles. But often a culture 
change is needed. Instead of 
stigmatizing flexibility, compa-
nies must learn to embrace it.
The mobility challenge. Members of dual- 
career couples understand that they’ll need to 
make multiple moves across functions and geog-
raphies if they want to ascend to senior roles—and 
they’re not averse to that. But having to drop 
everything and move at a moment’s notice forces 
them to choose which partner’s career will lead 
and which will follow. These days, fewer couples 
are willing to make that trade-off.
Take Melissa and Craig, both of whom were 
managers in their companies’ “future leader” pro-
grams. They had long harbored dreams of working 
abroad, but when Craig was offered a “now-or-
never golden opportunity” in London, he turned 
it down. “Melissa could probably have found a job 
in London, but not at the same level and on the 
same track,” he told me. “Equality is important to 
us, and we know that senior careers are uncertain. 
So we want to hedge against risk by balancing our 
careers. We need to move in a more planned way.”
Eventually, the two did make an international 
move. First they agreed on a destination—Dubai—
and then they launched parallel job searches. 
Melissa’s interest in moving to the Middle East 
landed her an in ternal transfer and a boost in 
responsibilities. Craig’s company was less keen 
on a transfer, but he found an exciting new role 
with a competitor.
Craig’s company lost a talented manager to a 
rival not because he wasn’t mobile but because it 
couldn’t match mobility options to his needs. Even 
if he had accepted the London job, his employer 
might have paid a price in the long run. Expatriate 
assignments and geographic relocations are often 
cut short when an executive’s partner struggles 
to adapt to a new community, for example, or 
can’t find a suitable career opportunity. Because 
Craig secured a good job in Dubai, Melissa’s expat 
assignment was more likely than many others to 
succeed.
The mobility challenge is exacerbated when 
organizations expect several moves in a short 
time frame, which is not unusual. At one global 
chemical company, for example, a new manage-
ment acceleration program moves peoplethrough 
three functions—and to three locations around 
the world—within a year and a half. “You move 
every six months,” the head of talent explained. 
This rounds out participants’ experience and 
knowledge in an efficient way. But, she added, “it 
certainly doesn’t work if you’re in a dual-career 
couple or for anyone who doesn’t want to drag 
their family around the world….So it stops a lot of 
great talent from even applying.”
Even when managers are not enrolled in formal 
rotation programs, many companies expect their 
best people to spend no more than three years in 
any role before moving to a new challenge. Those 
who don’t prog ress at that pace will look stagnant 
and perhaps be shown the door. “I’m dealing with 
a very talented woman who is going to lose her 
job,” the vice president of HR at a global logistics 
firm lamented. “She’s at the end of a three-year 
role, and she cannot relocate because of her hus-
band’s career. Rather than being flexible and say-
ing, ‘You can still live in Charlotte and commute to 
Atlanta three days a week,’ her manager is saying, 
‘No, it’s all or nothing. We’ll just have to let her go.’ 
It’s frustrating. Retaining senior female talent is 
a key priority for us, but the business is stuck in 
this rigid way of operating.”
I heard stories like this from about 40% of my 
research sample. It sounds crazy to set an arbitrary 
three-year limit on someone who is doing excel-
lent work. But most companies assess executives 
on potential as well as performance—and people 
who don’t want to move are dinged on poten-
tial, because they’re perceived as lacking ambi-
tion. Thwarted advancement is the most likely 
outcome, particularly for junior and midlevel 
managers. But at senior levels, where fewer lateral 
moves are available, there’s a great deal of pressure 
to “move up or out.”
The flexibility challenge. Every family has 
tasks that must get done—buying groceries, 
making meals, taking the car in for maintenance 
and repairs, driving children to and from school 
and activities, and so on. In traditional couples, 
the noncareer partner assumes the lion’s share 
of these responsibilities. For dual-career couples 
(even those who can afford to hire help), managing 
all this on top of work is a constant juggling act. As 
I studied these couples, it was clear that they do 
not want to work less, but they do need to work 
smarter and more flexibly.
Most leadership roles and paths, however, lack 
flexibility—and people who seek it are penal-
ized. This can lead to what one executive, Emily, 
called the “‘Whose job is more important today?’ 
roulette.” She and her partner, Jamal, had a finely 
tuned system: Emily dropped the kids at school in 
the morning and worked late in the evening, while 
Jamal did the opposite. However, when they hit 
a bump—sick kids, home repairs, elderly parents 
86 HBR Special Issue | FALL 2019
RETAINING THE BEST TALENT MANAGEMENT AND THE DUAL-CAREER COUPLE
place for other people in their lives....This affects 
how they want to work and prog ress. If we cannot 
change to cater to them, we will lose more and 
more talent.”
That generational shift is the result of changing 
marriage patterns that have profound implications 
for organizations. Over the past three decades, 
assortative mating—the tendency of people with 
similar outlooks and levels of education and ambi-
tion to marry each other—has risen by almost 25%. 
Nowadays, when an organization hires a manager 
in his or her thirties, that person’s partner is also 
likely to be an ambitious professional with a fast-
paced career. Paradoxically, a trend that should 
expand the talent pool for companies shrinks it 
instead, because of their outdated ways of devel-
oping people.
A New Talent Strategy
Designing effective leadership-development paths 
for members of dual-career couples requires two 
changes: a revised notion of what is needed to 
achieve growth and advancement, and a shift in 
the organizational culture to embrace flexibility in 
the talent development process.
Recognize that what matters more than 
where. Organizations must stop worrying so 
much about where aspiring leaders serve their 
time and instead focus on the skills and networks 
to be acquired. The talent management director of 
a global engineering firm described her company’s 
approach like this: “We have a list of experiences 
that future leaders need to have, but they are 
location-agnostic. For example, managing a busi-
ness in crisis or doing a turnaround—sometimes 
you don’t have to move at all to get these experi-
ences.” That’s a departure from the days when the 
company’s CEOs believed that one had to work in 
set locations to move up. Shifting the focus from 
“where” to “what” opens a range of creative solu-
tions, such as brief job swaps, short-term assign-
ments in various organizations or units (some-
times called secondments), and commuter roles.
Take Indira, an executive at a large pharmaceu-
ticals company who needed to build experience 
and knowledge of the Chinese market. To accom-
modate her dual-career situation, her company 
facilitated a six-week job swap with a peer in 
China, followed by a six-month strategic proj ect 
for the pair to work on. “Because it was a job swap, 
we felt a mutual responsibility to help each other,” 
who needed help—the system broke down and 
frantic negotiations began. Even when the system 
worked well, they found themselves being pun-
ished. Jamal, a management consultant, described 
being passed over for a promotion: “I brought 
more business to my firm than any other senior 
manager last year, but I left work at 5:30 PM every 
day. That was noticed. It’s not that I wasn’t work-
ing. I always put in an extra two or three hours 
after the kids went to bed. But I was told that my 
lack of presence signaled a lack of commitment 
to the firm.”
The expectation that rising stars should always 
be in the office made more sense when most 
business was local or regional and much of it had 
to be done in person. But now business is global, 
runs 24/7, and in many cases must be conducted 
virtually—and yet physical absence is still stigma-
tized. The head of learning and development at 
an engineering firm told me, “We’re one of those 
companies that has had a flexible working policy 
for a long time, but due to stigma we have not al-
lowed or encouraged people to take full advantage 
of that, and those who do have been sidelined in 
their careers.”
The irony is that research has shown the ben-
efits of flexible working—for instance, improve-
ments in efficiency and knowledge sharing. And 
in my interviews I’ve found that an organization’s 
commitment to cultivating and valuing flexible 
work is a key draw for members of dual-career cou-
ples. HR teams are well aware of these advantages. 
That’s why they put flexible policies in place.
If companies know what works in theory, why 
do they keep reverting to their old ways of manag-
ing and grooming talent? A big reason is inertia: 
It’s how they’ve done it for a long time, and they’re 
more likely to make incremental changes than 
overhauls. There’s also a dues-paying element, 
I’ve learned. People at the top tend to think, “Well, 
if I did it, so should the next generation.” It can be 
hard for them to identify with dual-career con-
straints if they came of age in a different time and 
never faced those constraints themselves. Because 
the current crop of high potentials aren’t willing to 
sacrifice their partners’ needs, a bit of a stalemate 
results—and mobility and flexibility challenges go 
largely unaddressed.
The head of learning and development at a large 
recruitment company put it this way: “Our Mil-
lennials are as ambitious and committed to their 
careers as other generations, but they also hold a 
FALL 2019 | HBR Special Issue 87
HBR.ORG
Indira told me. “We acted as each other’s coaches, 
extensively briefed each other before the swap, 
spoke almost every day during it, andworked 
closely together on the subsequent proj ect.” This 
model of having a peer-coach coupled with a burst 
of intensive experience acted as a “development 
accelerator,” she said. “I absorbed so much in 
that process.”
For instance, Indira was able to quickly build 
(and then maintain) a strong network in China. Her 
Chinese peer made great introductions, vouched 
for her, and asked people to “look after her” on the 
ground. (She did the same for him in the United 
States.) Acutely aware that she would be there for 
only six weeks, she didn’t want to waste a second, 
so she made an enormous effort, working evenings 
and weekends. In that time Indira acquired impor-
tant knowledge of the local market, the cultural 
aspects of doing business in China, and the varia-
tions in company culture between the two coun-
tries. And she gained valuable perspective, having 
never before worked outside the United States. As 
she put it, she saw that there was “more than one 
way to skin a cat.” She said she became better at 
problem solving and dealing with uncertainty.
Indira’s experience is common. Job swaps and 
shorter-term assignments facilitate rapid devel-
opment of the networks, skills, and perspective 
required to pro gress—which means they can 
circumvent, or at least minimize, the mobility 
challenge.
When more time—six months to two years— 
is needed for development, some companies are 
experimenting with partially remote leadership 
roles to accommodate members of dual-career 
couples. Managers work three or four days a week 
at the assignment location and the remainder of 
the week at home. Historically, this sort of arrange-
ment has been stigmatized, as the head of HR at 
a global mining company explained: “Business 
leaders believed it signaled a lack of commitment 
and that people used it to simply work less.” But 
companies, including his own, are changing their 
position. “More and more people in the talent pool 
are asking for it, and we have the technology to 
make it work, so we’re a lot more open—especially 
when it’s likely that someone will return to their 
home location at the end of their assignment.” 
This view is supported by a growing body of 
research showing that people who telecommute 
don’t work less than their colleagues at the office. 
In fact, they often put in more hours and are more 
productive in the hours they work.
Though networks, skills, and experiences can 
be acquired through job swaps, short-term as-
signments, and remote-leadership arrangements, 
full-time relocation is sometimes necessary to 
move one’s career forward. Members of dual-
career couples know that, yet they often feel let 
down by organizations that offer what one execu-
tive described as “a wealth of resources but little 
real support.” She explained that the resources 
made available to mobile talent are usually 
tailored to “trailing” homemakers or secondary- 
career partners, not to full-career partners. They 
typically include cultural adaptation courses, 
introductions to homemaker networks, and 
information about various social activities. When 
career help is offered, it is geared toward part-
time secretarial or teaching posts, for example, 
or volunteering. Thus, even when resources are 
abundant, they are often not appropriate for 
dual-career couples.
Some companies are tackling this shortcoming 
by using resources such as the International Dual 
Career Network as two-way headhunters. The 
mobile employee’s partner can register to receive 
access to workshops, placement support, and 
other job seekers’ services. And without paying 
a headhunter’s fee, the mobile employee’s 
organization can fill other vacant positions with 
qualified people in the network, who are quite 
clear about their location requirements. As one 
IDCN member told me, “We’ve filled some of our 
key senior positions through the network. This 
When executives 
see that people with 
flexible schedules are 
still working hard, 
they adjust their own 
ways of working—and 
change the culture.
88 HBR Special Issue | FALL 2019
RETAINING THE BEST TALENT MANAGEMENT AND THE DUAL-CAREER COUPLE
When executives see that Millennials (and others) 
with flexible schedules are still working hard and 
producing results, they revise their assumptions 
and begin to adjust their own ways of working. 
That has ripple effects. Even if the boss makes 
only small changes, the “signaling” impact is 
large—it gives others tacit permission to work 
more flexibly.
One HR professional in a manufacturing com-
pany pointed out, “Now we have leaders saying, 
‘Hey, listen, I’ve got to take off and run to a ball 
game,’ or ‘We’re going out for dinner.’ Or whatever 
it may be. That helps set the tone.” It’s especially 
powerful when senior men behave this way. 
That challenges the gender stereotype and also 
creates a more desirable place for members of 
dual-career couples to work. Joshua, a manager in 
the high-potential program of a global consumer 
goods company and part of a dual-career couple, 
explained: “Word gets around the HiPo group 
which senior managers encourage flexible work-
ing, and we compete like crazy to get assignments 
with them.”
COMPANIES MUST EMBRACE a new model of talent 
management to attract and retain tomorrow’s 
leaders. When high potentials see that it’s possible 
to grow and advance in their organizations with-
out sacrificing their partners’ success, they’ll feel 
safer opening up about their mobility and flex-
ibility challenges. As a result, their organizations 
will be able to plan better for the future and make 
the right kinds of investments in the right people. 
Everyone will come out ahead. 
 HBR Reprint R1803H
Jennifer Petriglieri is an associate professor of 
organizational behavior at INSEAD, where she directs 
the Management Acceleration Programme, the Women 
Leaders Programme, and the INSEAD Gender Diversity 
Programme. She is the author of Couples That Work: 
How Dual-Career Couples Can Thrive in Love and in 
Work (forthcoming from HBR Press).
isn’t a pool of trailing spouses. We’re tapping into 
a pool of highly skilled people, in some cases more 
skilled than the talent who is leading the geo-
graphic move.”
Remove cultural obstacles to flexibility. 
Even when companies redesign their talent strate-
gies so that their people can expand networks, 
skills, and experiences in new ways, those policies 
often get blocked culturally. That risk is particu-
larly high when leaders from the unbounded gen-
eration subscribe to the view that the mobility and 
flexibility challenges of dual-career couples are, as 
one executive put it, “personal things that talent 
should work out for themselves.” For HR’s benefit, 
such leaders may pay lip service to supporting 
members of dual-career couples—or they may 
genuinely believe they’re being supportive—while 
still, consciously or not, discouraging or punishing 
the use of flexible work policies.
To give their new talent strategies a fighting 
chance, companies need to change their culture. 
First, they must educate senior leaders about con-
temporary talent and the best ways to attract and 
nurture it. One organization I spoke with was using 
reverse mentoring—partnering a senior executive 
with a talented Millennial—to foster this aware-
ness. “It’s very effective,” the head of HR said. 
“Once leaders understand the challenges, they 
are much better at accommodating them—and of 
course those executives who really ‘get it’ are able 
to hoard the best talent.” The strongest examples 
I’ve seen set up the reverse mentoring in a bilateral 
way: The senior executive mentors a Millennial on 
career and organizational matters, and the Millen-
nial mentors the executive on a range of current 
issues—sometimes technology and social media, 
but more often what motivates Millennials and 
what their lives are like.
That this exposure changes mindsets mirrors 
a discovery in another area of study: the finding 
that men whose wives have careers areless likely 
to discriminate against women at work and more 
likely to facilitate their career development. The 
psychological mechanism at play here is personal-
ization. Someone who experiences “the other’s” 
situation firsthand is much more likely to under-
stand it and respond in a supportive way.
When companies broaden senior leaders’ 
minds through reverse mentoring and updates on 
the proven benefits of working flexibly, attitudes 
about flexible work quickly shift, and that’s what 
transforms the culture. Here’s how it happens: 
When more time—
six months to two 
years—is needed 
for development, 
some companies 
experiment with 
partially remote 
leadership roles.
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90 HBR Special Issue | FALL 2019
RETAINING THE BEST
benefits can win over some 
job seekers faced with higher- 
paying offers that come with 
fewer additional advantages.
As part of our study, we gave 
2,000 U.S. workers ages 18 to 
81 a list of 17 benefits and asked 
them how heavily they would 
weigh the options when decid-
ing between a high-paying job 
and a lower-paying job with 
more perks.
Better health, dental, and 
vision insurance topped the 
list, with 88% of respondents 
saying that they would give this 
benefit “some consideration” 
(34%) or “heavy consideration” 
(54%) when choosing a job. 
Health insurance is the most 
expensive benefit to provide, 
with an average cost of $6,435 
per employee for individual 
coverage or $18,142 for family 
coverage.
The next most-valued 
benefits were ones that offer 
flexibility and improve work-life 
balance. A majority of respon-
dents reported that flexible G
ET
TY
 IM
AG
ES
Quick Takes
The Most Desirable 
Employee Benefits
by Kerry Jones 
include lunches made by a 
professional chef, biweekly 
chair massages, yoga classes, 
and haircuts. Twitter employ-
ees enjoy three catered meals 
per day, on-site acupuncture, 
and improv classes. SAS has a 
college scholarship program for 
the children of employees. And 
plenty of smaller companies 
have received attention for their 
unusual benefits, such as vaca-
tion expense reimbursement 
and free books.
But what should a business 
do if it can’t afford Google-sized 
benefits? You don’t need to 
break the bank to offer at-
tractive extras. A new survey 
conducted by my team at 
Fractl found that, after health 
insurance, employees place the 
highest value on benefits that 
are relatively low cost to em-
ployers, such as flexible hours, 
more paid vacation time, and 
work-from-home options. Fur-
thermore, we found that certain 
IN TODAY’S hiring market, a 
generous benefits package is 
essential for attracting and re-
taining top talent. According to 
Glassdoor’s 2015 Employment 
Confidence Survey, about 60% 
of people report that benefits 
and perks are a major factor in 
considering whether to accept 
a job offer, and 80% of employ-
ees would choose additional 
benefits over a pay raise.
Google is famous for its 
over-the-top perks, which 
HBR.ORG
FALL 2019 | HBR Special Issue 91
using up their vacation time. 
Every year Americans leave 
$224 billion in unused vacation 
time on the table, which creates 
a huge liability for employers 
because they often have to pay 
out this unused vacation time 
when employees leave the 
company. Off ering an unlimited 
time-off policy can be a win-win 
for employer and employee. 
(More than two-thirds of our 
respondents said they would 
consider a lower-paying job 
with unlimited vacation.) For 
hours, more vacation time, 
more work-from-home options, 
and unlimited vacation time 
could help give a lower-paying 
job an edge over a high- paying 
job with fewer benefi ts. Further-
more, fl exibility and work-life 
balance are of utmost impor-
tance to a large segment of the 
workforce: parents. They value 
fl exible hours and work-life 
balance above salary and health 
insurance in a potential job, 
according to a recent survey by 
FlexJobs.
Eighty-eight percent of 
respondents said they’d give 
some or heavy consideration 
to a job off ering fl exible hours, 
while 80% would consider a job 
that lets them work from home. 
Both fl exible hours and work-
from-home arrangements are 
aff ordable perks for companies 
that want to off er appealing 
benefi ts but can’t aff ord an 
expensive benefi ts package. 
Both of these benefi ts typically 
cost the employer nothing—and 
often save money by lowering 
overhead costs.
More vacation time was 
an appealing perk for 80% of 
respondents. Paid vacation 
time is a complicated expense, 
because it’s not simply the cost 
of an employee’s salary for the 
days they are out; liability also 
plays into the cost. American 
workers are notoriously bad at 
Health insurance and 
fl exible hours might tip 
job seekers toward a 
lower-paying job.
Which Benefits Are Most Valued by Job Seekers?
When choosing between a high-paying job and a lower-paying one with better benefits, 
respondents said health insurance and flexible hours might tip them toward the latter.
SOURCE  FRACTL SURVEY OF 2,000 U.S. WORKERS
PERCENTAGE OF RESPONDENTS WHO SAID THE BENEFIT 
WOULD BE TAKEN INTO CONSIDERATION
Better health, dental, and vision insurance
More-flexible hours
More vacation time
Work-from-home options
Unlimited vacation
Student loan assistance
Tuition assistance
Paid maternity/paternity leave
Free gym membership
Free day care services
Free fitness/yoga classes
Free snacks
Free coffee
Companywide retreats
Weekly free employee outings
On-site gym
Team-bonding events
88%
88
80
80
68
48
44
42
39
38
33
32
30
26
24
22
20
Heavy consideration Some consideration
4
2
0
example, HR consulting fi rm 
Mammoth considers its unlim-
ited time-off policy a success 
not just for what it does but also 
for the message it sends about 
company culture: Employees 
are treated as individuals who 
can be trusted to responsibly 
manage their workload regard-
less of how many days they 
take off .
Switching to an unlimited 
time-off policy can solve the 
liability issue; wiping away the 
average vacation liability saves 
companies $1,898 per em-
ployee, according to research 
from Project: Time Off . And 
with only 1% to 2% of compa-
nies currently using an unlim-
ited time-off policy, according 
to the Society for Human 
Resource Management (SHRM), 
this benefi t clearly can make 
companies more attractive.
Contrary to what employers 
might expect, unlimited time 
off doesn’t necessarily equal 
less productive employees and 
more time out of the offi ce. 
92 HBR Special Issue | FALL 2019
RETAINING THE BEST QUICK TAKES
A survey from The Creative 
Group found that only 9% of 
executives think productivity 
would decrease significantly if 
employees used more vacation 
time. In some cases, under an 
unlimited time-off policy, em-
ployees take the same amount 
of vacation time. We adopted 
an unlimited time-off policy 
at Fractl about a year ago and 
haven’t seen a negative impact 
on productivity. Our vice presi-
dent of client services, Ryan 
McGonagill, says there hasn’t 
been a large spike in the amount 
of time employees spend out of 
the office, but the quality of 
work continues to improve.
Student loan and tuition 
assistance also ranked highly on 
the list of coveted benefits, with 
just less than half of respon-
dents reporting thatthese bo-
nuses could nudge them toward 
a lower-paying job. A benefits 
survey from SHRM found that 
only 3% of companies currently 
offer student loan assistance, 
and 52% provide graduate edu-
cational assistance. Although 
educational assistance sounds 
costly, companies can take ad-
vantage of a tax break; employ-
ers can provide up to $5,250 per 
employee per year for tuition 
tax-free.
Job benefits that don’t 
directly impact an individual’s 
lifestyle and finances were 
the least coveted by survey 
respondents, such as in-office 
freebies like food and coffee. 
Company-sponsored gatherings 
like team-bonding activities and 
retreats were low on the list as 
well. This isn’t to say employees 
don’t value these benefits, but 
61%
47
40
55
47
24
16
24
11
23
11
9
10
6
5
4
5
Which Benefits Do Men and Women Prefer?
When choosing between a high-paying job and a lower-paying one with better benefits, 
men and women differ in how much various perks might sway them.
SOURCE  FRACTL SURVEY OF 2,000 U.S. WORKERS
PERCENTAGE OF RESPONDENTS WHO SAID THE BENEFIT
WOULD BE TAKEN INTO HEAVY CONSIDERATION
Better health, dental, and vision insurance
More-flexible hours
More vacation time
Work-from-home options
Unlimited vacation
Student loan assistance
Tuition assistance
Paid maternity/paternity leave
Free gym membership
Free day care services
Free fitness/yoga classes
Free snacks
Free coffee
Companywide retreats
Weekly free employee outings
On-site gym
Team-bonding events
Men Women
47%
38
32
40
33
20
14
14
12
11
9
10
12
7
6
6
7
these perks probably aren’t 
important enough on their own 
to convince a job candidate to 
choose a company.
We noticed gender dif-
ferences regarding certain 
benefits. Most notably, women 
were more likely to prefer fam-
ily benefits like paid parental 
leave and free day care services. 
Parental leave is of high value 
to female employees: 25% of 
women said they’d give paren-
tal leave heavy consideration 
when choosing a job (only 14% 
of men said the same). Men 
were more likely than women 
to value team-bonding events, 
retreats, and free food. Both 
genders value fitness-related 
perks, albeit different types. 
Women are more likely to prefer 
free fitness and yoga classes, 
whereas men are more likely to 
prefer an on-site gym and free 
gym memberships.
Our survey findings suggest 
that providing the right mix of 
benefits that are both inexpen-
sive and highly sought after 
among job seekers can give a 
competitive edge to businesses 
that can’t afford high salaries 
and pricier job perks.
Originally published on HBR.org 
February 15, 2017
HBR Reprint H03FSR
Kerry Jones is the inbound marketing 
manager at Fractl, where she special-
izes in content marketing featuring the 
company’s proprietary research.
HBR.ORG
FALL 2019 | HBR Special Issue 93
get my credit card in time to get 
to my first meeting,” or “I had 
problems accessing the internal 
network.” All those things 
affect how someone feels about 
having joined the company. 
Once you realize that, the 
remit for the onboarding team 
becomes how people experience 
the whole process, end to end. 
To get it right, you have to work 
with a broader set of players. 
You bring in Security to make 
sure the ID badges are there. You 
bring in Real Estate to make sure 
people have a physical space 
and know where to go. You 
bring in Networking to make 
sure their remote access is up 
and running. All that is part of 
onboarding. It’s not just having 
a great meeting with a bunch 
of other new hires on your 
first day.
It took a while for us to 
understand that. You have 
to broaden your scope and 
stop thinking in silos in order 
to create a great employee 
experience.
How has IBM’s approach to 
learning and development 
changed? 
People consume content 
on their phones and tablets 
now—they use YouTube and 
TED talks to get up to speed on 
things they don’t know. So we 
had to put aside our traditional 
learning-management system 
and think differently about 
education and development. 
Again, we brought in our 
Millennials, brought in our 
users, and codesigned a 
learning platform that is 
individually personalized 
for every one of our 380,000 
IBMers. 
It’s tailored by role, with in-
telligent recommendations that 
Co-Creating 
the Employee 
Experience
A conversation with Diane 
Gherson, IBM’s head of HR 
by Lisa Burrell
HBR: In what sense is IBM 
putting employee experience 
at the center of people 
management? 
GHERSON: Like a lot of other 
companies, we started with the 
belief that if people felt great 
about working with us, our 
clients would too. That wasn’t 
a new thought, but it’s certainly 
one we took very seriously, 
going back about four or five 
years. We’ve since seen it borne 
out. We’ve found that employee 
engagement explains two-
thirds of our client experience 
scores. And if we’re able to 
increase client satisfaction by 
five points on an account, we 
see an extra 20% in revenue, on 
average. So clearly there’s an 
impact. That’s the business case 
for the change.
But it has required a shift 
in mindset. Before, we tended 
to rely on experts to build our 
HR programs. Now we bring 
employees into the design 
process, co-create with them, 
and iterate over time so that we 
meet people’s needs.
What does that look like 
in practice?
A good example is employee 
onboarding—the first process 
we took a very hard look at. We 
knew we wanted people to 
walk out thinking, “I’m 
superexcited I’m here, and 
I understand what I need 
to know to get going.” But 
we started too small. We 
approached it in a traditional 
way that made it all about the 
orientation class, all about 
the experience you have on 
your first day. Once we began 
asking new hires how their 
onboarding had gone, we heard 
things like “I didn’t get my 
laptop on time,” or “I couldn’t SA
LL
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M
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N
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94 HBR Special Issue | FALL 2019
RETAINING THE BEST QUICK TAKES
than most companies take to 
redesign their performance 
management programs, and 
we involved about 100,000 
employees. Finally, we asked, 
“What do you want to call it?” 
Tens of thousands of people 
voted. We had three names in 
the end, and Checkpoint was 
selected.
Performance management 
can never be perfect. But 
your baby is never ugly. Our 
employees created their own 
program, and there is pride 
in that. You can see it in their 
ongoing blogs, where we ask 
them to talk about what’s 
working and what’s not and 
to tell us how we can improve 
the system. We’ve been doing 
that ever since we put it out 
there. Their overall message 
has been “This is what we 
wanted.” It was cited as the top 
reason engagement improved. 
People are getting much more 
feedback out of this system, 
in much richer ways. And 
more important, they are not 
feeling like spectators in our 
transformation; they are active 
participants.
How are you using 
“sentiment analysis” to 
further address employees’ 
needs? 
Sentiment analysis is very 
helpful in a world where people 
are always commenting online. 
Our cognitive technology looks 
at the words people choose and 
picks up the tone. It identifies 
whether it’s positive or negative 
and then goes deeper, saying 
whether it’s strongly positive 
or strongly negative. In that 
way it’s almost like looking at 
music—seeing where there 
are very high notes or very low 
notes that are loud. It’s always 
extended hackathon. We used 
design thinking and came up 
with what you might describe 
as a “concept car”—something 
for people to test drive and 
kick the tires on, instead of 
just dealing with concepts. We 
did that in the summer of 2015 
and implemented it across the 
company five months later. 
That’s the power of engaging 
the whole workforce—people 
are much less likely to resist 
the change when they’ve had a 
hand in shaping it. 
To start the co-creation 
process, I blogged about it 
one day and said, “We’d love 
your input. If you hate it, we’ll 
start over,no problem. But we 
really want your thoughts.” 
We made a few videos about 
what we thought it might look 
like. I got 18,000 responses 
overnight. Fortunately, we had 
the technology to analyze it all 
and see what people liked and 
didn’t like. 
At first some people said, 
“This is such a sham—you 
already know what you want 
to do.” But we explained that 
we really wanted to hear from 
them, and we got them into 
various discussion forums. It 
took a while, but I think we 
did turn them around. We 
kept communicating, saying, 
“OK, you liked this; you didn’t 
like that. And here are areas 
where you can’t seem to agree.” 
Meanwhile, we were putting 
together prototypes to show 
people. 
I was clear up front that 
there were some ground rules. 
For example, we were not 
going to get rid of performance 
discussions, and we wanted 
pay-for-performance. But in 
general, it was wide open. The 
whole process took less time 
years to demonstrate which 
employees have applied skills. 
The tool then helps you achieve 
the badge by recommending 
specific webinars and internal 
and external courses. It’s all 
based on artificial intelligence. 
Skills inference is at about 96% 
accuracy at this point.
How do you know that? 
We used to have this laborious 
manual process of getting 
people to fill out skills 
questionnaires and having their 
managers sign off on them. But 
that gets outdated really fast. So 
we stopped doing that. Instead, 
leaders in particular job families 
or industries do spot checks 
on how well we are inferring. 
They interview employees 
and identify where they are, 
comparing that with what the 
inference was in our system. 
IBM has given its 
performance management 
system an overhaul as well. 
How have employees been 
involved in that process? 
As you know, performance 
management is kind of a 
lightning rod in most 
companies. Rather than do the 
typical thing—which would be 
to do some benchmarking, pull 
together a bunch of experts, 
come up with a new design, 
and pilot it—we decided to go 
all out and co-create it with 
our employees in a sort of 
are continually updated. And 
it’s organized sort of like Net flix, 
with different channels. You 
can see how others have rated 
the various offerings. There’s 
also a live-chat adviser, who 
helps learners in the moment. 
We measure HR offerings 
such as learning with a Net 
Promoter Score—the ultimate 
metric for an irresistible experi-
ence. Before, we used a classic 
five-point satisfaction scale. 
Even if someone rated you a 3.1, 
you ended up saying they were 
satisfied, whereas with Net Pro-
moter, you have to be at the far 
end of the scale for it to mean 
anything, because you have to 
subtract all the detractors. It’s 
much harder to get that, and it 
gives you much better feedback 
on what people are experienc-
ing. For learning, at last count, 
our NPS was 60. That’s in the 
“excellent” range, but of course 
there’s still room to improve.
What kinds of tools do you 
use to customize learning? 
With Watson Analytics, we’re 
able to infer people’s expertise 
from their digital footprint 
inside the company, and we 
compare that with where they 
should be in their particular 
job family. The system is 
cognitive, so it knows you—it 
has ingested the data about 
your skills and is able to give 
you personalized learning 
recommendations. It tells you, 
“OK, you need to increase your 
depth in these areas—and here 
are the offerings that will help 
you do that.” You can then pin 
those or queue them up in your 
calendar for future learning. The 
system also looks at how close 
you may be to earning a digital 
badge, which we’ve started 
using in just the past couple of 
“ People are much 
less likely to resist 
the change when 
they’ve had a hand 
in shaping it.”
FALL 2019 | HBR Special Issue 95
weekend. People didn’t want us 
making the decision for them. 
That was another case where 
we quickly got together and 
said, “Hey, if they want to be 
responsible for their own taxes, 
they can do it.” It was a good 
wake-up call for us to not be so 
paternalistic. 
In organizations where 
people aren’t physically all 
together, you can use sentiment 
analysis to get a sense of where 
you’ve got trouble spots, where 
your management isn’t strong 
enough, where groups of 
people are expressing negative 
opinions. It allows you to check 
in on those sites or groups and 
find out what’s going on.
Do employees have more 
power now than in the past?
Yes. So much more weight is 
now given to what is said inside 
an organization, because it 
can be heard outside as well, 
through social media. Glassdoor 
is a perfect example. In the past 
you might have had companies 
that weren’t great to work for, 
but only a small circle of people 
knew about it. Now the whole 
world knows about it, because 
it’s on Glassdoor—and that’s 
turned companies into glass 
houses. People can look in and 
see what’s going on and make 
judgments about whether they 
want to work there in a way that 
they weren’t able to before.
HBR.ORG
“ We’ve been able to 
swiftly detect problems 
and commit to doing 
something about them.”
behind our firewall, never 
external. It’s not looking at any 
of the information people pass 
around or at their email content 
or browsing behavior. It’s just 
looking at tone in their blogs and 
comments inside the firewall. 
With this approach you can 
pick up pretty quickly if there’s 
an area you need to dive into. 
We’ve been able to swiftly detect 
problems that are starting to 
brew and, more important, 
make a commitment to do 
something about them. This is 
the most exciting part of having 
a social platform to work with. 
We’ve had several examples of 
things we did wrong. Some 
of my folks decided we wouldn’t 
reimburse for ridesharing. 
Employees became agitated, 
and I could quickly respond 
to a concern that had turned 
into a petition. “I read all your 
comments,” I told them, “and 
you made some great points 
we hadn’t thought of. We were 
trying to look out for your 
security, but on balance, this 
wasn’t the right choice. Let’s 
return to our original policy.” All 
this happened within 24 hours. 
People felt listened to and were 
very appreciative.
We had a similar situation 
about a year ago. We had to 
impute income when you were 
traveling to a client site for a full 
week and, instead of returning 
home right away, you had your 
spouse or a friend join you 
for the weekend. Because we 
would reimburse the guest’s 
travel, it created a tax issue. We 
altered the program because 
that was getting messy, and 
again employees were incensed. 
I can certainly understand why. 
If you’re on the road all the 
time, of course you might want 
your spouse to join you for a 
Let’s go back to the business 
reasons behind IBM’s shift to 
agile talent practices—can you 
say more about those?
I mentioned client satisfaction. 
Clients today are looking for 
speed and responsiveness like 
never before. In an earlier era 
what they really wanted was the 
best product at the best price—
efficiency was important, but 
speed was less so. 
In the early 2000s we 
would have staffed a project 
with experts from all over the 
world, and they would have 
spent a fraction of their time 
on that project, because they 
were also working on other 
projects. They would have 
joined conference calls, which 
is always hard because people 
are in different time zones. And 
I’m sure they were multitasking 
while they were on those calls. 
That project might have taken 
six months to a year. Now we 
would take a smaller group of 
dedicated people and put them 
together for three months, 
and they would get it all done 
using agile methodology. It’s a 
different way of thinking about 
how to create value for clients. 
It responds to their need for 
speed.
Is there some hope that an 
agile approach to talent will 
help IBM make up ground in 
revenue and growth that 
it lost in its transition to 
cloud computing and otherbusinesses? 
We’re a company that’s 
transforming itself: 45% of our 
revenue comes from businesses 
we were not in five years ago, 
and we are an $80 billion 
company. When you’re going 
through that kind of shift and 
seeing a downturn in some 
of your legacy businesses, 
and you’re renovating those 
while you’re launching new 
businesses, you may see some 
unevenness in performance. 
You’re basically changing the 
tires while you’re driving 
the car. And yes, that takes 
agility. 
Originally published in Harvard Business 
Review March–April 2018 
HBR Reprint R1802B
Lisa Burrell is a senior editor at HBR.
96 HBR Special Issue | FALL 2019
RETAINING THE BEST QUICK TAKES
More working parents care 
more—and may vote with 
their feet. Several recent stud-
ies indicate that for working 
parents, flexibility and work-life 
balance trump every other ca-
reer decision-making criteria—
including pay. And research 
shows that men, historically 
less engaged in childcare and 
other child-related activities, 
are becoming increasingly 
committed to it: Today’s dads 
overwhelmingly report wanting 
to be present and on the job 
at home. They’re becoming 
increasingly willing to make 
serious career choices around 
it, too. So working parenthood 
isn’t a “women’s thing” any-
more—it’s a universal concern 
driving whether people join or 
stay with your organization.
It’s a bellwether. How you 
treat working parents is an 
indicator of how you treat talent 
in general, especially in the eyes 
of prospective or more-junior 
employees. Does the Career 
sections of your corporate 
website include information 
about family-related policies? If 
not, candidates—whether they 
have kids or not—may quickly 
move on to other sites and job 
opportunities that appear more 
parent-friendly. And if up-
and-coming stars with young 
children are leaving your team 
or organization to stay home, or 
accepting jobs where it seems 
more feasible to combine work 
and family, their younger col-
leagues (folks who aren’t part 
of that 52 million yet but want 
to be someday) will notice 
and start wondering if they’ve 
found the right place to build 
their long-term careers.
Bottom line: Without a good 
approach to working parent-
hood that you’re willing to 
ployment rates are at near-
record lows. So, if you’re having 
serious trouble finding the tal-
ent you need, it’s probably time 
to focus on how you can attract 
this huge pool of working moth-
ers and fathers, retain them, and 
ensure they deliver at work.
Although I’ve used the United 
States as an example here, data 
on the growing ranks of profes-
sionals with children in other 
countries is also eye-opening. 
(In England alone, there are one 
million more working moth-
ers now than 20 years ago.) In 
today’s war for talent, working 
parenthood isn’t a skirmish—it’s 
a major, central battle.
The struggle is arguably 
more difficult today than 
in past decades. Not only is 
the sheer number of working 
parents large and growing, but 
those men and women also 
carry much heavier loads than 
previous generations have. To-
day’s working parents are three 
times more likely, on average, to 
be part of dual-career couples or 
to be single than they are to have 
spouses at home full-time. That 
means the majority of commit-
ted working-parent employees 
have no slack in their system: no 
one to whom they can hand off 
the school pickup or pediatri-
cian visit or 10 PM feeding. And 
as wonderful as many techno-
logical changes are, some have 
also made working parenthood 
harder: iPhone in hand, there’s 
no reason, or excuse, to ever 
be “off” work, even during the 
parent-teacher conference or 
family dinner. Translation: 
Being a working parent isn’t a 
marginal or occasional concern 
for mothers and fathers on your 
team; it’s one of the central chal-
lenges of their lives, and they 
grapple with it daily.
issue probably still felt adjacent 
to your core business goals, a 
relatively small and inevitable 
cost of doing business.
But it isn’t anymore. In the 
current economic and cultural 
landscape, the Working Parent 
Problem has moved up to the 
forefront of leadership concerns, 
and it’s going to stay there. 
Ignored, it can become a power-
ful and insidious threat to your 
team’s and organization’s success.
Here’s why focusing on work-
ing parents is so important:
The demographic is huge. 
Let’s look at the cold hard data: 
In the United States, the civilian 
workforce ages 25 to 54 is 102 
million people, and there are 
52 million working parents, 
according to the Department 
of Labor. It’s therefore pos-
sible—probable, even—that 50% 
or more of your new-product 
sales team, or line managers, or 
clinical care providers, or the 
candidates for that specialty 
role you’ve been recruiting for 
and that’s proving impossible to 
fill, are trying to be committed 
professionals while also raising 
their kids in a present and loving 
way. At the same time, unem-
YOU’RE A LEADER with ambi-
tious goals for yourself and your 
team in 2019. The plan is set; 
the performance, growth, and 
efficiency targets committed 
to. But, to be fully prepared for 
the year, one issue should be 
at the top of your priority list: 
the Working Parent Problem.
This is a new, simple label we 
can use to describe the some-
times overwhelming challenge 
of trying to earn a living and 
build a career while also parent-
ing well. For organizations and 
leaders, it refers to the challenge 
of effectively employing and 
fully unleashing the potential of 
the folks who are navigating the 
demands of work and family.
If you’ve thought about the 
Problem before as a manager, 
it’s probably been under a dif-
ferent, hazier label (“work-life 
balance” or “integration”), and 
potential solutions may have 
seemed like a nebulous, elective 
effort; there was no clear path or 
upside to getting involved. Even 
if you’ve directly confronted 
the Problem in the past—for 
example, a star performer sud-
denly decided to stay home at 
the end of a parental leave—the 
Your Company Needs a Better 
Retention Plan for Working Parents
by Daisy Wademan Dowling 
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FALL 2019 | HBR Special Issue 97
HBR.ORG
if counterintuitive: It helps the 
business succeed.
In my last job as senior 
director at HubSpot, and now 
as CMO of G2, I’ve not only 
encouraged my employees to 
look elsewhere but also told 
them that I keep an eye out for 
potential new jobs for myself as 
well. Ironically, all this helps me 
win—and quite often keep—ter-
rific employees. Here’s why.
Employees want develop-
ment, not lip service. Today’s 
employees, especially Millen-
nials, “want jobs to be develop-ST
AN
 T
EK
IE
LA
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UT
H
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AG
ES
Why I Encourage My Best 
Employees to Consider 
Outside Job Offers
by Ryan Bonnici
showcase publicly and some 
visible examples of moms and 
dads succeeding in your organi-
zation, you’ll have a hard time 
developing a reputation as a 
great boss or convincing people 
that your company is “a great 
place to work.”
The issue pervades our 
public dialogue. Scan the 
headlines or type the term 
“working parent” into your 
browser, and you’ll find a 
deluge of articles, commentary, 
and opinion generated in the 
past two to three years—all 
underscoring the immediacy 
and scope of the Working Par-
ent Problem. It’s certainly top 
of mind for anyone directly 
affected by it, and increasingly 
for people who aren’t, and will 
quite likely stay in that spotlight 
for the foreseeable future. If 
you’re a senior leader who 
hasn’t yet gotten a question 
about the issue from a reporter, 
investor, or board member in 
front of a crowd, or from a star 
performer during a mentoring 
conversation, you probably 
will soon. You don’t want to get 
caught without a thoughtful 
stance on a hot-button topic 
that affects so many people.
External help probably 
isn’t on the way—at least, not 
anytime soon. Yes, there has 
been a lot of discussionrecently 
in the United States and other 
countries about working-parent- 
friendly legislation, including 
paid and extended parental 
leaves. While those types of laws 
could eventually be helpful for 
parents and for organizations, 
they may not pass or pass as 
proposed, and they could be de-
layed for years. To be effective, 
your talent strategy has to be 
based on the here and now, not 
on the “maybes” of the future.
So what exactly does a strong, 
feasible strategy look like? And 
how, in the face of this large, 
complex challenge, can indi-
vidual leaders take charge and 
make an impact? In my consult-
ing work, I’ve advised executives 
and organizations of all sizes and 
types in various industries to 
focus on six key things:
1. Demonstrate personal 
support for working-parent em-
ployees in a highly visible way.
2. Define your organization’s 
working-parent challenge from 
the frontline employee perspec-
tive, through both a quantitative 
and a qualitative lens.
3. Engage allies within and 
outside the HR team to identify 
and execute on solutions.
4. Take a comprehensive 
approach rather than relying on 
silver bullet solutions.
5. Support—and help 
shape—grassroots, employee-
led solutions, such as peer-to-
peer working-parent mentoring 
programs or employee resource 
groups (ERGs).
6. Outcommunicate the 
competition when it comes to 
working-parent matters.
Ultimately, every leader and 
organization will find differ-
ent ways to solve the Working 
Parent Problem. But, as with 
any challenge, acknowledging 
its reality, size, and nature is 
always the right place to start.
Originally published on HBR.org 
February 1, 2019
HBR Reprint H04RHK
Daisy Wademan Dowling is the founder 
and CEO of Workparent, a consulting 
firm that provides practical, commercial 
advice, solutions, and training to working 
parents and to the organizations that 
employ them. She also works as a coach, 
consultant, and adviser to organizations 
seeking to drive performance through 
their people. 
EVERY DAY we get new remind-
ers of just how tough the 
war for talent can be. It isn’t 
enough to attract the greatest 
employees— you have to retain 
them. That’s become a bigger 
challenge with job-hopping on 
the rise. One survey found that 
64% of workers, and 75% of 
those younger than age 34, be-
lieve frequently switching jobs 
will benefit their careers.
Why, then, would I actively 
encourage even my best em-
ployees to pursue outside job 
offers? The answer is simple, 
98 HBR Special Issue | FALL 2019
RETAINING THE BEST QUICK TAKES
Openness allows conversa-
tions to thrive. By encourag-
ing my employees to consider 
outside possibilities and sharing 
my stories with them, I foster 
a culture of openness in our 
communication. When they get 
outside offers, that communica-
tion makes a big difference.
As LinkedIn founder Reid 
Hoffman wrote in “Encourage 
Your Employees to Talk About 
Offers” (HBR, 2014), employees 
often feel they can’t speak hon-
estly with their managers about 
their career goals “because of 
the reasonable belief that doing 
so is risky and career-limiting if 
the employee’s aspirations do 
not perfectly match up with the 
manager’s existing views and 
time horizons.” So they don’t 
share information about out-
side offers until they’ve gone 
“far down the road” with the 
potential new employer.
By showing my team that 
I want to support them either 
way, I am creating a culture 
in which my employees feel 
comfortable sharing every 
career step with me. This open 
dialogue gives me the time and 
opportunity to find a way 
to keep them. Often, there’s 
something I can do—such as get 
them a new experience or proj-
ect, add to their responsibilities, 
or negotiate a raise. I’ve found 
that most employees don’t 
realize how much flexibility 
ment opportunities,” Gallup 
explains. Eighty-seven percent 
of Millennials and 69% of non-
Millennials rate “professional or 
career growth and development 
opportunities” as important. 
But many businesses are failing 
on this front. Less than half the 
Millennials surveyed by Gallup 
strongly agreed that they’d had 
opportunities to learn and grow 
in the previous year. And only 
one-third said their most recent 
learning opportunity was “well 
worth” their time.
So while almost every com-
pany promises to develop its 
employees, all too often that’s 
just lip service. And it’s up to 
managers to ensure their com-
panies live up to the promises 
of professional development. 
As executive coach Monique 
Valcour wrote in “If You’re Not 
Helping People Develop, You’re 
Not Management Material” 
(HBR, 2014), the “manager- 
employee dyad is the new 
building block of learning and 
development in firms.”
When I make clear to my 
employees that I want them 
to consider all options for 
their careers, they see that 
I’m genuinely committed to 
helping them learn and grow. 
If I think they’ve gotten to the 
top of their learning curve on 
my team, and I can’t figure out 
a way to help them grow, I will 
support their efforts to get a job 
somewhere else.
As research has found, em-
ployees often quit not because 
of their company but because of 
their manager. They stay for 
a manager they believe in—
one who wants to help them 
achieve their goals. I’ve had 
employees tell me they chose to 
work for me, and chose to stay, 
because of that commitment.
When great employees 
decide to leave on good 
terms, there can be 
upsides for the company.
a company has when it comes 
to finding a way to retain high-
performing talent.
This process also makes 
them feel respected. As Chris-
tine Porath and Tony Schwartz 
found in an HBR survey they 
conducted in 2013, half of 
employees don’t feel respected 
by their bosses. Those who do 
are more likely to stay.
There are benefits to their 
leaving. This may be the most 
counterintuitive point of all. 
But when great employees 
decide to leave on good terms, 
there can be an upside for the 
company. Out in the world, 
they’ll be in a powerful posi-
tion to speak honestly about 
their experiences. If they 
leave our company feeling 
good about us, they’ll speak 
positively about the brand. 
If they feel good about me, 
they’ll encourage great people 
to come work for me.
This is why, once it’s be-
come clear that there’s no way 
I can keep them, I offer advice 
to help my staff negotiate the 
best deal they can get at their 
new employer.
Every employee is unique. 
So it’s true that not everyone 
is entirely replaceable. But 
when someone leaves, it is an 
opportunity for me to bring in 
someone else with different 
strengths and new things to 
offer the team.
They’re more likely to 
return. Not every new venture 
works out. Some employees 
leave to try their hand at start-
ups, which have a high failure 
rate. Others work at new 
companies only to find that the 
job isn’t what they expected 
or the culture isn’t the right 
fit. So these great employees 
may be looking for work again 
someday—and you want your 
company to be at the top of 
their list.
These so-called boomerang 
employees are on the rise and 
“will be an increasingly valu-
able source of talent,” Tammy 
Erickson has noted (see “Never 
Say Goodbye to a Great Em-
ployee” below). So a goodbye 
party for an employee may turn 
out to have been a “farewell 
for now.” If you can help that 
employee feel that the place he 
or she is leaving is something of 
a work “home,” he or she just 
might return.
Of course, there’s no “one 
size fits all” way to handle 
employee relationships. People 
have different styles and differ-
ent comfort zones for commu-
nication. And businesses have 
different hiring and recruiting 
strategies depending on their 
company cultures. No matter 
what I do, some employees 
will choose to be more secre-
tive and to keep their outside 
opportunities closer to the 
vest. That’s OK. As long as 
I make clear that my door is 
open, and that while they’re 
wanted at our company, we 
won’t try totrap them here, 
we build a culture of employee 
empowerment.
And no matter where they 
end up next, if they become 
hiring managers, I want them to 
have learned valuable lessons 
about giving their own em-
ployees this same freedom and 
encouragement. This is how we 
build stronger work cultures.
Originally published on HBR.org 
September 11, 2018
HBR Reprint H04J1B
Ryan Bonnici is the chief marketing 
officer of G2.
FALL 2019 | HBR Special Issue 99
HBR.ORG
forward-thinking work arrange-
ments that let people connect 
and reconnect with your organi-
zation in a variety of ways. 
For example:
Flexible time: flexible shifts, 
compressed workweeks, and 
individualized work schedules
Reduced time: part-time 
options, job sharing, self-
scheduling, leave-of-absence 
programs, and cyclic or project-
based work
Flexible place: mobile work 
and telecommuting
Tasks, not time: require-
ments to put in only as much 
time as it actually takes to 
get the work done, removing 
restrictions around a prescribed 
time or place
Decelerating roles: career 
path options that go “down” (to 
lower levels of responsibility)
In addition to setting the 
right tone at the beginning, 
structure the exit process to 
facilitate reentry, and build 
a flexible network of talent 
possibilities. Invite them to 
join your network, build your 
own flexible talent pool, and 
create a residual knowledge 
bank. Regardless of whether 
a person’s departure is volun-
tary or involuntary, it’s never 
wise to say goodbye to a good 
employee. 
Originally published on HBR.org 
December 19, 2013
HBR Reprint H00L7A
Tamara J. Erickson is the author of Re-
tire Retirement: Career Strategies for the 
Boomer Generation (Harvard Business 
Press, 2008), Plugged In: The Generation 
Y Guide to Thriving at Work (Harvard 
Business Press, 2008), and What’s Next, 
Gen X? Keeping Up, Moving Ahead, and 
Getting the Career You Want (Harvard 
Business Press, 2009). Erickson was 
named one of the top 50 global business 
thinkers for 2011.
Setting the stage for positive 
exits and creating the possibil-
ity of happy returns requires 
redefining the relationship from 
the beginning—setting different 
expectations during the hiring 
process. Today more than 25% 
of the working population goes 
through career transitions 
every year, and half of all hourly 
workers leave new jobs within 
the first 120 days, according to 
research conducted by Talya N. 
Bauer of SHRM Foundation; 
clearly the “employee for life” 
model has run its course.
Rather than implying that 
you expect indefinite tenure 
and unconditional loyalty, ask 
for the employee’s full discre-
tionary effort for the time he or 
she will be here. And instead of 
signaling that you will provide 
opportunities for life (some-
thing few hires actually trust 
anyway), make it clear that you 
are offering interesting and 
challenging work, coupled with 
fair arrangements, while it is 
available.
Reducing the implied 
promise of long-term protection 
and care sets the expectation 
that departures will naturally 
occur when that interesting 
and challenging work comes to 
an end. It conveys the expec-
tation that departures can be 
mutually positive and facilitates 
multiple employment stints 
(off-ramps, on-ramps, boomer-
angs, and retiree returns) as the 
company’s workload warrants. 
This philosophy focuses on 
matching relevant skills and 
capabilities in the moment and 
recognizes, where appropriate, 
the legitimacy of concurrent 
employment arrangements.
Creating an environment that 
leverages the power of positive 
“outs” is greatly enhanced by 
cheaper to hire, particularly if 
a former manager has main-
tained contact while the 
employee is away.
So how do you make it so 
that these boomerang employ-
ees actually want to return to 
your company?
The biggest challenge to 
leveraging boomerang talent for 
most organizations is the nature 
of the “out” process itself. For 
most of us, departures, whether 
initiated by the employee or the 
company, are negative events 
weighed down with feelings of 
guilt and failure, often on both 
sides. This negativity occurs 
because conventional “outs” 
are shaped by the expectations 
we convey about the relation-
ship from the beginning—that 
we want unconditional loyalty 
and that it will be rewarded 
(perhaps “wink, wink”) with 
a steady career and comfort-
able retirement. When these 
expectations are not borne out, 
due to either party’s initiative, 
bad feelings are the inevitable 
result.
SO-CALLED BOOMERANG 
employees—those who leave 
and then return—will become 
an increasingly valuable source 
of talent over the years ahead. 
Perhaps the most frequently 
discussed example is women 
who chose to off-ramp for 
several years sometime in their 
career and are now eager to 
return to work. Older workers 
may present boomerang pos-
sibilities as well. Sixty percent 
of workers ages 60 and older 
say they will look for a new job 
after they retire, possibly back 
in your organization.
But it would be a mistake to 
focus only on these two groups; 
there are also those who left 
initially due to personal issues, 
other job opportunities, or even 
a round of layoffs.
Former employees, of course, 
offer many advantages: They 
are familiar with your opera-
tions and culture, know many 
of your current employees and 
clients, and may require little 
or no training to start making 
contributions. Often they are 
Never Say Goodbye to a Great 
Employee
by Tammy Erickson
AL
TM
O
DE
RN
/G
ET
TY
 IM
AG
ES
100 HBR Special Issue | FALL 2019
Originally published in 
March–April 2018
ILLUSTRATION BY JOANNA ŁAWNICZAK
H AVE YOU EVER been on a 
trapeze?” That’s how Martha, 
an independent consultant, 
responded when we asked her 
to describe her work in the fi ve 
years since she’d left a global 
consulting fi rm to set out on her own. She had re-
cently tried the art, which she saw as a good meta-
phor for her life: the void she felt when between 
assignments; the exhilaration of landing the next 
engagement; the discipline, concentration, and 
grace that mastering her profession required. Tra-
peze artists seem to take huge risks, she explained, 
but a safety system—including nets, equipment, 
and fellow performers—supports them: “They 
appear to be on their own, but they’re not.”
Thriving 
in the 
Gig 
Economy
How successful freelancers manage the 
uncertainty by Gianpiero Petriglieri, Susan Ashford, 
and Amy Wrzesniewski
UNDERSTANDING THE GIG ECONOMY
102 HBR Special Issue | FALL 2019
UNDERSTANDING THE GIG ECONOMY THRIVING IN THE GIG ECONOMY
Martha (whose name, like others in this article, 
has been changed) is part of a burgeoning seg-
ment of the workforce loosely known as the gig 
economy. Approximately 150 million workers in 
North America and Western Europe have left the 
relatively stable confines of organizational life—
sometimes by choice, sometimes not—to work 
as independent contractors. Some of this growth 
reflects the emergence of ride-hailing and task-
oriented service platforms, but a recent report 
by McKinsey found that knowledge-intensive 
industries and creative occupations are the larg-
est and fastest-growing segments of the freelance 
economy. 
To learn what it takes to be successful in inde-
pendent work, we recently completed an in-depth 
study of 65 gig workers. We found remarkably 
similar sentiments across generations and occupa-
tions: All those we studied acknowledged that 
they felt a host of personal, social, and economic 
anxieties without the cover and support of a 
traditional employer—but they also claimed that 
their independence was a choice and that they 
would not give up the benefits that came with it. 
Although they worried about unpredictable sched-
ules and finances, they also felt they had mustered 
more courage and were leading richer lives than 
their corporate counterparts. 
We discovered that the most effective in-
dependent workers navigate this tension withcommon strategies. They cultivate four types 
of connections—to place, routines, purpose, and 
people—that help them endure the emotional 
ups and downs of their work and gain energy 
and inspiration from their freedom. As the gig 
economy grows worldwide, these strategies are 
increasingly relevant. Indeed, we believe they 
may also be helpful to any corporate employees 
who are working more autonomously, from 
home or a remote office, or who feel they 
might one day want—or need—to jump into 
a freelance career. 
Produce or Perish
The first thing we realized when we began 
interviewing independent consultants and art-
ists was that the stakes of independent work are 
enormously high—not just financially but also 
existentially. Unshackled from managers and 
corporate norms, people can choose assignments 
that make the most of their talents and reflect 
their true interests. They feel ownership over 
what they produce and over their entire profes-
sional lives. One study participant told us, “I can 
be the most I’ve ever been myself in any job.” 
However, the price of such freedom is a 
precariousness that seems not to subside over 
time. Even the most successful, well-established 
people we interviewed still worry about money 
and reputation and sometimes feel that their 
identity is at stake. You can’t keep calling yourself 
a consultant, for example, if clients stop ask-
ing for your services. A well-published writer 
told us, “You become your work. If you write a 
good book…it’s really great, and when you don’t 
achieve it, you have to accept…that failure might 
define who you are to yourself.” An artist agreed: 
“There’s no arriving. That’s a myth.”
For this reason, productivity is an intense 
preoccupation for everyone we interviewed. 
It provides self-expression and an antidote to 
precariousness. Interestingly, however, the 
people we talked with aren’t just focusing on 
getting things done and sold. They care about 
both being at work—having the discipline to 
regularly generate products or services that find 
a market—and being into their work: having the 
Independent workers spend a great deal of 
time developing a “holding environment”— 
a physical, social, and psychological space 
for their work.
FALL 2019 | HBR Special Issue 103
HBR.ORG
Idea 
in Brief
THE SHIFT
A growing segment of the work-
force, known as the gig economy, 
is forgoing the relatively stable 
confines of organizational life for 
the freedom and ownership of 
independent work. But the price 
of such liberty is a precarious-
ness that doesn’t wane.
MAKING A SPACE
To combat instability and sustain 
productivity, successful inde-
pendent contractors develop a 
“holding environment” for them-
selves, establishing connections 
to place, routines, purpose, and 
people that help them endure 
the emotional turbulence of their 
work and gain energy from their 
autonomy. 
FINDING BALANCE
These strategies both liber-
ate people to be creative and 
bind them to work so that they 
continue to produce. Freelancers 
find their success in the balance 
between predictability and 
possibility, between the promise 
of continued work—and feeling 
present, authentic, and alive in it. 
courage to stay fully invested in the process and 
output of that labor. 
Sustaining productivity is a constant struggle. 
Distress and distractions can erode it, and both 
impediments abound in people’s working lives. 
One executive coach gave a poignant descrip-
tion of an unproductive day: “It’s when there 
is so much to do that I’m disorganized and 
can’t get my act together. [In the evening,] the 
same e-mails I opened in the morning are still 
open. The documents I wanted to get done are 
not done. I got distracted and feel like I wasted 
time.” A day like that, he said, leaves him full of 
self-doubt.
When we asked interviewees the secret to get-
ting through such days and ultimately sustaining 
productivity as they defined it, we discovered 
a paradox at the heart of their answers. They 
all want to preserve their independence and, in 
many cases, even their unsettledness (which 
one consultant described as the key to continued 
learning and “keeping my edge”), but they also 
spend a great deal of time developing a “holding 
environment”—a physical, social, and psycho-
logical space for their work. 
This concept—first used by the British psycho-
analyst Donald Winnicott to describe how atten-
tive caregivers facilitate children’s development 
by buffering them against distress and creating 
room for experimentation—has since been em-
ployed in the field of adult development to refer 
to conditions in which people can be their best 
and grow. Corporate employees, of course, can 
find them with a good boss in a solid organiza-
tion. But for independent workers, a holding en-
vironment is less a gift than an accomplishment; 
it must be cultivated, and it can be lost. 
So they create these environments for them-
selves by establishing and maintaining what 
we call “liberating connections”—because they 
both free people up to be individually creative 
and bind them to work so that their output 
doesn’t wane. 
The Four Connections
Place. Disconnected from a corporate office, 
the people we interviewed find places to work 
that protect them from outside distractions and 
pressures and help them avoid feeling rootless. 
Though many claimed their work was portable, 
they all still seemed to have somewhere to 
retreat. One writer told us, “People fail because 
they don’t create a space and time to do whatever 
it is they need to do.” 
We visited many of these spaces in person and 
noticed several similarities among them. They 
feel confined—almost uncomfortably so in the 
case of some artists. They are used consistently 
for all substantive work. They allow easy access 
to the tools of the owner’s trade and to little else. 
And they’re dedicated to work; people usually 
leave them once their daily tasks are done. One 
software engineer, whose home office has all 
these features, described it as a “fighter pilot 
cockpit,” where everything he needs is within 
arm’s reach. “Sometimes it’s claustrophobic,” he 
explained, but “when I’m there, the open space is 
in my mind.”
Despite these commonalities, each workspace 
is also unique, with a location, furniture, sup-
plies, and decorations that reflect the idiosyn-
crasy of its owner’s work. These places are not 
just protective cocoons for the working self—they 
evoke it, too. Karla, an independent consultant 
who initially told us she could do work “wher-
ever I show up and am doing something that 
has positive impact in the world,” eventually 
admitted that her home office is where she goes 
to avoid distraction and find inspiration, literally 
surrounded by her current and potential projects, 
arranged in visible and accessible piles. “When 
I walk through that door, I step into a space that 
embraces all the different aspects of myself,” she 
told us. “I feel at home in there.” Without that 
place and the space it gives her, Karla explained, 
she would probably be too sensitive to external 
demands and thus less focused and free. 
Routines. In organizations, routines are often 
associated with safety or boring bureaucracy. 
However, a growing body of research has shown 
that elite athletes, scientific geniuses, popular 
artists, and even everyday workers use routines 
to enhance focus and performance. The profes-
sionals we spoke with tend to rely on them in the 
same way. 
Some routines improve people’s workflow: 
keeping a schedule; following a to-do list; begin-
ning the day with the most challenging work or 
with a client call; leaving a sentence incomplete 
in an unfinished manuscript to make an easy 
start the next day; sweeping the studio floor 
while reflecting on a new piece. Other routines, 
usually involving sleep, meditation, nutrition, or 
104 HBR Special Issue | FALL 2019
UNDERSTANDING THE GIG ECONOMY THRIVING IN THE GIG ECONOMY
exercise, incorporatepersonal care into people’s 
working lives. Both kinds often have a ritual ele-
ment that enhances people’s sense of order and 
control in uncertain circumstances.
One consultant we interviewed takes a bath 
every morning and visualizes what she wants to 
accomplish while she soaks. Another consultant, 
Matthew, who specializes in helping boards focus 
on innovation, keeps a strict daily schedule: 
“I’m up at 6:00 and there’s exercise. I pack my 
wife’s lunch. We pray. She’s out the door around 
8:00. I’m in my office by 8:30, and I do work 
where there’s deeper thought required—design 
or writing— in the morning. That’s when I’m at 
my best. Then in the afternoon I schedule phone 
calls, more of the business or financial things that 
need to be done.” This discipline even extends to 
his wardrobe: “I always get dressed for the office. 
Most days in summer I wear shorts when I’m not 
on the road, but still I shower and shave as if I 
were going to a workplace separate from home.” 
That may sound rigid, but it helps Matthew 
pour himself into his work. He and other suc-
cessful independent workers seem to follow the 
advice of the French novelist Gustave Flaubert: 
“Be regular and orderly in your life…so that you 
may be violent and original in your work.” 
Purpose. For most people in our study, 
striking out on their own initially involved do-
ing whatever work would allow them to find a 
footing in the market. But they were adamant 
that succeeding means taking only work that 
clearly connects to a broader purpose. All could 
articulate why their work, or at least their best 
work—be it to empower women through film, 
expose harmful marketing practices, sustain the 
American folk music tradition, or help corporate 
leaders succeed with integrity—is more than 
a means of earning a living. Purpose creates a 
bridge between their personal interests and moti-
vations and a need in the world. Matthew, for ex-
ample, said that although at first he felt “a certain 
desperation around having clients and making 
an income,” over time his view of success shifted 
“to one that is a lot about living a life of service to 
others and making the planet a better place.” 
An executive coach we interviewed told us that 
purpose keeps her steady, inspired, and inspiring. 
“A big distinction between successful indepen-
dents and the ones who aren’t or go back [to 
corporate jobs] is getting to that place of knowing 
what you’re meant to do. That gives me resilience 
for the ups and downs. It gives me the strength 
to decline work that isn’t in alignment. It gives 
me a quality of authenticity and confidence that 
clients are drawn to. It’s helpful to building or 
maintaining the business and serving the people 
I am here to serve.”
We found that purpose, like the other connec-
tions, both binds and frees people by orienting 
and elevating their work.
People. Humans are social creatures. Studies 
in corporate settings have long demonstrated 
how important other people are to our careers—
as role models who show us who we might be-
come, and as peers who help us progress by shar-
ing our path. Researchers have also warned about 
a “loneliness epidemic” hitting the workplace, for 
which independent workers can certainly be at 
even greater risk.
But those we interviewed are keenly aware of 
the dangers of social isolation and strive to avoid 
it. Though many are ambivalent about formal 
peer groups, which they often see as insipid 
People in the gig economy must pursue 
a different kind of success—one that comes 
from finding a balance between predictability 
and possibility, between viability and vitality.
FALL 2019 | HBR Special Issue 105
HBR.ORG
a traditional workplace. Martha, the consultant 
who compared herself to a trapeze artist, recalled 
that she became “much more successful profes-
sionally” and “much more comfortable in my 
identity personally” when a trusted counselor 
helped her reframe—and own—her struggle, 
rather than seek ways to evade it. “She helped 
me understand that I could think of myself, 
which I now do, as a pioneer. I don’t fit in any 
categories that exist in organizations, and it’s 
more effective for me to be independent.” Seen 
this way, discomfort and uncertainty were not 
just tolerable but affirming—signs that she 
was just where she needed to be. 
When we spoke, she portrayed employment 
as no longer an anchor she missed but a shackle 
she’d been fortunate enough to break. “I don’t 
know that I would frame [my new life] as pre-
cariousness anymore,” she concluded. “I would 
frame it as really living.” 
HBR Reprint R1802M
Gianpiero Petriglieri is an associate professor of 
organizational behavior at INSEAD. Susan Ashford is 
the Michael & Susan Jandernoa Professor of Manage-
ment and Organizations at the University of Michigan. 
Amy Wrzesniewski is the Michael H. Jordan Professor 
of Management at Yale University. 
substitutes for collegiality, all reported having 
people they turn to for reassurance and encour-
agement. Sometimes these are direct role models 
or supportive collaborators; in other cases they’re 
family members, friends, or contacts in similar 
fields, who can’t always offer specific work advice 
but nevertheless help our study participants push 
through challenging times and embolden them to 
take the risks their work entails. 
Matthew, for example, noted that reaching 
out to people in his inner circle helps calm his 
anxiety: “If I were just left on my own, I could sit 
here in the office and go down a rat hole. You’re 
left to your own inner voice, and it spirals down 
into ruminating.” Karla told us that she, too, 
regularly turns to a handful of peers with whom 
she’s close. “All the work I do in the independent 
economy comes through these connections,” she 
said. But their help goes well beyond referrals. 
“My ability to process, develop, and grow as a hu-
man being and understand who I am in the work 
I’m doing comes from the conversations that 
I have with these folks,” she explained. “These 
people are how I know what I’m supposed to 
be doing.” 
Redefining Success
In popular management tales, career success usu-
ally comes with security and equanimity. For in-
dependent workers, however, both are ultimately 
elusive. And yet most of those we studied told us 
they feel successful. 
Our conclusion is that people in the gig econ-
omy must pursue a different kind of success— 
one that comes from finding a balance between 
predictability and possibility, between viability 
(the promise of continued work) and vitality (feel-
ing present, authentic, and alive in one’s work). 
Those we interviewed do so by building holding 
environments around place, routines, purpose, 
and people, which help them sustain productiv-
ity, endure their anxieties, and even turn those 
feelings into sources of creativity and growth. 
“There’s a sense of confidence that comes from 
a career as a self-employed person,” one consul-
tant told us. “You can feel that no matter how bad 
it gets, I can overcome this. I can change it. I can 
operate more from a place of choice as opposed 
to a place of need.”
Many we spoke to believe they wouldn’t be 
able to find the same mental space or strength in 
106 HBR Special Issue | FALL 2019
growing economy that’s offering 
more full-time employment, 
but it also shows a generation 
that may want the same thing as 
their parents: a steady job with 
a clear advancement track and 
benefits such as health insur-
ance and paid time off.
We’re all going to be giggers. 
The size of the gig economy and 
how fast it’s growing also seem 
to be overimagined at times. 
The measurements can vary a 
lot, and so can the predictions 
for how much it may expand. 
Back in 2013 a much-touted 
survey suggested that by 2020—
just over a year from now—a 
whopping 40% of the workforce 
would be so-called contingent 
workers, including contractors, 
temps, and the self-employed. 
But here are the facts: The best 
estimates,according to the 
Gig Economy Data Hub, a joint 
project of Cornell University’s 
Institute of Labor Relations 
and the Aspen Institute, put 
the percentage at around 30%. 
That’s a lot, and it’s growing. 
But don’t think the world as you 
know it is completely disappear-
ing. Only about 10% of workers 
rely on gig arrangements for 
their full-time jobs. And on-
demand services, where you get 
constant gigs from an app like 
Lyft or Task Rabbit, represent 
an even smaller percentage of 
gig workers. In fact, less than 
1% of workers have used online 
platforms to arrange work in 
the past month. Most workers 
are still grabbing extra hours 
the old-fashioned way—tend-
ing bar or doing temp work on N
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Quick Takes
Myths of the 
Gig Economy, 
Corrected
by David Jolley 
Gig work is growing, 
but not as much as you 
might think.
UNDERSTANDING THE GIG ECONOMY
employ this approach through 
my work at EY supporting cre-
ative, successful start-ups.
But there are a lot of myths 
about gig work, whether full-
time or part-time. Gig work is 
growing, but not as much as 
you might think, and in ways 
that may be very different from 
what you imagine. It might 
even be better for older execu-
tives than recent grads. Here are 
a few myths worth dispelling.
Millennials love to gig. There 
is a common perception that 
somehow the Millennial genera-
tion (those born between 1981 
and 1996) just loves part-time 
gig employment. But a recent 
study by EY found a more 
complicated picture: 60% of Mil-
lennials were not involved in the 
gig economy at all, and only 24% 
report earning money from it. In 
fact, the percentage of Millenni-
als with full-time careers is rising 
at a brisk clip from 45% in 2016 
to 66% in 2018, according to the 
data we collected. That reflects a 
EVERY DAY there are news 
stories about the so-called gig 
economy where workers con-
tribute part- or full-time labor—
not as employees with benefits 
but as independent contractors. 
Dara Khosrowshahi, CEO of the 
ride-sharing giant Uber, proudly 
declared last year that “very 
few brands become verbs.” The 
same week Upwork, a platform 
for hiring freelancers, filed for 
an IPO, as did Fiverr, which 
boasts that it offers a “freelance 
services marketplace for the 
lean entrepreneur.” In fact, 
the gig economy has not only 
turned millions of Americans 
into contractors but given the 
more successful entrepreneurs 
the tools to grow even faster. A 
fast-moving start-up can secure 
talent as it needs it, outsource 
more-quotidian tasks like pay-
roll, and stay lean and mean; 
indeed, I see entrepreneurs 
HBR.ORG
FALL 2019 | HBR Special Issue 107
THE GIG ECONOMY workforce is 
growing. A Pew Research Center 
survey on the sharing economy 
showed that in 2015, 8% of 
American adults earned money 
from an online employment 
platform across industries such 
as ride hailing, online tasks, 
and cleaning/laundry. These 
gig economy workers are driven 
by a range of motivations, from 
lacking other jobs to wanting 
control over their schedule 
to seeking social connection. 
But there are big differences 
separating those who are more 
financially reliant on gig work 
(56% of workers surveyed) and 
“casual” gig workers (42%), 
who report that they could live 
Kraft, and Mastercard. Miller 
says that her stable of top talent 
wants “to be able to choose who 
we work with and what we work 
on.” This lines up with EY’s re-
cent findings. On a global basis, 
according to our 2018 Growth 
Barometer, a lack of skilled 
talent is a bigger headache for 
U.S. companies than for those 
in other countries, with 25% of 
U.S. survey respondents citing 
this as a challenge to growth 
compared with 10% of their 
counterparts elsewhere. With 
U.S. unemployment at a historic 
40-year low, there just aren’t the 
numbers of suitably qualified 
people in the talent pool to hire.
Lisa Hufford, a consultant 
and the author of Navigating 
the Talent Shift: How to Build 
On-Demand Teams That Drive 
Innovation, Control Costs, and 
Get Results (Palgrave Macmil-
lan, 2016), has worked with gig 
talent for years. She’s seeing 
firsthand that while the gig 
economy isn’t the answer to all 
problems, it can help start-ups 
meet their talent needs at lower 
costs and help mature compa-
nies grow. It can also be a sur-
prising boon to Baby Boomers 
and Generation Xers. “We were 
raised at a time when there 
weren’t a lot of options, and 
now there are so many choices,” 
says Hufford, a member of 
Generation X. “For people who 
didn’t grow up that way, it can 
feel overwhelming. I like to help 
people navigate that shift. They 
realize they have a lot of skills 
that companies want and a lot 
of options. It’s kind of cool.”
Originally published on HBR.org 
October 30, 2018
HBR Reprint H04MNG
David Jolley is the EY Americas Growth 
Markets leader.
the side—not by being digitally 
summoned.
Gig work is better. In our 
2018 EY Growth Barometer, an 
annual global survey of middle 
market company leaders, we 
found some movement away 
from part-time and gig hiring. 
Most companies are still com-
mitted to full-time hires for all 
the advantages that bestows—
loyalty, retained knowledge, 
institutional memory, stealing 
top talent from the competi-
tion. In many cases, you have 
jobs in which the worker is 
integral to a team or needs to 
be supervised. That’s why so 
many entrepreneurs use the gig 
economy where they can but 
also have a deep and abiding 
interest in hiring great full-time 
talent. Gig-based businesses 
can’t transmit “a culture” in a 
traditional sense. “You have in-
dividuals doing things you have 
no supervision of, other than 
the work itself,” says D. Quinn 
Mills, the Albert J. Weather-
head, Jr. Professor of Business 
Administration Emeritus at 
Harvard Business School. Mills 
notes that while the gig econ-
omy can benefit companies and 
will most likely expand, it’s not 
for every business.
Gig work is unfulfilling. The 
perception is that gig jobs are 
dead-end jobs. Not true. Con-
sider Jody Greenstone Miller, 
who has had a stunning career 
in places ranging from the 
White House to The Walt Disney 
Company. The Los Angeles 
lawyer– turned– entrepreneur 
is the cofounder and CEO of 
Business Talent Group, which 
pairs high-end talent with 
high-end expertise in areas 
such as finance, operations, 
and mergers and acquisitions 
at companies including Pfizer, 
comfortably without the ad-
ditional income. While gig work 
is a necessity for some, it is a 
luxury for others.
This bifurcation has been 
apparent in my own research. 
For more than two years, I’ve 
been doing qualitative research 
on Uber and Lyft drivers. I first 
examined, with my coauthor 
Luke Stark, how Uber uses auto-
mated mechanisms to manage 
drivers. More recently, I inter-
viewed 85 Uber and Lyft drivers 
across the U.S. and Canada to 
see how their work varies across 
regions. I’ve also found that the 
ride-hail workforce spans many 
different types of drivers—from 
full-time earners to part-time 
What Motivates 
Gig Economy Workers
by Alex Rosenblat
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UNDERSTANDING THE GIG ECONOMY QUICK TAKES
Although no one likes a pay cut, 
they aren’t as invested in their 
work conditions as those who 
make their living driving. Hob-
byists like Nathan, who con-
tinue to drive despite declining 
earnings, represent an influx of 
workers who are motivated in 
part by nonfinancial values and 
are usually better positioned 
to absorb pay cuts. This may 
contribute to income destabili-
zation for occupational drivers.
What Motivates Full-Time 
Ride-Hail Drivers
A minority of ride-hail drivers 
work full-time, and for driv-
ers who have made significant 
investments in this job, the 
precarity of their employ-
ment can cause a lot of strain. 
Another driver I talked to, 
Fernando, who drives for uberX 
and uberXL in the Boston area 
to supporthis family, reflected 
on a pattern that is common 
to drivers: They’re initially 
optimistic and satisfied with 
their work, particularly in the 
early stages of the company’s 
growth in their city, but they 
become distrustful of it over 
time. In addition to the flood 
of new drivers in his market 
and lower compensation (he 
noted that his take-home pay 
from airport trips had fallen, 
for example), he was also upset 
about Uber shifting its eligibil-
ity requirements for cars—in 
2014 he spent $42,000 on an 
Uber-eligible car (which meant 
a 2005 or newer model), but 
in February 2015, Uber began 
allowing models dating to 2001. 
“You know how many people 
went to the dealer and bought 
new cars?” he asks.
Another driver I talked to, 
Raj, has been driving profes-
sionally in Toronto for nine 
My research suggests that 
they benefit most clearly from 
Uber’s employment model of 
independent contract labor, as 
they gain more opportunities 
for marginal employment and 
are less vulnerable to the same 
business practices (for example, 
rate cuts) that prompt strikes 
and protests from drivers who 
rely on Uber as a primary source 
of their household income.
For example, one driver I 
interviewed, Nathan*, is in 
his late 60s and works as a 
licensed psychotherapist in Los 
Angeles. On weekends when 
he’s not working, he drives six 
to 12 hours for Lyft. Although 
the money is a plus, he mainly 
drives for social reasons and to 
escape from the emotionally 
taxing demands of dealing with 
patients. Nathan earns about 
$130 an hour as a psychothera-
pist, and he initially made $34 
an hour driving for Lyft, with 
incentive pay, though this has 
dropped over the four months 
he’s been driving to $15 to $20 
an hour. Yet he told me, “If I 
didn’t like going out to do it, I’d 
probably stop.”
In January 2016, Uber cut 
rates for drivers in more than 
100 cities in the U.S. and Can-
ada, and Lyft followed suit in 
33 cities. For drivers who need 
the money, these cuts can be 
hard to absorb. Rate cuts have 
sparked protests, strikes, and 
efforts to organize from Uber 
drivers in New York, Dallas, 
Seattle, and elsewhere. Driver 
discontent around rate cuts is 
widespread in forums.
But while labor activism has 
gained momentum on the backs 
of frustrated ride-hail drivers, 
the experiences of hobbyists 
and other part-time earners in 
the workforce create an issue: 
largely of part-time workers, 
employers like Uber have more 
flexibility to adjust wages and 
working conditions—but it’s 
their most dedicated workers 
who are affected most. The 
availability of part-time earners 
reduces pressure on employ-
ers to create more-sustainable 
earning opportunities. The 
workers who hope to make a 
living in ride-hail work take on 
the most risk.
This comes at a cost, how-
ever. Turnover is high—one in 
six online platform workers is 
new in any given month, and 
more than half of participants 
quit within a year. To continue 
attracting new workers, com-
panies like Uber and Lyft have 
to do a better job of engaging 
existing ones by recognizing 
and meeting their different 
motivations and needs.
What Motivates Part-Time 
Ride-Hail Drivers
One of the promises of the gig 
economy is that workers have 
more flexibility to work when 
and as much as they want. 
That’s why many people start 
driving to earn extra income 
outside their day jobs or in their 
free time. Hobbyists represent 
an illustrative segment of part-
time drivers in the ride-hail 
workforce. These supplemental 
earners are retirees, work-
ing professionals, and empty 
nesters. Their primary motiva-
tion to work is often social. 
workers and “hobbyists”—
who drive for many different 
reasons. And I’ve seen that not 
everyone benefits from this 
work equally.
In the U.S., Uber has 600,000 
active drivers and Lyft has 
315,000 (though both com-
panies may define “active” 
differently, many drivers work 
for both, and turnover is very 
high). But research has found 
that most of these drivers work 
part-time. For example, an 
analysis by Jonathan Hall at 
Uber and Princeton economist 
Alan Krueger found that 51% 
of Uber drivers work one to 15 
hours per week, and 30% work 
16 to 34 hours per week—while 
12% work 35 to 49 hours per 
week, and 7% work more than 
50 hours per week. Similarly, a 
survey of subscribers to Harry 
Campbell’s popular blog for 
ride-share drivers found that 
Uber drivers who work 20 
hours or less per week (nearly 
half of them) accounted for 
about 24% of Uber’s services 
and hours worked. And accord-
ing to Lyft, 78% of their drivers 
work one to 15 hours per week, 
and 86% of them are either em-
ployed full-time elsewhere or 
seeking full-time employment. 
Other reports have found that 
most independent workers (in 
the U.S. and Europe) don’t rely 
on platforms like Uber for their 
primary source of income.
As UCLA law professor Noah 
Zatz has observed, “A small 
proportion of drivers are doing 
most of Uber’s work.” This 
creates a tension between a mi-
nority of full-time drivers and 
a majority of drivers who work 
part-time, earn supplemental 
income, or drive for social 
reasons. Because the supply of 
gig labor is liquid and composed 
While gig work is a 
necessity for some, 
it is a luxury for others.
HBR.ORG
FALL 2019 | HBR Special Issue 109
But one important and 
growing population in organiza-
tions isn’t benefiting from this 
feedback renaissance. They’re 
the external professionals 
your organization increasingly 
counts on: freelancers, gigsters, 
advisers, and consultants, the 
people we call agile talent in 
our new book. In our research, 
performance management is 
the weakest link in managing 
WE SEE BIG changes ahead in 
performance management. 
Organizations like GE and 
Accenture are experimenting 
with new approaches to that old 
shibboleth: the annual perfor-
mance review. And far-thinking 
companies are replacing the an-
nual rating and ranking process 
with more-timely capture of 
critical incidents and authentic 
spot feedback.
dom, an employment tribunal 
recently ruled that two Uber 
drivers must receive employee 
benefits, including the national 
living wage. Uber plans to ap-
peal that ruling.)
For companies seeking to 
replicate Uber’s success, it’s 
important to understand that 
high attrition rates may not be 
a feasible long-term strategy—
the flood of part-time workers 
could always dry up. Many driv-
ers, both full- and part-timers, 
already strategize to maximize 
their incomes by switching 
between multiple platforms 
that offer different incentives or 
premiums. Uber, Lyft, and other 
app-based employers stand to 
gain from retaining dedicated 
users, or “power drivers,” who 
may be willing to work under 
more-strenuous conditions 
than social or supplementary 
earners. Platforms should seek 
to understand their diverse 
workforces and offer distinct 
employment promises that 
speak to their varied motiva-
tions and needs.
* Names have been changed to preserve 
driver anonymity.
Originally published on HBR.org 
November 17, 2016
HBR Reprint H03A10
Alex Rosenblat is the author of Uber-
land: How Algorithms Are Rewriting the 
Rules of Work (University of California 
Press, 2018). She is also a technology 
ethnographer and works as a research 
lead at the Data and Society Research 
Institute. 
years, first as a taxi driver, 
then as the owner of a for-hire 
vehicle business, and now for 
UberSelect. He admires Uber’s 
technology, but he sees the 
influx of nonoccupational driv-
ers as a threat to his livelihood: 
“Competition is always good for 
everyone, but again, it should 
be reasonable, not that you just 
flood the market.” With the 
advent of Uber, he’s become 
anxious about the stability of 
his income as a professional 
driver and is looking to change 
careers. He keeps textbooks 
under the front passenger seat 
so that he can study to become 
a mortgage broker in between 
rides.
For others, driving offers a 
solution to a lack of other jobopportunities, especially for 
those with a criminal record or 
limited education. Cody, who 
is in his mid-20s, is a Lyft driver 
in the Ann Arbor and Detroit, 
Michigan, area. He told me that 
he’s not eligible for good jobs 
with only a high school educa-
tion: “There’s not a lot of jobs 
unless you’re looking at work-
ing in a factory for 80 hours a 
week.” The Pew survey found 
that one in five respondents 
said they used these digital 
platforms because job opportu-
nities in their area were limited.
In sum, the effects of the gig 
economy on the workforce are 
mixed. These platforms seem 
to most benefit people earning 
supplementary income or those 
lacking other job opportunities, 
while they impose the most 
risk on full-time earners. And 
Uber and Lyft are still facing 
legal challenges in the U.S. for 
classifying drivers as indepen-
dent contractors rather than 
employees who can receive 
benefits. (In the United King-
Performance 
Management in 
the Gig Economy
by Jon Younger and Norm Smallwood
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110 HBR Special Issue | FALL 2019
UNDERSTANDING THE GIG ECONOMY QUICK TAKES
in the HR/talent tech space. He was pre-
viously a partner of the RBL Group and 
senior vice president of human resources 
of a top-five U.S. bank. Younger is the 
coauthor of several books in talent man-
agement and HR, including Agile Talent: 
How to Source and Manage Outside 
Experts (Harvard Business Review Press, 
2016). Norm Smallwood is a cofounder 
of the RBL Group, a strategic HR and 
leadership systems advisory firm, 
and a coauthor of several books, 
including Agile Talent: How to Source 
and Manage Outside Experts: How to 
Source and Manage Outside Experts 
(Harvard Business Review Press, 2016).
agile talent and their work? 
We heard time and again from 
external experts about the 
importance of both a perfor-
mance and a developmental 
mindset. Managers who are 
performance oriented but 
not development oriented 
may assess well but not pro-
vide effective feedback and 
coaching. Managers who focus 
on development more than 
performance may miss when it 
comes to frank, tough assess-
ments. Good managers of agile 
talent—just like good managers 
of full-timers—do both.
Acknowledge excellence 
and share the news. Agile 
talent is just as motivated by 
appreciation and recognition as 
your full-time employees are—
more so, in fact, given that cli-
ent satisfaction is the basis for 
their career success. Whether 
through something as simple as 
public praise or as personal 
as sending a dozen flowers and 
a handwritten letter, reinforce 
with acknowledgment and 
thanks. And let colleagues 
know.
Agile talent is growing and 
here to stay, and organizational 
leaders are increasingly turning 
to external experts to provide 
the speed, flexibility, and in-
novation they need and to more 
cost-effectively plan initiatives. 
But organizations will gain the 
full benefits they seek only if 
they recognize that their agile 
talent needs strong perfor-
mance management support, 
too. 
Originally published on HBR.org 
January 11, 2016
HBR Reprint H02LPB
Jon Younger is the founder of the Agile 
Talent Collaborative, a nonprofit research 
organization, and an investor and adviser 
that both agile talent and their 
client organizations miss critical 
opportunities to provide a thor-
ough orientation to the work 
and its importance.
Measure more than cost, 
schedule, and quality. Defin-
ing the usual measures isn’t 
enough. Agile talent wants to 
know the nuances, and they’re 
particularly concerned that 
issues like cultural fit or other 
“soft” factors are often left 
unsaid or undefined until prob-
lems arise, creating additional 
cost or difficulty and enabling 
preventable conflict with inter-
nal colleagues.
Encourage agile talent to 
communicate concerns before 
problems bloom. To resolve 
problems before they affect a 
project, organizational lead-
ers must sincerely encourage 
agile talent to communicate 
concerns. Our interviews rein-
force the importance of regular 
review and a well-defined 
agenda for review. Rapport, the 
secret sauce of open discussion, 
blooms when agile talent is 
regularly invited and expected 
to honestly discuss potential 
problems.
Demonstrate two-way 
feedback. But encourage-
ment isn’t enough. When we 
ask agile talent whether their 
client organizations really want 
feedback, we often see more 
teeth gnashing than affirma-
tion. We learned that boundar-
ies are important in two-way 
feedback—for example, “We 
talk about issues, not individu-
als,” or what some people call 
the “no gossip” rule.
Make sure the right manag-
ers are supervising your agile 
talent. Is your organization 
assigning the right profession-
als and managers to supervise 
and engaging agile talent and in 
gaining the greatest productiv-
ity from your external talent 
investment.
According to Deloitte, exter-
nal workers may represent 30% 
or more of your organization’s 
true workforce. Freelancers 
Union reports that as much 
as 40% of the U.S. workforce 
views themselves as freelanc-
ers. And our research found that 
more than 50% of leaders fully 
expect agile talent to increase as 
a percentage of total employ-
ees. Why? Certainly, one goal 
is cost efficiency. But the more 
important drivers are speed, 
flexibility, and innovation.
Most organizations, however, 
are not set up to benefit from 
their increased investment in 
agile talent. Research by PMI 
describes most problems in 
project performance as being 
the result of alignment issues. 
Our findings concur. And 
the alignment gap is greatest 
when it comes to performance 
management.
What can we do to close the 
performance alignment gap? 
Our research suggests six 
important steps:
Share context. Too often 
agile talent reports that they 
are excluded from critical 
meetings and discussions that 
would provide helpful—and 
sometimes essential—context 
for their work. Our data shows 
Rapport blooms when 
agile talent is expected 
to honestly discuss 
potential problems.
The world will 
always need the 
digital global 
mindset you gain 
at Thunderbird.
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TODAY’S TALENT 
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112 HBR Special Issue | FALL 2019
10 | HR Goes Agile 
Peter Cappelli and Anna Tavis
Companies’ core businesses and functions have 
largely replaced long-range planning models with 
methods that let them adapt and innovate more 
quickly, and to support that, HR departments are 
starting to go “agile lite”—adopting the general prin-
ciples but not all the protocols from the tech world.
In this article Wharton’s Peter Cappelli and NYU’s 
Anna Tavis discuss the profound changes compa-
nies are making in six critical areas. Annual per-
formance appraisals are often the fi rst traditional 
practice to go. As employees work on shorter-term 
projects, run by diff erent leaders and organized 
around teams, companies are recognizing that 
workers need more-immediate, ongoing feedback 
so that they can “course-correct” mistakes, im-
prove performance, and learn through iteration.
Coaching is another key item: getting managers 
to movefrom judging employees to helping them 
develop. Teams, rather than individuals, are the 
focus now that work is increasingly organized 
project by project. Compensation is changing too, 
with a switch to spot bonuses or no bonus but 
more-frequent salary adjustments. Recruiting has 
become faster and nimbler, and new learning and 
development practices help employees identify and 
access the skills and training they need to advance.
HR has not had to change in recent decades 
nearly as much as have the line operations it sup-
ports. But now the pressure is on, and organiza-
tions from IBM to Regeneron Pharmaceuticals to 
the Bank of Montreal are paving the way.
18 | One Bank’s Agile Team 
Experiment
Dominic Barton, Dennis Carey, and Ram Charan
As mobile banking took hold and customers 
became increasingly aware of what they could 
do for themselves, the global banking group ING 
launched a pilot transformation in its Dutch retail 
unit, replacing most of its traditional structure 
with a fl uid and more responsive organization 
composed of tribes, squads, and chapters. Domi-
nic Barton, Dennis Carey, and Ram Charan report 
on this new way of working, which is being rolled 
out more widely across the bank.
HBR Reprint R1802B
Executive 
Summaries
SpeciaI
Issue
Build the 
Workforce 
You Need
The Best of HBR
Insights on: 
Better People Analytics, 
Desirable Benefits, 
Adapting Your 
Workforce, 
and More!
How to Hire the 
Right People and 
Keep Them 
Engaged
“Hiring talent remains the 
number one concern of CEOs 
in the most recent Conference 
Board Annual Survey; it’s also 
the top concern of the entire 
executive suite.”
YOUR APPROACH TO HIRING 
IS ALL WRONG 
PAGE 50
114 HBR Special Issue | FALL 2019
40 | “Numbers Take Us 
Only So Far”
Maxine Williams
Though executives tend to think—and want to 
believe—they’re hiring and promoting fairly, bias 
still creeps into their decisions. They often use 
ambiguous criteria to filter out people who aren’t 
like them or deem people from minority groups to 
be “not the right cultural fit,” leaving those em-
ployees with the uneasy feeling that their identity 
might be the real issue. 
Companies need to acknowledge that it’s fair 
for employees from underrepresented groups to 
be suspicious about bias, says Williams, Face-
book’s global director of diversity. They also must 
find ways to give those workers more support. To 
that end, many organizations are turning to people 
analytics, which aspires to replace gut decisions 
with data-driven ones. Unfortunately, firms often 
say that they don’t have enough people from 
marginalized groups in their data sets to produce 
reliable insights. 
But there are things employers can do to 
supplement small n’s: draw on industry or sector 
data; learn from what’s happening in other com-
panies; and deeply examine the experiences of 
individuals who work for them, talking with them 
to gather critical qualitative information. If firms 
are systematic and comprehensive in these ef-
forts, they’ll have a better chance of improving 
diversity and inclusion.
HBR Reprint R1706L
22 | Reinventing 
Performance Management
Marcus Buckingham and Ashley Goodall 
Like many other companies, Deloitte realized that 
its system for evaluating the work of employees—
and then training them, promoting them, and pay-
ing them accordingly—was increasingly out of step 
with its objectives. It searched for something nim-
bler, real-time, and more individualized—some-
thing squarely focused on fueling performance in 
the future rather than assessing it in the past. The 
new system will have no cascading objectives, no 
once-a-year reviews, and no 360-degree-feedback 
tools. Its hallmarks are speed, agility, one-size-
fits-one, and constant learning, all underpinned by 
a new way of collecting reliable performance data.
To arrive at this design, Deloitte drew on three 
pieces of evidence: a simple counting of hours, a 
review of research in the science of ratings, and 
a carefully controlled study of its own organiza-
tion. It discovered that the organization was 
spending close to 2 million hours a year on per-
formance management, and that “idiosyncratic 
rater effects” led to ratings that revealed more 
about team leaders than about the people they 
were rating. From an empirical study of its own 
high-performing teams, the company learned that 
three items correlated best with high performance 
for a team: “My coworkers are committed to do-
ing quality work,” “The mission of our company 
inspires me,” and “I have the chance to use my 
strengths every day.” Of these, the third was the 
most powerful across the organization. 
With all this evidence in hand, the company 
set about designing a radical new performance 
management system, which the authors describe 
in this article.
HBR Reprint R1504B
30 | Better People Analytics
Paul Leonardi and Noshir Contractor
Lately, people analytics—using statistical insights 
from employee data to manage talent—has gotten 
a lot of hype and even won mainstream accep-
tance. Yet most firms lack an understanding of 
which talent dimensions drive performance in 
their organizations. Why? Their analytics examine 
only the attributes of employees, when people’s 
interactions are equally, if not more, telling. 
Research shows that a lot of employees’ 
success can be explained by their relationships—
something that’s the focus of a new discipline, 
relational analytics. The key is finding “structural 
signatures”: patterns in social networks that pre-
dict who will have good ideas, which employees 
have the most influence (it’s not senior leaders), 
which teams will be efficient, which will innovate 
best, where silos exist, and which employees firms 
can’t afford to lose.
This article describes what indicators to watch 
for and how most firms already have the raw 
material they need to build relational analytics 
models: the “digital exhaust” from their internal 
communications.
HBR Reprint R1806E
58 | Navigating Talent 
Hot Spots
William Kerr
Innovation clusters like San Francisco and Boston 
have long had an outsize impact on the global 
economy, and their infl uence keeps growing. In 
2017, for instance, America’s 10 largest tech hubs 
accounted for 58% of U.S. patents. Globally, cities 
such as Tokyo, Paris, Beijing, Shenzhen, and Seoul 
produced a similar proportion. The increased 
geographic concentration of innovation activity 
poses a challenge for fi rms based in suburban 
industrial parks. To stay relevant, they need to 
tap into urban hotbeds, but setting up operations 
there can be extremely expensive. 
In his work on global talent fl ows, Harvard 
Business School’s Kerr has seen organizations try 
three solutions: At one extreme, they can relocate 
their headquarters to a hub, as GE recently did 
(but make them much smaller). A less expensive 
strategy is to create an innovation lab or corporate 
outpost in a talent cluster, as Walmart did with 
Walmart Labs. The most conservative strategy is 
to run executive retreats and immersions in talent 
clusters—a tactic Vodafone uses eff ectively.
These three options aren’t mutually exclusive. 
Given the need to stay in touch with multiple clus-
ters, companies may want to try them all. Each 
one involves substantial risks that executives must 
manage. But together they off er a good playbook 
to fi rms that are fi nding themselves outside the 
action as the clout of a handful of cities grows. 
HBR Reprint R1805E
50 | Your Approach to 
Hiring Is All Wrong
Peter Cappelli
Businesses have never done as much hiring as 
they do today and have never done a worse job 
of it, says Peter Cappelli of Wharton. Much of 
the process is outsourced to companies such as 
Randstad, Manpower, and Adecco, which in turn 
use subcontractors to scour LinkedIn and social 
media for potential candidates. When applica-
tions come—always electronically—software sifts 
through them for key words that hiring managers 
want to see. Vendors