ONUS ARTICLE
“ Profits Without Prosperity”
The McKinsey Award Winner
By William Lazonick
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Find more digital content or join the discussion on ww w.h b r.o rgContents
Editors’ Note
vii
Reinventing Performance Management
by Marcus Buckingham and Ashley Goodall
The Transparency Trap
by Ethan Bernstein
1
15
Profi ts Without Prosperity
by William Lazonick
29
Outsmart Your Own Biases 47
by Jack B. Soll, Katherine L. Milkman, and John W. Payne
The 3-D Printing Revolution
by Richard D’Aveni
61
Why Strategy Execution Unravels—and What to Do About It
by Donald Sull, Rebecca Homkes, and Charles Sull
The Authenticity Paradox
by Herminia Ibarra
75
89
The Discipline of Business Experimentation
by Stefan Thomke and Jim Manzi
When Senior Managers Won’t Collaborate
by Heidi K. Gardner
103
121
Workspaces That Move People 139
by Ben Waber, Jennifer Magnolfi , and Greg Lindsay
Digital Ubiquity: How Connections, Sensors, and
Data Are Revolutionizing Business 153
by Marco Iansiti and Karim R. Lakhani
About the Contributors
Index
171
175
vEditors’ Note
As our editorial team read through the past year’s worth of Harvard
Business Review to select the articles for this volume, perhaps the
most interesting part of the proceeding was seeing how a group of
seemingly disparate articles actually overlapped and wove together.
Of course some themes were the result of deliberate eff ort; but ac-
cidental commonalities and contrasts perhaps even better represent
the interests of our authors and our readers. This year we saw orga-
nizations focused on their physical spaces, and we’ve included two
articles from our issue on workplaces. But one of them, tellingly, also
addresses the issue of privacy in the virtual world, which dovetails
with questions raised by the growing internet of things and its atten-
dant business models. That interplay of digital and physical worlds
(not to mention innovative business models) is also embodied in the
rise of 3-D printing. Among the other themes that emerged were bet-
ter collaboration through the breaking down of physical walls and
organizational silos (But how much of this openness is too much?);
the balance between intuition and rationality; and the (im)balance
between corporate profi t and human prosperity.
This volume begins by focusing on the critical (if more prosaic)
process of assessing performance. In “Reinventing Performance
Management,” Marcus Buckingham and Ashley Goodall describe
how Deloitte overhauled its performance management system. In
a public survey the company conducted, more than half the execu-
tive participants indicated that their current method of evaluating
employees’ work neither drove employee engagement nor encour-
aged high performance: It depended too much on past results and
off ered no practical look into the future. In the new model, rather
than asking for their impressions of a particular individual, the
performance system asks managers what they would do with the
employee to recognize, capture, and fuel performance—bringing
agility and constant learning into the center of the organization’s
culture.
In “The Transparency Trap,” the Harvard Business School pro-
fessor Ethan Bernstein takes up the question of performance as
well, examining how openness—both in a physical context and
through the use of technology and social platforms—can aff ect a
viiEDITORS’ NOTE
team’s creativity and productivity. Companies are increasingly
using open environments to encourage idea sharing and account-
ability. But Bernstein’s research shows that too much transparency
can stifl e experimental behaviors that might benefi t the enterprise.
Privacy, he fi nds, is just as essential as transparency for high per-
formance. Bernstein goes on to suggest four types of boundaries to
establish zones for private work within transparent organizations.
Shifting away from the individual worker, our next piece fo-
cuses on the corporation and how its performance aff ects the U.S.
economy. In his McKinsey Award–winning call to action, “Profi ts
Without Prosperity,” William Lazonick, an economics professor
at the University of Massachusetts Lowell and a codirector of its
Center for Industrial Competitiveness, studies the reasons behind
the increasing underpayment—and unemployment—of American
workers, despite a booming stock market. Lazonick corrals remark-
able research to suggest that executives are using massive stock
buybacks to manipulate share prices and boost their own alloca-
tion of corporate profi ts. Rather than contribute further to execu-
tive compensation, he argues, companies should reinvest profi ts in
their people for future growth.
On the level of individual managerial skills, “Outsmart Your Own
Biases” describes some of the toughest traps leaders fall into as they
make hard choices—tunnel vision about future scenarios, about ob-
jectives, and about options—and encourages them to broaden their
perspective. A variety of methods, from premortems to joint evalu-
ations, can help us overcome the habits that prevent good decision
making and move beyond gut instinct to deliberate reasoning.
Another prominent theme this year was how technological ad-
vances are changing the way businesses compete. One such ad-
vance is 3-D printing. Many have already discussed the changes this
technology could potentially bring to the manufacturing sector.
But as the Dartmouth strategy professor Richard D’Aveni asserts in
“The 3-D Printing Revolution,” industrial 3-D printing is no longer
just about prototyping or creating trinkets and toys. This transfor-
mative technology is gaining momentum, and any companies that
sell products will be aff ected—from their internal processes to the
viiiEDITORS’ NOTE
competitors they face. D’Aveni’s forward-looking piece considers
the changing landscape and explains how to adjust your company’s
strategy to redesign customer off erings, optimize operations, and
evolve your business model to fi t this new context.
But even when the strategy is right, who’s to say it will be imple-
mented properly? The next piece in our volume views that peren-
nial struggle through a practical lens. In “Why Strategy Execution
Unravels—and What to Do About It,” Donald Sull, Rebecca Homkes,
and Charles Sull bust fi ve myths about strategy execution—includ-
ing what it looks like, who drives it, and why it often fails. (Hint:
Silos are part of the problem.) By understanding what’s behind suc-
cessful execution, leaders can seize opportunities that align with
their strategy, pinpoint where eff orts are stalling, and translate
their ideas into results.
We turn again to individual development with “The Authentic-
ity Paradox.” Authenticity is quickly becoming a key leadership
trait, says the INSEAD professor Herminia Ibarra. But for many,
remaining “authentic” is an excuse for sticking with what’s com-
fortable—which means leaders don’t take the risks necessary for
growth and development. Instead they should experiment: By try-
ing out a new role or temporarily feeling “fake,” they can develop a
personal style that feels right to them and suits the organization’s
changing needs as well.
Experimentation isn’t just for leaders; it’s a core component of
the innovation process for organizations. But many companies
skip rigorous experimentation in favor of intuition, leading (again)
to bad decisions. In “The Discipline of Business Experimenta-
tion,” the authors use examples from Kohl’s, Wawa, and Petco to
show how companies can eff ectively test-drive innovation eff orts
to improve their operations and products. What makes this article
important is not the specifi c questions it asks (although those are
valuable) but that it draws from the authors’ extensive research and
experience to give readers a full understanding of how to try out
ideas in the market while minimizing risk.
Innovation, experimentation—they often rely on diverse per-
spectives and areas of expertise. But what can you do when your
ixEDITORS’ NOTE
best people from various groups and disciplines won’t collabo-
rate? Professional services fi rms often fi nd themselves in just that
situation: Partners are so accustomed to competing with one an-
other that they don’t work together even for the benefi t of a shared
client—or of their company. In “When Senior Managers Won’t Col-
laborate,” Heidi K. Gardner, who studies legal organizations and
other professional services fi rms, explains how one organization
recognized this issue and helped partners with diverse specialties
work together to provide a higher-value combined off ering for cli-
ents, thus growing revenue for the whole fi rm. Though the piece
focuses on professional services, its lessons are applicable to any
organization looking to create a more collaborative culture.
A culture of collaboration is also the focus of “Workspaces That
Move People.” Here the authors urge leaders to create physical
workplaces that encourage face-to-face communication and chance
encounters among employees. On the surface, this may seem to
contradict the zones of privacy suggested in “The Transparency
Trap.” But the authors focus less on visibility and more on sponta-
neity. They suggest making changes to your physical space that pro-
mote informal cross-silo conversation to generate ideas and expand
learning. With small tweaks, such as reducing the number of coff ee
machines, and larger changes, such as increasing the size of break
rooms or establishing easily reconfi gurable spaces, leaders can or-
chestrate the unplanned interactions that lead employees to mingle
and share knowledge—all for greater creativity and productivity.
It’s striking to see how much discussion this year was focused on
in-person interaction and collaboration, since so much of work and
life is now mediated by digital devices. In “Digital Ubiquity: How
Connections, Sensors, and Data Are Revolutionizing Business,”
the Harvard Business School professors Marco Iansiti and Karim
R. Lakhani discuss the competitive landscape created by the inter-
net of things as it connects previously distinct products and ser-
vices. Using GE as a central example, they show how companies can
proactively evolve their business models to stay ahead—and take
advantage—of this digital revolution.
xEDITORS’ NOTE
From disruptive technological advances to new ways of work-
ing together, business is transforming. Some articles we publish
in HBR help leaders prepare for the future by describing the here
and now—by showing how innovative practices can work in real or-
ganizations, for example, or by presenting research that can help
them hone their management skills. Others point more explicitly to
what’s coming. We hope that this volume, in combining both, helps
leaders meet the changing competitive landscape head-on.
—The Editors
xiHBR’S
10
MUST
READS
The defi nitive
management ideas
of the year from
Harvard Business Review.
2016Reinventing Performance
Management
A
by Marcus Buckingham and Ashley Goodall
AT DELOITTE WE’RE REDESIGNING our performance management
system. This may not surprise you. Like many other companies,
we realize that our current process for evaluating the work of our
people—and then training them, promoting them, and paying them
accordingly—is increasingly out of step with our objectives. In a
public survey Deloitte conducted recently, more than half the ex-
ecutives questioned (58%) believe that their current performance
management approach drives neither employee engagement 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 assessing 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 cascad-
ing objectives, no once-a-year reviews, and no 360-degree-feedback
tools. We’ve arrived at a very diff erent and much simpler design for
managing people’s performance. Its hallmarks are speed, agility, one-
size-fi ts-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 evi-
dence: a simple counting of hours, a review of research in the science
of ratings, and a carefully controlled study of our own organization.
1BUCKINGHAM AND GOODALL
Counting and the Case for Change
More than likely, the performance management 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 begin-
ning of the year; after a project is fi nished, each person’s manager
rates him or her on how well those objectives were met. The man-
ager 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 predict-
ability 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
conversations conducted in the moment about actual performance.
But the need for change didn’t crystallize until we decided to
count things. Specifi cally, we tallied the number of hours the organi-
zation was spending 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 talking 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, strategic thinking, it turns out that how much strategic think-
ing I do, or how valuable I think strategic thinking is, or how tough
2Idea in Brief
The Problem
Not just employees but
their managers and even
HR departments are by now
questioning the conventional
wisdom of performance
management, including its common
reliance on cascading objectives,
backward-looking assessments,
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
REINVENTING PERFORMANCE MANAGEMENT
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 separates
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 performance on
course.
a rater I am signifi cantly aff ects 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 percep-
tion. Actual performance 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 tenden-
cies of the rater. Thus ratings reveal more about the rater than they do
about the ratee.” This gave us pause. We wanted to understand perfor-
mance 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 eff ects”?
3BUCKINGHAM AND GOODALL
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 mem-
bers feel that they are called upon to do their best work every day.
This discovery was not based on intuitive judgment 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 eventually 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 mis-
sion and purpose 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 opportunity 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 satisfac-
tion 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
identifi ed 60 high-performing teams, which involved 1,287 employ-
ees and represented 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 sur-
vey. 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 design. We wanted to spend more time
helping our people use their strengths—in teams characterized by
4REINVENTING PERFORMANCE MANAGEMENT
great clarity of purpose and expectations—and we wanted a quick
way to collect reliable and diff erentiated performance data. With
this in mind, we set to work.
Radical Redesign
We began by stating as clearly as we could what performance man-
agement is actually for, at least as far as Deloitte is concerned. We
articulated three objectives for our new system. The fi rst 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 eff ect and the need to streamline our
traditional process of evaluation, project rating, consensus meeting,
and fi nal 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 immedi-
ate team leader—but, critically, to ask a diff erent kind of question.
People may rate other people’s skills inconsistently, but they are
highly consistent when rating their own feelings and intentions. To
see performance at the individual level, then, we will ask team lead-
ers 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 quarter for long-term
projects) we will ask team leaders to respond to four future- focused
statements about each team member. We’ve refi ned the wording
of these statements through successive tests, and we know that at
Deloitte they clearly highlight diff erences among individuals and
reliably measure 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 fi ve-
point scale from “strongly agree” to “strongly disagree” ].
5BUCKINGHAM AND GOODALL
2. Given what I know of this person’s performance, I would
always want him or her on my team [ measures ability to work
well with others on the same fi ve-point scale ].
3. This person is at risk for low performance [ identifi es 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 indi-
vidual. 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 planning, devel-
opment paths, or performance-pattern analysis. Once a quarter the
organization’s leaders can use the new data to review a targeted
subset 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 talking about our people—from ascertaining the facts of perfor-
mance 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 diffi culty of project assignments in a given year and contribu-
tions to the organization other than formal projects. So the data will
serve as the starting point for compensation, not the ending point.
The fi nal 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 resem-
blance, 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.
6REINVENTING PERFORMANCE MANAGEMENT
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 diff erently, although it may be great to be able to measure and
reward the performance 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 expecta-
tions for the upcoming week, review priorities, comment on recent
work, and provide 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 mem-
ber’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 engagement of team
7BUCKINGHAM AND GOODALL
Performance intelligence
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.”
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 two statements: “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.
5.0
People: 1,014
4.0
3.0
2.0
1.0
Level 6
Level 5
Level 4
Level 3
Level 2
Level 1
2.0
3.0
4.0
5.0
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
8REINVENTING PERFORMANCE MANAGEMENT
How would this data help determine pay?
Next the data was fi ltered 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 off ers a starting point for broader discussion.
5.0
People: 343
4.0
3.0
2.0
Level 4
1.0
2.0
3.0
4.0
5.0
(continued)
the guidance and attention they provide—rather than by the team
leader.
To support both people in these conversations, 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 gen-
erate 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 successful
9BUCKINGHAM AND GOODALL
How would it help guide promotions?
This view was fi ltered 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.
5.0
4.0
People: 153
A candidate for
accelerated promotion
But may not be eligible
this year
Tracking toward
promotion
Confirm eligibility
according to time in role,
performance history,
business requirements,
leader support, and
other metrics
3.0
Team leaders’ scores
vary significantly
Investigate performance
discrepancies further
2.0
Level 4
1.0
2.0
3.0
4.0
5.0
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, achieve-
ments, and impact. So 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 defi ned 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
10REINVENTING PERFORMANCE MANAGEMENT
How would it help address low performance?
This view was fi ltered 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.
5.0
People: 35
4.0
A blip in otherwise
high performance
May need clarity on new
responsibilities—address
through coaching
3.0
2.0
1.0
Not performing to
expectations
Work style is disruptive
to the team—start
remediation
2.0
Level 4
3.0
4.0
5.0
performance snapshot, 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: Diff erent
business units can introduce a strengths orientation first, then
more- frequent conversations, then new ways of measuring, and
fi nally new software for monitoring performance. (See the exhibit
“Performance intelligence.”)
But one issue has surfaced again and again during this work,
and that’s the issue of transparency. When an organization knows
11BUCKINGHAM AND GOODALL
How Deloitte Built a Radically Simple
Performance Measure
ONE OF THE MOST IMPORTANT TOOLS in our redesigned performance
management system is the “performance snapshot.” It lets us see perfor-
mance 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 eff ect, 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 confusion, 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 pro-
motion. Those categories may or may not be right for other organizations, but
they work for us.
2. The Rater
We were looking for someone with vivid experience of the individual’s per-
formance and whose subjective judgment 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 func-
tional 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 diffi culty (as revealed by mean responses) and the
something about us, and that knowledge is captured in a number,
we often feel entitled to know it—to know where we stand. We sus-
pect that this issue will need its own radical answer.
In the fi rst version of our design, we kept the results of perfor-
mance 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 sugarcoated. Because we
12REINVENTING PERFORMANCE MANAGEMENT
range of responses (as revealed by standard deviations). We knew that if
they consistently yielded a tight cluster of “strongly agree” responses, we
wouldn’t get the diff erentiation 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 fi nd correla-
tions 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 snapshot 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 evaluation 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 diffi cult conversations. We know that we’ll ag-
gregate 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 sharing
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 context of a group of peers—so that we can give our people the richest pos-
sible view of where they stand. Time will tell how close to that ideal we can get.
wanted to capture unfi ltered assessments, we made the responses
private. We worried that otherwise we might end up destroying 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
13BUCKINGHAM AND GOODALL
percentiles. At work, however, at least when it comes to quantifying
performance, we try to express the infi nite 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 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 performance 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 diff erent: not so much that ratings fail to
convey what the organization knows about each person but that as
presented, 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 dis-
tillation of the truth—and up until now, one might argue, a neces-
sary 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 ver-
sion 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.
Originally published in April 2015. Reprint R1504B
14The Transparency
Trap
T
by Ethan Bernstein
“TRANSPARENCY” is a watchword in management these days, and it’s
easy to understand why. After all, if people conduct their work in
plain view, won’t they be more open and accountable? Won’t they
fl ag and fi x problems more easily, and share information and their
good ideas more freely?
That’s certainly what I expected to discover a few years ago, when
I went in search of empirical evidence that transparency improves
performance in organizations. But through rigorous fi eld research
and experiments, and observations by embedded researchers, I
learned that it’s not that simple. My fi ndings, which complement
various studies on open workspaces, suggest that more-transparent
environments are not always better. Privacy is just as essential for
performance.
Here’s the paradox: For all that transparency does to drive out
wasteful practices and promote collaboration and shared learning,
too much of it can trigger distortions of fact and counterproduc-
tive inhibitions. Unrehearsed, experimental behaviors sometimes
cease altogether. Wide-open workspaces and copious real-time data
on how individuals spend their time can leave employees feeling
exposed and vulnerable. Being observed changes their conduct.
They start going to great lengths to keep what they’re doing under
wraps, even if they have nothing bad to hide. If executives pick up on
15BERNSTEIN
signs of covert activity, they instinctively start to monitor employee
behavior even more intensely. And that just aggravates the problem.
If all this seems vaguely Orwellian, so did some of the activities I
saw in leading companies where intense visibility and tracking were
making things worse, not better. For instance, at one of the world’s
largest mobile phone factories, which is in China and is owned by a
global contract manufacturer, the workers on one line were hiding
process improvements they had made—not just from managers but
from their peers on other lines. Why? Because, as one experienced
worker explained, “it’s most effi cient to hide it now and discuss it
later. Everyone is happy: They see what they expect to see, and we
meet our targets.”
This was not an isolated example. In my research, I found that
individuals and groups routinely wasted signifi cant resources in
an eff ort to conceal benefi cial activities, because they believed that
bosses, peers, and external observers who might see them would
have “no idea” how to “properly understand” them. Even when
everyone involved had only the best of intentions, being observed
distorted behavior instead of improving it.
Some organizations, however, had found the sweet spot between
privacy and transparency, getting the benefi ts of both. They used
four types of boundaries to establish certain zones of privacy within
open environments: They created boundaries around individual
teams—zones of attention—to avoid exposing every little action to
the scrutiny of a crowd. They drew boundaries between feedback
and evaluation—delineating zones of judgment—to avoid politick-
ing and eff orts wasted on managing impressions. They set boundar-
ies between decision rights and improvement rights—establishing
zones of slack—to avoid driving out tinkering. And they put bound-
aries around carefully defi ned periods of experimentation—zones of
time—to avoid both too frequent and too infrequent interruptions.
Across several studies involving diff erent industries, cultures, and
types of work, the companies that had done all this were the ones
that consistently got the most innovative, productive, and thought-
ful work from their employees.
16THE TRANSPARENCY TRAP
Idea in Brief
Problem
To get people to be more creative
and productive, managers increase
transparency with open workspaces
and access to real-time data. But
too much transparency can leave
employees feeling exposed. As a
result, they may actively conceal
what they’re doing—even when
making improvements—reducing
productivity and, paradoxically,
transparency.
Solution
Employees perform better when
they can try out new ideas and
approaches within certain zones of
privacy. Organizations allow them
to do that by drawing four types of
boundaries: around teams of people
(zones of attention), between
feedback and evaluation (zones of
judgment), between decision rights
and improvement rights (zones
of slack), and for set periods of
experimentation (zones of time).
Benefi t
Less-transparent work
environments can yield more-
transparent employees. And by
balancing transparency and privacy,
organizations can encourage just
the right amount of “deviance”
to foster innovative behavior and
boost productivity.
Type 1: Boundaries Around Teams
As social media platforms, wearable devices, and other tools
for transparency become more advanced, our sense of being
“onstage” is growing. And so, in keeping with the sociologist
Erving Goff man’s insights about interpersonal behavior, we spend
more time acting, trying to control others’ impressions and avoid
embarrassment— particularly at work. We cater to our audience,
doing what’s expected.
That was the case at the Chinese mobile phone factory, which had
14,000 workers. When I began studying that work environment, it
seemed like the epitome of transparency: Each fl oor—roughly the
size of a football field, with no walls or other divisions—held as
many as 2,000 workers across shifts.
By embedding into the lines fi ve Chinese-born Harvard under-
graduate researchers—who worked, ate, and lived alongside the
employees, who knew them only as coworkers—I quickly learned
17BERNSTEIN
that the production teams hid a great deal from observers, despite
the open environment. For example, to speed up assembly, work-
ers scanned multiple bar codes into the system at once instead of
scanning each one individually after applying it to a metal shield in
a phone, as standard operating procedure required. And team mem-
bers cross-trained on tasks during downtime—it looked like fooling
around from the outside—so they could cover for one another when
an operator fell behind. There was no ill intent—only a rational cal-
culation about how to be most productive without having to waste
time on explanations.
Such subterfuge is problematic for a host of reasons, though,
ranging from increased risk of compliance-related defects to a lack of
shared learning. To test some basic interventions that might address
it, I set up a few fi eld experiments. On one fl oor, where 32 produc-
tion lines made similar mobile data cards, I randomly selected four
lines on which to experiment, leaving 28 “controls” to work as they
always had.
Because one of the experimental lines was very close to a con-
trol line, engineering put up a curtain between the two. When it
was raised, one of the embedded students overheard a worker say,
“Wouldn’t it be nice if they hung up curtains all around the line, so
we could be completely closed off ? We could be so much more pro-
ductive if they did that.” Curious to see if that would be true, I asked
engineering to fully encircle each experimental line with the equiva-
lent of a hospital bed curtain. Over the next fi ve months, to my sur-
prise, the lines with curtains were 10% to 15% more productive than
the rest, even when I controlled for other infl uences (such as the
Hawthorne eff ect, whereby subjects improve simply in response to
being studied).
By shielding employees from observation, the curtains supported
local problem solving, experimentation, and focus. But within the
curtains work became much more transparent. Partly for that rea-
son, defects remained extremely low, even as throughput rose. And
over time the camaraderie within boundaries made the workers
more likely to share—as a group—their privately worked-out solu-
tions with other lines.
18THE TRANSPARENCY TRAP
Traditionally, people in organizations expect full transparency
within teams but not necessarily beyond them. Team boundaries can
allow for productive, selective opacities within starkly transparent
environments—as was clear at Valve Software, a top PC game devel-
oper I studied with Francesca Gino and Bradley Staats. Valve’s 400-
plus employees are allowed to allocate 100% of their time to projects
they feel are valuable to customers. When they collaborate on new
products or features, they form teams called cabals and move their
desks (which are set on wheels) together into clusters. The offi ce lay-
out is so fl uid, with some individuals rolling their desks to diff erent
cabals multiple times a week, that Valve even has an internal appli-
cation to track desk location.
Valve’s cabals choose their own workspaces, creating privacy by
positioning themselves at a distance from others. Though transpar-
ency is high within them, it’s moderate at best across the company
because of the physical separation and Valve’s distaste for manage-
rial oversight. (No one has the role of keeping tabs on the cabals or
shuttling information back and forth.) This gives the cabals more
freedom to investigate ideas.
When one employee started a cabal to explore how Valve could
get into hardware, the team was initially tiny. Had it immediately
tried to rally the support of the entire organization of software engi-
neers, the hardware concept might have been dead on arrival—it’s
hard to persuade lots of people at once to embrace anything new,
even at Valve. But acquiring a few followers with whom to experi-
ment and create prototypes was doable. Gradually, the hardware
cabal accreted people and resources, gaining scale and momentum.
To recruit more people to join it, early members eventually had to
tell others what they were up to. In other words, they increased their
transparency outside the group—but in their own way and when
they were ready.
Is Valve providing an innovative, productive work environment?
Its success suggests that it is. In its 18-year existence, Valve has pro-
duced a large share of top PC games. According to its founder, Valve
has grown sales by more than 50% every year and brought in more
revenue per employee than Apple or Microsoft. Its game platform
19BERNSTEIN
consumes more bandwidth than most countries do. The cabals help
the company compete in a market where creativity and rapid proto-
type and launch capabilities are critical.
Though Valve is an extreme case (and its success is a product
of many factors), other firms are similarly fostering innovation
and productivity by allowing privacy within team boundaries. For
instance, Google doesn’t track when and where its engineers spend
the 20% of their time that they devote to projects that interest them
personally—but they feel transparently accountable to others within
the self-organized teams in which the work gets done. And that
protected 20% time has been credited with the incubation of more
than half of Google’s current product portfolio, including Gmail,
AdSense, Google Talk, Google News, Google Transit, Google Now,
and the Google Transparency Report.
Team boundaries have a big impact on performance for service
providers as well. In a recent Harvard Business School study, Melissa
Valentine and Amy Edmondson show how such boundaries (in their
case, counters delimiting small and very fl uid groupings of nurses
and physicians) improved teamwork and effi ciency in a hospital’s
emergency department. Transparency and accountability among
people working within the boundaries increased. As a result, aver-
age patient time in the department fell by more than 40%, with
no decrease in quality. Remarkably, the department sustained that
improvement for over a year (the length of the study) even though
its daily patient volume rose by more than 25%.
Although tools for observation (see the sidebar “Tracking Every
Move”) and collaboration have become more powerful, making
it easier for individuals to do much of their work without formal
teams to support them, teams are actually proliferating rather than
dying off . Longitudinal surveys show that today nearly all Fortune
1000 fi rms have formal team structures, compared with fewer than
20% in 1980. Though a number of factors are driving that trend, my
research suggests it has something to do with the value of bound-
aries. Workers today can tackle problems in cooperation with
large networks—and even crowds—of people, but as teams scholar
Richard Hackman demonstrated, they frequently do it better on
20THE TRANSPARENCY TRAP
Tracking Every Move
MANY OF THE SAME COMPANIES that led the digital transformation of in-
dustries are also leading the digital transformation of work—allowing manag-
ers to observe from a distance far more than they could before.
Even knowledge work can be digitally monitored now. VoloMetrix—a Seattle-
based start-up that extracts and analyzes data from company e-mails, calen-
dars, social platforms, and line-of-business operations—provides employees
with “people analytics” productivity dashboards based on their own collabo-
ration and activity data or the data of the people they manage.
Of course, all this can feel intrusive—creepy, even—unless employers say
what’s in it for those being watched. That’s how companies persuade con-
sumers to give up personal information—by off ering a quid pro quo. Yet for
all the rhetoric about the value of utter transparency, there is scant empiri-
cal research to support it. So, what value can managers give in exchange for
digitally tracking employees? Can they make the work easier or increase its
impact? Can they use the data for recognition rather than coercion?
Ambition, a Y Combinator start-up, is trying to make transparency more en-
gaging and less intrusive by reporting performance data as if employees were
players on fantasy football teams (the user interface mimics fantasy football).
Meanwhile, more individuals are monitoring their own activity through such de-
vices as the Jawbone UP, the Fitbit, and the Nike+ FuelBand, to improve their be-
havior. Perhaps that will make them more receptive to digital tracking at work,
which can yield equally benefi cial self-awareness, even if the boss is watching.
Some Examples:
Amazon warehouse employees carry handheld computers that track and
optimize every move.
Tesco warehouse workers wear armbands that do the same.
UPS trucks now have sensors that record nearly every action by their drivers.
Harrah’s uses RFID technology to track how long it takes the waitstaff to serve
drinks to customers.
clearly bounded teams. Boundaries create a focus on “us” and “our
work together,” liberated from external noise, whether it’s unpro-
ductive interference or chaotic workfl ow. No matter what the work
is, some observers will increase productivity, but others will under-
mine it. Whether boundaries are spatial or psychological, they can
21BERNSTEIN
limit observation to a zone of people. It happens with curtains,
cabals, counters—even nominal team boundaries mitigate the pres-
sures of being onstage by keeping the audience small.
Type 2: Boundaries Between Feedback and Evaluation
Organizations are incorporating more and more real-time data—all
those electronic bread crumbs we leave behind as we do our work—
into performance assessments. In response, employees waste a lot
of valuable energy managing impressions. But tools that separate
data-informed feedback from the evaluation process help lower
people’s defenses and put the focus squarely on productivity and
problem solving, where you want it.
In general, any information that goes into a formal performance
review tends to put people on edge. Nevertheless, most employ-
ees are keenly interested in improving their skills. Just look at
the popularity of Rypple, a social media platform created to allow
members of organizations to give and gather anonymous feedback.
(Salesforce.com purchased Rypple within three years of its launch
for $60 million. It’s now called Work.com.) “You simply had to ask,
‘How am I doing at X?’” explains Rypple cofounder Daniel Debow,
“and the answers were purely for you.” Because only the recipients
had access to their feedback, fear of repercussions was removed
from the equation. Further, Debow notes, those giving the feedback
submitted honest, useful appraisals—with assurance of privacy,
they didn’t have to worry that candid criticism might damage col-
leagues’ reputations.
Another way of allowing employees to learn from their day-to-
day actions without having every little mistake exposed to manage-
ment is to deliver feedback within a protective bubble. A large U.S.
trucking company did this when it installed a DriveCam at the top
of each tractor cab’s windshield to improve driver safety and per-
formance. The small video camera points both outside and at the
driver, gathering and wirelessly transmitting data that analysts can
use to fl ag risky behaviors and prevent accidents. A green light tells
the driver that all is well. But during a “G-force event” (any erratic
22THE TRANSPARENCY TRAP
driving incident that causes gravitational force, such as excessive
speeding, slamming of brakes, or sudden swerving), the light blinks
red and green. If the force is strong enough, the light turns red and
the camera stores footage from eight seconds before and four sec-
onds after the event. (On average, each vehicle’s DriveCam stores
about fi ve minutes’ worth of video a month.) The DriveCam also
records key metrics, like the truck’s speed and location.
A small group of coaches who oversee fl eet safety review any
events deemed preventable. Only in a situation involving damage
or a willful breaking of the law—for instance, failing to use a seat
belt or text ing while driving—would the coaches share footage with
management. And the supervisors who evaluate the truckers aren’t
privy to the coaching.
When the DriveCams were installed, drivers initially dreaded
“being watched by Big Brother.” Some got distracted when the red
light came on, which made safety worse. But drivers have since
warmed to the cams, because they now trust that management
won’t use the videos to evaluate or reprimand them. As one coach
explains, the collaboration is helping drivers “turn bad habits into
good habits” and improving their safety record. When coaches look
at the footage with drivers, “it really does help,” another says. “It
changes people’s perspectives.” Sometimes it’s just a simple realiza-
tion: “Wow, you know, I was following a little too closely.”
Type 3: Boundaries Between Decision Rights
and Improvement Rights
Managers work hard to clarify decision rights, and for good reason.
Spelling out who gets to make which calls helps organizations run
more smoothly. It prevents duplicated eff ort, for example, and deci-
sion gridlock. But the empowerment of a select few can leave the
other people in the organization feeling voiceless, especially if they
aren’t explicitly invited to improve systems, processes, roles, and
tasks. Employees may withhold their ideas or implement them on
the sly. When organizations don’t grant improvement rights to those
without decision rights, innovation by those who see solutions
23BERNSTEIN
where others don’t—known as productive, or positive, deviance—is
eff ectively squashed in favor of conformity and compliance.
It’s important to draw a line between the two kinds of rights,
because the people exercising them have diff erent needs. Holders
of decision rights benefi t from a transparent environment, where
“every small fact becomes the subject of careful, scientifi c investiga-
tion,” as Frederick Winslow Taylor put it more than a century ago.
But while holders of decision rights want perfect visibility, which
requires transparency from everyone, that kind of visibility gets in
the way of employees’ striving to make things better, because it cur-
tails the experimentation necessary for improvements, as seen in
the mobile phone factory and other settings.
In fact, a long stream of research tells us that in the presence of
others, people do better on repetitive, practiced tasks—what psy-
chologists call dominant responses—but worse on learning tasks
that call for creative thinking. The visibility created by transparency
conjures up self-consciousness and inhibitions. That’s why musi-
cians perform in front of an audience but practice without one—they
need privacy to noodle and make discoveries. So, the right level of
transparency—and thus oversight—depends on the activity and the
observer. While musicians may practice in front of a teacher, that
teacher is an invited coach, not a consumer of their work. Technology
is making close scrutiny by large audiences of consumers possible
to a degree that Taylor could never have imagined, and clear deci-
sion rights amplify its eff ects. If you’re under the spotlight in front
of such an audience, the last thing you want to do is to make unprac-
ticed improvements while being held to a performance standard. All
that transparency can create yearning for a closed door with a sign
that says, “I’m in rehearsal!”
Organizations that understand all this are giving employ-
ees a reprieve from total transparency in order to make “slack”
(excess resources) more productive rather than more scarce. Take
Flextronics, a company that Willy Shih, Nina Bilimoria Angelo, and
I have studied. By setting up a “moonshine shop,” Flextronics has
turned its factory fl oor in Guadalajara into a veritable Legoland for
workers. The shop gives employees a place to develop tools and
24THE TRANSPARENCY TRAP
fi xtures for their lines in periods of downtime—creative work that
imparts a sense of ownership. (Manufacturing companies often
facilitate improvement rights in this way.) Made of simple pipes,
connectors, and recycled materials, the designs produced in the
shop can cost a tenth of what it takes to produce the more complex,
specially sourced fi xtures provided by vendors. The quality makes
IKEA look high-end, but the designs do the job effi ciently, safely, and
eff ectively. More important, the shop encourages continual innova-
tion by the operators, creating effi ciencies that would otherwise
remain in the imagination of workers.
Manufacturers aren’t the only organizations that have made
slack more productive by protecting improvement rights. Saravanan
Kesavan, Bradley Staats, and I saw this happen at the U.S. retailer
Belk when it upgraded a mostly manual labor-scheduling system for
its 24,000 employees and 300-plus department stores. Belk could
have followed the lead of large retailers that have automated nearly
all the scheduling tasks, increasing the effi ciency of labor with com-
plex algorithms based on minute-by-minute sales fi gures, real-time
weather predictions, activity-based time studies, and other data.
But Belk wanted to give its store managers and schedulers the fl ex-
ibility to account for staffi ng variations and other local factors, since
retail labor is a key driver of customer experience—and, therefore,
sales. So its managers chose the simplest form of the technology and
allowed local store managers and schedulers to exercise judgment,
revising the schedules proposed by the system without having to
seek corporate-level approval.
In the early days they revised more than 70% of the scheduling.
Now that rate is below 50%—a more efficient, productive range.
And while at least one of Belk’s competitors recently suff ered well-
publicized challenges in getting a return on its new fully automated
scheduling system, Belk’s pilot stores showed a 2% lift in gross profi t
by the end of 2013, several months after implementing the version
that allowed for overrides.
Which employees should be given improvement rights in order
to create productive zones of slack? That depends on the organi-
zation and its leadership. In a lean environment everyone may be
25BERNSTEIN
responsible for improvement. But other companies might treat it as
an opportunity, not a mandate, perhaps vesting improvement rights
in an R&D unit, a heavyweight team of senior managers, or front-
line workers. Or an organization might outsource improvements to
suppliers, contractors, or consultants. In any case, the assignment of
improvement rights both refl ects and infl uences strategy, so leaders
must protect them by putting skunkworks activities inside zones of
privacy.
Type 4: Boundaries Around Time
Another way to strike the right balance between transparency and
privacy is to experiment within limited blocks of time. With this
approach, execu