Strategies for learning from Failure
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LEADERSHIP
Strategies for Learning from Failure by Amy C. Edmondson
FROM THE APRIL 2011 ISSUE
The wisdom of learning from failure is incontrovertible. Yet organizations that do itwell are extraordinarily rare. This gap is not due to a lack of commitment tolearning. Managers in the vast majority of enterprises that I have studied over the past 20 years—pharmaceutical, financial services, product design, telecommunications, and
construction companies; hospitals; and NASA’s space shuttle program, among others—
genuinely wanted to help their organizations learn from failures to improve future
performance. In some cases they and their teams had devoted many hours to after-action
reviews, postmortems, and the like. But time after time I saw that these painstaking efforts
led to no real change. The reason: Those managers were thinking about failure the wrong
way.
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Most executives I’ve talked to believe that failure is bad (of course!). They also believe that
learning from it is pretty straightforward: Ask people to reflect on what they did wrong and
exhort them to avoid similar mistakes in the future—or, better yet, assign a team to review
and write a report on what happened and then distribute it throughout the organization.
These widely held beliefs are misguided. First, failure is not always bad. In organizational
life it is sometimes bad, sometimes inevitable, and sometimes even good. Second, learning
from organizational failures is anything but straightforward. The attitudes and activities
required to effectively detect and analyze failures are in short supply in most companies,
and the need for context-specific learning strategies is underappreciated. Organizations
need new and better ways to go beyond lessons that are superficial (“Procedures weren’t
followed”) or self-serving (“The market just wasn’t ready for our great new product”). That
means jettisoning old cultural beliefs and stereotypical notions of success and embracing
failure’s lessons. Leaders can begin by understanding how the blame game gets in the way.
The Blame Game
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Failure and fault are virtually inseparable in most households, organizations, and cultures.
Every child learns at some point that admitting failure means taking the blame. That is why
so few organizations have shifted to a culture of psychological safety in which the rewards
of learning from failure can be fully realized.
Executives I’ve interviewed in organizations as different as hospitals and investment banks
admit to being torn: How can they respond constructively to failures without giving rise to
an anything-goes attitude? If people aren’t blamed for failures, what will ensure that they
try as hard as possible to do their best work?
This concern is based on a false dichotomy. In actuality, a culture that makes it safe to admit
and report on failure can—and in some organizational contexts must—coexist with high
standards for performance. To understand why, look at the exhibit “A Spectrum of Reasons
for Failure,” which lists causes ranging from deliberate deviation to thoughtful
experimentation.
Which of these causes involve blameworthy actions? Deliberate deviance, first on the list,
obviously warrants blame. But inattention might not. If it results from a lack of effort,
perhaps it’s blameworthy. But if it results from fatigue near the end of an overly long shift,
the manager who assigned the shift is more at fault than the employee. As we go down the
list, it gets more and more difficult to find blameworthy acts. In fact, a failure resulting from
thoughtful experimentation that generates valuable information may actually be
praiseworthy.
When I ask executives to consider this spectrum and then to estimate how many of the
failures in their organizations are truly blameworthy, their answers are usually in single
digits—perhaps 2% to 5%. But when I ask how many are treated as blameworthy, they say
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(after a pause or a laugh) 70% to 90%. The unfortunate consequence is that many failures go
unreported and their lessons are lost.
Not All Failures Are Created Equal
A sophisticated understanding of failure’s causes and contexts will help to avoid the blame
game and institute an effective strategy for learning from failure. Although an infinite
number of things can go wrong in organizations, mistakes fall into three broad categories:
preventable, complexity-related, and intelligent.
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Preventable failures in predictable operations. Most failures in this category can indeed be considered “bad.” They usually involve
deviations from spec in the closely defined processes of high-volume or routine operations
in manufacturing and services. With proper training and support, employees can follow
those processes consistently. When they don’t, deviance, inattention, or lack of ability is
usually the reason. But in such cases, the causes can be readily identified and solutions
developed. Checklists (as in the Harvard surgeon Atul Gawande’s recent best seller The
Checklist Manifesto) are one solution. Another is the vaunted Toyota Production System,
which builds continual learning from tiny failures (small process deviations) into its
approach to improvement. As most students of operations know well, a team member on a
Toyota assembly line who spots a problem or even a potential problem is encouraged to pull
a rope called the andon cord, which immediately initiates a diagnostic and problem-solving
process. Production continues unimpeded if the problem can be remedied in less than a
minute. Otherwise, production is halted—despite the loss of revenue entailed—until the
failure is understood and resolved.
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Unavoidable failures in complex systems. A large number of organizational failures are due to the inherent uncertainty of work: A
particular combination of needs, people, and problems may have never occurred before.
Triaging patients in a hospital emergency room, responding to enemy actions on the
battlefield, and running a fast-growing start-up all occur in unpredictable situations. And in
complex organizations like aircraft carriers and nuclear power plants, system failure is a
perpetual risk.
Although serious failures can be averted by following best practices for safety and risk
management, including a thorough analysis of any such events that do occur, small process
failures are inevitable. To consider them bad is not just a misunderstanding of how complex
systems work; it is counterproductive. Avoiding consequential failures means rapidly
identifying and correcting small failures. Most accidents in hospitals result from a series of
small failures that went unnoticed and unfortunately lined up in just the wrong way.
Intelligent failures at the frontier. Failures in this category can rightly be considered “good,” because they provide valuable
new knowledge that can help an organization leap ahead of the competition and ensure its
future growth—which is why the Duke University professor of management Sim Sitkin calls
them intelligent failures. They occur when experimentation is necessary: when answers are
not knowable in advance because this exact situation hasn’t been encountered before and
perhaps never will be again. Discovering new drugs, creating a radically new business,
designing an innovative product, and testing customer reactions in a brand-new market are
tasks that require intelligent failures. “Trial and error” is a common term for the kind of
experimentation needed in these settings, but it is a misnomer, because “error” implies that
there was a “right” outcome in the first place. At the frontier, the right kind of
experimentation produces good failures quickly. Managers who practice it can avoid the
unintelligent failure of conducting experiments at a larger scale than necessary.
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Leaders of the product design firm IDEO understood this when they launched a new
innovation-strategy service. Rather than help clients design new products within their
existing lines—a process IDEO had all but perfected—the service would help them create new
lines that would take them in novel strategic directions. Knowing that it hadn’t yet figured
out how to deliver the service effectively, the company started a small project with a
mattress company and didn’t publicly announce the launch of a new business.
Although the project failed—the client did not change its product strategy—IDEO learned
from it and figured out what had to be done differently. For instance, it hired team members
with MBAs who could better help clients create new businesses and made some of the
clients’ managers part of the team. Today strategic innovation services account for more
than a third of IDEO’s revenues.
Tolerating unavoidable process failures in complex systems and intelligent failures at the
frontiers of knowledge won’t promote mediocrity. Indeed, tolerance is essential for any
organization that wishes to extract the knowledge such failures provide. But failure is still
inherently emotionally charged; getting an organization to accept it takes leadership.
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How Leaders Can Build a
Psychologically Safe Environment
If an organization’s employees are to help spot existing and pending failures and to learn from them, their leaders must make it safe to speak up. Julie Morath, the chief operating officer of Children’s Hospital and Clinics of Minnesota from 1999 to 2009, did just that when she led a highly successful effort to reduce medical errors. Here are five practices I’ve identified in my research, with examples of how Morath employed them to build a psychologically safe environment.
Frame the Work Accurately People need a shared understanding of the kinds of failures that can be expected to occur in a given work context (routine production, complex operations, or innovation) and why openness and collaboration are important for surfacing and learning from them. Accurate framing detoxifies failure.
Building a Learning Culture
Only leaders can create and reinforce a culture that counteracts the blame game and makes
people feel both comfortable with and responsible for surfacing and learning from failures.
(See the sidebar “How Leaders Can Build a Psychologically Safe Environment.”) They should
insist that their organizations develop a clear understanding of what happened—not of “who
did it”—when things go wrong. This requires consistently reporting failures, small and large;
systematically analyzing them; and proactively searching for opportunities to experiment.
Leaders should also send the right message
about the nature of the work, such as
reminding people in R&D, “We’re in the
discovery business, and the faster we fail, the
faster we’ll succeed.” I have found that
managers often don’t understand or
appreciate this subtle but crucial point. They
also may approach failure in a way that is
inappropriate for the context. For example,
statistical process control, which uses data
analysis to assess unwarranted variances, is
not good for catching and correcting random
invisible glitches such as software bugs. Nor
does it help in the development of creative
new products. Conversely, though great
scientists intuitively adhere to IDEO’s slogan,
“Fail often in order to succeed sooner,” it
would hardly promote success in a
manufacturing plant.
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In a complex operation like a hospital, many consequential failures are the result of a series of small events. To heighten awareness of this system complexity, Morath presented data on U.S. medical error rates, organized discussion groups, and built a team of key influencers from throughout the organization to help spread knowledge and understanding of the challenge.
Embrace Messengers Those who come forward with bad news, questions, concerns, or mistakes should be rewarded rather than shot. Celebrate the value of the news first and then figure out how to fix the failure and learn from it.
Morath implemented “blameless reporting”—an approach that encouraged employees to reveal medical errors and near misses anonymously. Her team created a new patient safety report, which expanded on the previous version by asking employees to describe incidents in their own words and to comment on the possible causes. Soon after the new system was implemented, the rate of reported failures shot up. Morath encouraged her people to view the data as good news, because the hospital could learn from failures—and made sure that teams were assigned to analyze every incident.
Acknowledge Limits Being open about what you don’t know, mistakes you’ve made, and what you can’t get done alone will encourage others to do the same.
Often one context or one kind of work
dominates the culture of an enterprise and
shapes how it treats failure. For instance,
automotive companies, with their
predictable, high-volume operations,
understandably tend to view failure as
something that can and should be prevented.
But most organizations engage in all three
kinds of work discussed above—routine,
complex, and frontier. Leaders must ensure
that the right approach to learning from
failure is applied in each. All organizations
learn from failure through three essential
activities: detection, analysis, and
experimentation.
Detecting Failure
Spotting big, painful, expensive failures is
easy. But in many organizations any failure
that can be hidden is hidden as long as it’s
The slogan “Fail
often in order to
succeed sooner”
would hardly
promote success in a
manufacturing plant.
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As soon as she joined the hospital, Morath explained her passion for patient safety and acknowledged that as a newcomer, she had only limited knowledge of how things worked at Children’s. In group presentations and one-on-one discussions, she made clear that she would need everyone’s help to reduce errors.
Invite Participation Ask for observations and ideas and create opportunities for people to detect and analyze failures and promote intelligent experiments. Inviting participation helps defuse resistance and defensiveness.
Morath set up cross-disciplinary teams to analyze failures and personally asked thoughtful questions of employees at all levels. Early on, she invited people to reflect on their recent experiences in caring for patients: Was everything as safe as they would have wanted it to be? This helped them recognize that the hospital had room for improvement. Suddenly, people were lining up to help.
Set Boundaries and Hold People Accountable Paradoxically, people feel psychologically safer when leaders are clear about what acts are blameworthy. And there must be consequences. But if someone is punished or fired, tell those directly and indirectly affected what happened and why it warranted blame.
unlikely to cause immediate or obvious harm.
The goal should be to surface it early, before it
has mushroomed into disaster.
Shortly after arriving from Boeing to take the
reins at Ford, in September 2006, Alan
Mulally instituted a new system for detecting
failures. He asked managers to color code
their reports green for good, yellow for
caution, or red for problems—a common
management technique. According to a 2009
story in Fortune, at his first few meetings all
the managers coded their operations green, to
Mulally’s frustration. Reminding them that
the company had lost several billion dollars
the previous year, he asked straight out,
“Isn’t anything not going well?” After one
tentative yellow report was made about a
serious product defect that would probably
delay a launch, Mulally responded to the
deathly silence that ensued with applause.
After that, the weekly staff meetings were full
of color.
That story illustrates a pervasive and
fundamental problem: Although many
methods of surfacing current and pending
failures exist, they are grossly underutilized.
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When she instituted blameless reporting, Morath explained to employees that although reporting would not be punished, specific behaviors (such as reckless conduct, conscious violation of standards, failing to ask for help when over one’s head) would. If someone makes the same mistake three times and is then laid off, coworkers usually express relief, along with sadness and concern—they understand that patients were at risk and that extra vigilance was required from others to counterbalance the person’s shortcomings.
Total Quality Management and soliciting
feedback from customers are well-known
techniques for bringing to light failures in
routine operations. High-reliability-
organization (HRO) practices help prevent
catastrophic failures in complex systems like
nuclear power plants through early detection.
Electricité de France, which operates 58
nuclear power plants, has been an exemplar
in this area: It goes beyond regulatory
requirements and religiously tracks each
plant for anything even slightly out of the ordinary, immediately investigates whatever
turns up, and informs all its other plants of any anomalies.
Such methods are not more widely employed because all too many messengers—even the
most senior executives—remain reluctant to convey bad news to bosses and colleagues. One
senior executive I know in a large consumer products company had grave reservations
about a takeover that was already in the works when he joined the management team. But,
overly conscious of his newcomer status, he was silent during discussions in which all the
other executives seemed enthusiastic about the plan. Many months later, when the
takeover had clearly failed, the team gathered to review what had happened. Aided by a
consultant, each executive considered what he or she might have done to contribute to the
failure. The newcomer, openly apologetic about his past silence, explained that others’
enthusiasm had made him unwilling to be “the skunk at the picnic.”
In researching errors and other failures in hospitals, I discovered substantial differences
across patient-care units in nurses’ willingness to speak up about them. It turned out that
the behavior of midlevel managers—how they responded to failures and whether they
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encouraged open discussion of them, welcomed questions, and displayed humility and
curiosity—was the cause. I have seen the same pattern in a wide range of organizations.
A horrific case in point, which I studied for more than two years, is the 2003 explosion of the
Columbia space shuttle, which killed seven astronauts (see “Facing Ambiguous Threats,” by
Michael A. Roberto, Richard M.J. Bohmer, and Amy C. Edmondson, HBR November 2006).
NASA managers spent some two weeks downplaying the seriousness of a piece of foam’s
having broken off the left side of the shuttle at launch. They rejected engineers’ requests to
resolve the ambiguity (which could have been done by having a satellite photograph the
shuttle or asking the astronauts to conduct a space walk to inspect the area in question), and
the major failure went largely undetected until its fatal consequences 16 days later.
Ironically, a shared but unsubstantiated belief among program managers that there was
little they could do contributed to their inability to detect the failure. Postevent analyses
suggested that they might indeed have taken fruitful action. But clearly leaders hadn’t
established the necessary culture, systems, and procedures.
One challenge is teaching people in an organization when to declare defeat in an
experimental course of action. The human tendency to hope for the best and try to avoid
failure at all costs gets in the way, and organizational hierarchies exacerbate it. As a result,
failing R&D projects are often kept going much longer than is scientifically rational or
economically prudent. We throw good money after bad, praying that we’ll pull a rabbit out
of a hat. Intuition may tell engineers or scientists that a project has fatal flaws, but the
formal decision to call it a failure may be delayed for months.
Again, the remedy—which does not necessarily involve much time and expense—is to
reduce the stigma of failure. Eli Lilly has done this since the early 1990s by holding “failure
parties” to honor intelligent, high-quality scientific experiments that fail to achieve the
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desired results. The parties don’t cost much, and redeploying valuable resources—
particularly scientists—to new projects earlier rather than later can save hundreds of
thousands of dollars, not to mention kickstart potential new discoveries.
Analyzing Failure
Once a failure has been detected, it’s essential to go beyond the obvious and superficial
reasons for it to understand the root causes. This requires the discipline—better yet, the
enthusiasm—to use sophisticated analysis to ensure that the right lessons are learned and
the right remedies are employed. The job of leaders is to see that their organizations don’t
just move on after a failure but stop to dig in and discover the wisdom contained in it.
Why is failure analysis often shortchanged? Because examining our failures in depth is
emotionally unpleasant and can chip away at our self-esteem. Left to our own devices, most
of us will speed through or avoid failure analysis altogether. Another reason is that
analyzing organizational failures requires inquiry and openness, patience, and a tolerance
for causal ambiguity. Yet managers typically admire and are rewarded for decisiveness,
efficiency, and action—not thoughtful reflection. That is why the right culture is so
important.
The challenge is more than emotional; it’s cognitive, too. Even without meaning to, we all
favor evidence that supports our existing beliefs rather than alternative explanations. We
also tend to downplay our responsibility and place undue blame on external or situational
factors when we fail, only to do the reverse when assessing the failures of others—a
psychological trap known as fundamental attribution error.
My research has shown that failure analysis is often limited and ineffective—even in
complex organizations like hospitals, where human lives are at stake. Few hospitals
systematically analyze medical errors or process flaws in order to capture failure’s lessons.
Strategies for Learning from Failure
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Recent research in North Carolina hospitals, published in November 2010 in the New
England Journal of Medicine, found that despite a dozen years of heightened awareness that
medical errors result in thousands of deaths each year, hospitals have not become safer.
Fortunately, there are shining exceptions to this pattern, which continue to provide hope
that organizational learning is possible. At Intermountain Healthcare, a system of 23
hospitals that serves Utah and southeastern Idaho, physicians’ deviations from medical
protocols are routinely analyzed for opportunities to improve the protocols. Allowing
deviations and sharing the data on whether they actually produce a better outcome
encourages physicians to buy into this program. (See “Fixing Health Care on the Front
Lines,” by Richard M.J. Bohmer, HBR April 2010.)
Motivating people to go beyond first-order reasons (procedures weren’t followed) to
understanding the second- and third-order reasons can be a major challenge. One way to do
this is to use interdisciplinary teams with diverse skills and perspectives. Complex failures
in particular are the result of multiple events that occurred in different departments or
disciplines or at different levels of the organization. Understanding what happened and how
to prevent it from happening again requires detailed, team-based discussion and analysis.
A team of leading physicists, engineers, aviation experts, naval leaders, and even astronauts
devoted months to an analysis of the Columbia disaster. They conclusively established not
only the first-order cause—a piece of foam had hit the shuttle’s leading edge during launch—
but also second-order causes: A rigid hierarchy and schedule-obsessed culture at NASA
made it especially difficult for engineers to speak up about anything but the most rock-solid
concerns.
Promoting Experimentation
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The third critical activity for effective learning is strategically producing failures—in the
right places, at the right times—through systematic experimentation. Researchers in basic
science know that although the experiments they conduct will occasionally result in a
spectacular success, a large percentage of them (70% or higher in some fields) will fail. How
do these people get out of bed in the morning? First, they know that failure is not optional in
their work; it’s part of being at the leading edge of scientific discovery. Second, far more
than most of us, they understand that every failure conveys valuable information, and
they’re eager to get it before the competition does.
In contrast, managers in charge of piloting a new product or service—a classic example of
experimentation in business—typically do whatever they can to make sure that the pilot is
perfect right out of the starting gate. Ironically, this hunger to succeed can later inhibit the
success of the official launch. Too often, managers in charge of pilots design optimal
conditions rather than representative ones. Thus the pilot doesn’t produce knowledge about
what won’t work.
In the very early days of DSL, a major telecommunications company I’ll call Telco did a full-
scale launch of that high-speed technology to consumer households in a major urban
market. It was an unmitigated customer-service disaster. The company missed 75% of its
commitments and found itself confronted with a staggering 12,000 late orders. Customers
Too often, pilots are conducted under
optimal conditions rather than
representative ones. Thus they can’t show
what won’t work.
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Designing Successful Failures
Perhaps unsurprisingly, pilot projects are usually designed to succeed rather than to produce intelligent failures—those that generate valuable information. To know if you’ve designed a genuinely useful pilot, consider whether your managers can answer yes to the following questions:
were frustrated and upset, and service reps couldn’t even begin to answer all their calls.
Employee morale suffered. How could this happen to a leading company with high
satisfaction ratings and a brand that had long stood for excellence?
A small and extremely successful suburban pilot had lulled Telco executives into a
misguided confidence. The problem was that the pilot did not resemble real service
conditions: It was staffed with unusually personable, expert service reps and took place in a
community of educated, tech-savvy customers. But DSL was a brand-new technology and,
unlike traditional telephony, had to interface with customers’ highly variable home
computers and technical skills. This added complexity and unpredictability to the service-
delivery challenge in ways that Telco had not fully appreciated before the launch.
A more useful pilot at Telco would have tested the technology with limited support,
unsophisticated customers, and old computers. It would have been designed to discover
everything that could go wrong—instead of proving that under the best of conditions
everything would go right. (See the sidebar “Designing Successful Failures.”) Of course, the
managers in charge would have to have understood that they were going to be rewarded not
for success but, rather, for producing intelligent failures as quickly as possible.
In short, exceptional organizations are those
that go beyond detecting and analyzing
failures and try to generate intelligent ones
for the express purpose of learning and
innovating. It’s not that managers in these
organizations enjoy failure. But they
recognize it as a necessary by-product of
experimentation. They also realize that they
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Is the pilot being tested under typical circumstances (rather than optimal conditions)?
Do the employees, customers, and resources represent the firm’s real operating environment?
Is the goal of the pilot to learn as much as possible (rather than to demonstrate the value of the proposed offering)?
Is the goal of learning well understood by all employees and managers?
Is it clear that compensation and performance reviews are not based on a successful outcome for the pilot?
Were explicit changes made as a result of the pilot test?
don’t have to do dramatic experiments with
large budgets. Often a small pilot, a dry run of
a new technique, or a simulation will suffice.
The courage to confront our own and others’
imperfections is crucial to solving the
apparent contradiction of wanting neither to
discourage the reporting of problems nor to
create an environment in which anything
goes. This means that managers must ask
employees to be brave and speak up—and
must not respond by expressing anger or
strong disapproval of what may at first appear
to be incompetence. More often than we
realize, complex systems are at work behind
organizational failures, and their lessons and
improvement opportunities are lost when
conversation is stifled.
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Savvy managers understand the risks of unbridled toughness. They know that their ability
to find out about and help resolve problems depends on their ability to learn about them.
But most managers I’ve encountered in my research, teaching, and consulting work are far
more sensitive to a different risk—that an understanding response to failures will simply
create a lax work environment in which mistakes multiply.
This common worry should be replaced by a new paradigm—one that recognizes the
inevitability of failure in today’s complex work organizations. Those that catch, correct, and
learn from failure before others do will succeed. Those that wallow in the blame game will
not.
A version of this article appeared in the April 2011 issue of Harvard Business Review.
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Amy C. Edmondson is the Novartis Professor of Leadership and Management at
Harvard Business School and author of Teaming: How Organizations Learn, Innovate, and
Compete in the Knowledge Economy (Jossey-Bass, 2012). She received her PhD in
organizational behavior, AM in psychology, and AB in engineering and design, all from
Harvard University.
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