Why Movie Production Teams Do Not Learn From Failure

We love those wonderful stories about how people learn from failure. We champion the practices in certain industries (such as healthcare, the military, and commercial aviation) in which organizations improve based on systematic reflection. Yet, in a new study, Suresh Muthulingam and Kumar Rajaram find that Hollywood production teams do not seem to learn from failure effectively.  Perhaps we should not be surprised, as we have all witnessed highly publicized films, with top actors, flop spectacularly at the box office. 

Why is learning from failure difficult in the movie business?  The UCLA Anderson Review summarizes these scholars' findings: 

So why does failure appear to stick rather than teach? The researchers point to three structural barriers. First, fluid teams disband before the financial verdict arrives, so there is no collective moment of reckoning. Second, individuals tend to blame losses on external factors or other team members rather than examining their own contributions. Third, movie production lacks the kind of systematic post-failure review that exists in aviation or medicine.

The implications stretch beyond Hollywood. Any industry that relies on project-based teams assembled for a single engagement — teams that are dissolved afterward — may face similar dynamics. The research suggests that managers assembling such teams should pay close attention to the collective financial track record of members, particularly those in coordinating roles like producers who bring the group together.

These three points are right on point and consistent with my work and the research of other scholars about learning from failure.  First, stable teams have an opportunity to iterate, to reflect and learn.  Harvard's Richard Hackman once demonstrated the importance of stability, and the perils of instability, in his research on airplane cockpit crews.   Second, the fundamental attribution error is very real.  People tend to blame the person when others fail, but they blame external circumstances when failing themselves.  Finally, you learn effectively if you have a systematic process for evaluating, reflecting, and putting new techniques into practice.  The After Action Review used by the U.S. military is one such successful systematic practice, now employed by many companies, such as Royal Dutch Shell, as well as by many healthcare organizations.   

Why Might a Leader Fail in One Situation, But Succeed in Another?

Several months ago, I wrote about how many professional sports coaches do not win a championship in their first gig as a head coach.  Instead, they win in their second tenure, or even later.  I suggested that we don't see many CEOs in business get a second chance if they fail during their first tenure as a chief executive.  Today, however, I read about one leader who is thriving during her second opportunity to serve as a CEO.  Fortune's Phil Wahba wrote about Michelle Gass.  She served as CEO of Kohl's, which struggled during her time there.  Now, she's serving as chief executive at Levi's, and the company has been growing profitably with strong shareholder returns so far during her tenure.  

Why might Gass be succeeding after stumbling at Kohl's? Wahba offers two key reasons. First, he writes that the Levi's role "plays to all the strengths she's developed over her long career." In short, we have a better match between Gass' skillset and the demands of the job at Levi's than at Kohl's. Gass' background at Starbucks gave her a set of brand management skills that match well with the Levi's brand positioning work that needed to be done. Second, some chief executives may be more suited to growth scenarios than turnaround situations. The skillsets required in each situation are quite different. I certainly agree with both points, and I would add that the Kohl's situation was a tough one for any leader. Brick-and-mortar retailers of that type simply face a tough road with any leader at the helm; the economic and strategic headwinds are strong. I would also add that some leaders may learn from experience very effectively. Gass may have reflected on her first tenure and made key changes that helped her thrive in her second role.

Wahba makes one other key point though. He writes, "some might be in the right place at the right time and get too much credit for success, or, conversely, get blamed for being unable to fix an unfixable company." I think he hits the nail on the head. We often have a severe case of attribution error when it comes to chief executives. We typically give them too much credit when their companies succeed, and too much blame when their companies fail. The same goes for head coaches in sports. We need to consider all the factors that contribute to the performance of a company: the management team surrounding the CEO, the efficacy of corporate governance, the attractiveness of the industry structure, the macroeconomic conditions, and frankly, the good or bad fortune they may encounter during their tenure (to name just a few key factors).

The Downfall of Allbirds

Remember when Allbirds became the "cool" shoe that offered comfort and plenty of virtue signaling about sustainability.  People such as Larry Page and Barack Obama wore the sneakers.  The company went public in 2021, reaching a valuation at one point of more than $4 billion. Now, the Wall Street Journal reports that the company sold its intellectual property and other assets and liabilities to American Exchange Group for $39 million.   What happened to this once-popular brand, and what can we learn from its downfall?

1.  Allbirds expanded too aggressively and did not define their target market clearly as they grew.  After its initial success, the company moved into a variety of other product categories.  They developed other types of sneakers, as well as leggings, jackets, underwear, and golf shoes.  The company seemed to be trying to both offer performance shoes and comfort shoes, without the technological capabilities and advantages required to sell to more serious athletes.  Moreover, it invested heavily in retail stores, building out brick-and-mortar locations around the country.  Through it all, it became unclear who Allbirds' target market was.  Were they selling to athletes, "tech bros", or wealthy people who cared deeply about the planet?  Were they selling to millennials, or a much broader audience?  Trying to be all things to all people turned out to be a key factor in their downfall.  

2.  Allbirds' value proposition did not have sufficient breadth and depth.  The company positioned its distinctive wool sneakers as highly sustainable footwear.  The question becomes: Is sustainability sufficient enough to drive very high willingness to pay on the part of consumers?  In most successful cases, companies pair a sustainability dimension of their value proposition with other key features. For example, On running shoes offer high performance for athletes and comfort for walkers, not just eco-friendly materials and the opportunity to recycle used sneakers.  Tesla offers speed, luxury, and status, not just the opportunity to drive a car that does not use fossil fuels.  Patagonia offers very high quality, durable, and stylish outdoor wear alongside its eco-friendly credentials.  Allbirds trumpeted the shoes as comfortable, but many companies were innovating to offer incredible comfort.  I bought a pair of Allbirds; while I liked the shoes, they were not durable, and other shoes offered superior comfort.  In short, Allbirds failed to optimize other aspects of its value proposition, relying too heavily on sustainability alone to drive willingness to pay. The Wall Street Journal's Suzanne Kapner writes,

The premise that consumers would pay a premium for sustainably made products turned out to be flawed. “Sustainability comes way down the batting order behind factors like style, price and comfort,” said Neil Saunders, a managing director of research firm GlobalData. “Allbirds could have leaned in to any of these things alongside its green credentials but largely chose not to do so.”

3. Quality and durability concerns undermined the company's brand image.  The shoes didn't last long enough for many customers, or they became damaged too easily.   In the end, people were not willing to sacrifice quality for the sake of sustainability.  

4.  Finally, competitors offered a more compelling value proposition.  Let's take On, for example.  They began by offering a distinctive, high performance running shoe.  They layered on eco-friendly components to their value proposition. Then, they expanded their target market by attracting customers who found the shoes very comfortable for walking.  Elderly individuals loved them too for this reason.  They almost didn't need to market to this broader audience.  Word-of-mouth spread, and the distinctive look of the shoe attracted attention.   Yet, On didn't lose sight of the athlete.  They continue to innovate with the serious runner in mind.  In many ways, starting with the athlete and then selling to the masses is an easier transition than the one that Allbirds tried to execute (i.e., going from a casual shoe to trying to compete with performance sneakers).  

How Do We Avoid Getting Caught by Surprise?

Why do we get caught by surprise at times? A competitor catches us off guard with an innovative new product launch. A new social trend emerges that shifts consumer tastes substantially. A sudden shift in workforce engagement and employee turnover stuns us. How can we avoid getting surprised by such changes?   

In a new study, Nir Halevy, Elizabeth Miclau, and Serena Lee argue that the traditional explanations may not suffice.  Conventional wisdom suggests that such surprises often occur because managers fail to gather, attend to, and evaluate information effectively.  They stick to pre-existing beliefs rather than adjusting their conclusions based on new data, or they dismiss those with dissenting views.  In short, people miss the signals because they are not processing information effectively.  Halevy and colleagues provide an alternative explanation.  In their paper, published American Psychologist, the researchers posit that, "strategic surprises emerge when individuals, organizations, and nations think too abstractly or too concretely during strategic interactions."  Stanford Leadership Insights summarizes the scholars' main argument:

"The researchers suggest that people and institutions can be caught off guard when they think too abstractly or too concretely about the information related to a particular situation. The quality of information matters, but so does the framework in which it is interpreted.  Overly abstract thinking relies on broad schemas that can lead decision-makers to apply poorly fitting mental models, misjudge possible threats or opportunities, or assume that others will behave in stereotypical ways. Concrete thinking, on the other hand, involves being deeply immersed in the minutiae of a specific situation, which can lead people to ignore broad trends." 

Thus, the scholars suggest that we shift between abstract and concrete thinking as we evaluate data about emerging trends, marketplace dynamics, and consumer preferences.  In so doing, we are more likely to arrive at robust conclusions.  You are less likely to get caught off guard.  

What is the Value of an AI-Generated Cover Letter?

Source: https://chatmaxima.com/

Cover letters used to provide insight to hiring managers and helped them identify which candidates to select for an interview. A well-written cover letter signaled something about the quality of a candidate. Moreover, a well-tailored letter also could signal that a candidate was serious about the particular job opening. Do cover letters still have signaling value in the age of AI?

Several months ago, Jingyi Cui, Gabriel Dias, and Justin Ye published a working paper titled "Signaling in the Age of AI: Evidence from Cover Letters." They studied over 5 million cover letters submitted to 100,000 jobs on freelancer.com platform.  The examined the impact of a new feature on the platform that uses AI to generate cover letters for job candidates.  Perhaps not surprisingly, "Access to the tool increased textual alignment between cover letters and job posts and raised callback rates."  

However, that is not the end of the story.  The key finding pertained to a substantial drop in the correlation between cover-letter tailoring and invitations to interview, as well as a significant drop in the correlation with job offers.  On the other hand, workers' review scores (a metric developed by the platform to evaluate past work experiences) became more meaningful.  The authors conclude "These patterns suggest that as AI adoption increases, employers substitute away from easily manipulated signals like cover letters toward harder-to-fake indicators of quality."  

Finally, the scholars examined whether people spent time revising or editing the AI-generated cover letter.  Many people did not.  Yet, those people who did edit the letters increased their probability of landing the job!   

Interestingly, another study by Galdin and Silbert also studied job candidates on the freelancer.com platform.  They found that the length of applications increased after the introduction of AI tools to help candidates.  At the same time, "employers had a high willingness to pay for workers with more customized applications in the period before LLMs were introduced, but not after."  In short, they discovered a drop in the value of the well-crafted application as a signal of quality.  That drop had important implications.  They write, "Without costly signaling, employers are less able to identify high-ability workers, causing the market to become significantly less meritocratic: compared to the pre-LLM equilibrium, workers in the top quintile of the ability distribution are hired 19% less often, workers in the bottom quintile are hired 14% more often." 

Have We Failed to Prepare Gen Z Properly for the Workforce?

Have We Failed to Prepare Gen Z Properly for the Workforce?  NYU Professor Tessa West tackles this question in today's Wall Street Journal.  She argues that many recent college graduates do not have the social skills required to communicate clearly, manage conflict, and respond well to constructive feedback. She argues that they lack these skills for three main reasons:

1. West points out that a substantially lower percentage of younger workers have experienced a romantic relationship. Therefore, they have not developed the social competencies that are cultivated through these types of complex relationships. Those competencies (such as how to express emotions and deal with conflict) often are critical for effective workplace interactions.

2. Online education has harmed their ability to collaborate effectively on in-person teams.

3. The heavy reliance on digital communication (texts and instant messages) have made them unprepared to handle high-stakes interactions such as key presentations and in-person meetings, as well as unplanned moments of engagement with their managers.

West has some helpful suggestions for improving the ability of younger workers to navigate the workforce. I particularly liked her thoughts about creating a "culture of asking." Here's an excerpt:

Create a culture of asking. Anxiety leads us to retreat, rather than asking how to approach situations. There will be many times when new employees are unsure of whether the criticism they faced was normal or toxic, if they should approach the team first or their boss over an interpersonal conflict, and what “casual Friday” really means. Leaders should showcase asking. Start with established employees doing it—asking for clarity over jargon in a meeting is a good place to start. People should feel comfortable asking, “Was this feedback negative from the boss? I can’t tell.” They will build social connections while learning the landscape.

Transparency + Clarity: Information Dumps Don't Work

Lately, we hear a great deal about the value of radical transparency.  Consultants argue that leaders need to share information broadly with members of their organization.  They argue that radical transparency builds buy-in, trust, and commitment.  Sounds sensible, right?  Is there a downside though?  What risks does this approach create?

Martin Gutmann and Antoni Lacinai examine this issue in a new Fast Company article.  They contend that transparency only works when coupled with clarity.  They write:

Transparency in a company setting typically means more dashboards, more all-hands, and more context. It feels responsible—especially in uncertain moments—because it signals you aren’t hiding anything.  But facts don’t organize themselves. People still have to decide what matters, what they need to ignore, and what to do next. When leaders don’t provide that structure, they leave teams confused, and teams will fill in the blanks with rumor and gossip. In the end, this leads to more insecurity and more internal politics.

Gutmann and Lacinai argue that leaders need to explain why information is important, and then they must provide clear direction to their team members.  They have be wary of creating cognitive overload and overwhelming their employees with information.  People need to know what the priorities are and how to interpret key data.  

For me, any attempt to add clarity begins with leaders stepping into their employees' shoes.  They need to try to see things from their team members' perspectives.  How will they interpret information?  What might confuse them?  How might they be unsettled by certain data?  Stepping into their shoes will help leaders frame their messages, anticipate challenges, and develop strategies for reducing stress and anxiety among workers.  

NASA Issues Investigative Report About Starliner Failure

Twenty-three years ago, the Columbia Accident Investigation Board issued its comprehensive report on the 2003 Space Shuttle Accident.  My colleagues Amy Edmondson, Richard Bohmer, and I began an intensive research project about the tragedy, and we published a case study, book chapter, and Harvard Business Review article with our analysis.  We argued that the failed mission demonstrated how and why organizations and their leaders actively downplay ambiguous threats at times.  We examined how the culture and team dynamics made it difficult for technical experts to express dissenting views and share bad news.  

Sadly, it seems that many of these same challenges led to the problems on the 2024 Starliner mission which left astronauts stranded on the space station for approximately nine months.  Yesterday, NASA issued its investigative report on the Starliner failure.   Here is the excerpt from the report that caught my attention: 

A posture of risk acceptance was communicated by CCP (NASA's Commercial Crew Program) and Boeing leadership, creating division within the large working/joint team and eroded trust. During the mission, CCP and Boeing operational leadership consistently conveyed a position of risk acceptance and readiness to undock, which many perceived as premature and dismissive of unresolved technical concerns. This was particularly apparent regarding the Service Module RCS 138thruster anomalies. This posture gave the impression that completing the sortie mission was prioritized over a thorough assessment of crew safety risks.  

One interviewee noted, “People said, ‘Why bother? He’s driving in one direction and that’s what he wants.’”   

Some interviewees also mentioned the shuttle operational background of the SMMT Chair, NOM, and CCP PM, and the possible preconceived notion that accepting risk to return the vehicle and crew was the only real path forward. This mirrors decisions made for the shuttle when no safe haven in LEO or alternative return capability was available. 

This forward leaning approach led to a breakdown in open dialogue. NASA institutional stakeholders, including ISSP, FOD, and Technical Authorities, felt their input was undervalued or ignored, requiring governance intervention to ensure additional data analysis occurred before a final crew return decision. The perception that CCP leadership had formed a position before hearing all viewpoints created organizational silence, resistance to collaboration, and stagnation in decision making. 

Strong personalities within CCP and Boeing were seen as overly optimistic in presenting data, which some interviewees interpreted as lobbying rather than objective analysis. This dynamic discouraged dissenting views and contributed to a growing sense of distrust. As one interviewee described, opposing positions felt like “pushing a rock uphill.” 

The situation improved later in the mission when key personnel changes were made within the Boeing team and there was collective recognition that senior leadership should have played a more active role in facilitating respectful engagement across differing perspectives. These changes allowed for more productive conversations regarding the technical qualification campaign of the hardware and testing at the WSTF. The lack of early intervention to address team dysfunction allowed conflict to overshadow mission objectives and delayed consensus on critical decisions. 

Organizational silence, discouraging of dissenting views, dismissed technical concerns, overly optimistic analysis... the pattern is clear.  Once again, we see ample evidence that leadership did not create a culture in which open and candid dialogue could occur about ambiguous risks.  I'm glad to see a careful after-action review taking place here, with transparency about the organizational problems that have been identified (rather than only focusing on the technical problems).  Having said that, now the challenge is clear: can NASA turn these lessons into action and fundamentally change the way future programs are led?  

Overestimating What We Know: The Trap of Effortless Search

You would like to learn about a particular topic.  You have two options.  You can search online for information, which AI tools and search engines summarize quickly for you.  Alternatively, you could dig deeper, read an article or two, listen to a podcast, and... maybe even read a book on the subject!  How much do we rely on the easy route to knowledge, and how confident are we that we have become highly knowledgeable through our rapid search for information?

In her amazing book, Uncertain: The Wisdom and Wonder of Being Unsure, author and journalist Maggie Jackson explores this topic.  She writes:

After even a brief online search, information seekers tend to think they know more than they actually do, according to a decade of studies. In one set of five experiments, people were asked to study weighty topics, such as autism or inflation, before taking a quiz on the subject. Half the participants were told to find an online article on the topic, while others were simply given the same information without having to search for it.  People who searched online were far more overconfident going into the quiz.  In one round, they predicted that, on average, they would get two-thirds of the questions right, although they scored less than 50%. 

In contrast, people who had been given the information studied longer, absorbed more, and got about 60% of the questions right - about what they had expected.  Rarely if ever in life are just handed information. Searching and seeking are the human condition. But how we do so matters.  In the virtual realm, we seem to lose the ability to sense that we don't know, the starting point of discernment.  This false confidence blossoms even when people learn nothing from an online search, further studies show. By assuming we can know effortlessly, we close our eyes to our failings and so to chances to explore.  We run from the work of fully attuning to the here and now, finding in hubris a retreat from the challenges of facing up to reality as potent as that of outcome-oriented fear. 

This research suggests that we need to proceed with caution when we jump to conclusions based on a breezy online search or quick prompt on an AI tool such as ChatGPT, Gemini, or Claude.   Ask yourself: What do I actually know?  How deep and accurate is my knowledge?  Should I be making critical decisions based on this superficial knowledge?

Careful How You Handle Familiar Faces on Your Team

When you take on a new role, do you like adding some familiar faces to your team?  It seems logical.  We want to surround ourselves with a few people we trust and can depend on when we move into a new position.   We hope that having some trusted lieutenants on the team will lead to faster, more impactful action. We may encounter some key risks, though, when we build our team in this fashion.  Morag Barrett, a leadership development expert, has written a terrific article for Fast Company about how leaders should (and should not) build their teams.  

Barrett argues that inner and outer circles may form on the team.  In academic terms, we describe this type of situation as a "fault line" between subgroups, and that type of fracture can harm team performance a great deal.  Barrett writes, "Leaders who 'go way back' share shorthand, context, and trust earned elsewhere. Others, often equally capable with deep institutional knowledge, find themselves outside that orbit."  

She goes on to give an example of one CEO with whom she worked.  She writes, "I coached a CEO who’d brought three former colleagues into a 10-person executive team. Within months, critical decisions were being pre-discussed among “The Four” before formal meetings. The other six leaders became increasingly passive, not because they lacked capability, but because challenging pre-baked decisions felt politically risky."  

I've seen this type of situation as well.  If team members outside the inner circle feel as though decisions are being presented at staff meetings as a fait accompli, then buy-in and commitment will decline precipitously.  Motivation and decision implementation will suffer.  We can bring trusted colleagues onto our team, but we need to work hard to integrate these members with the others in the group.  We can't let people feel as though there is a huge status gap between two subgroups.   

What Happens When We Can Quantify Some Aspects of a Decision But Not Others?

Do we make biased decisions because we are obsessed with quantifying our decision analysis? Linda Chang, Erika Kirgios, Sendil Mullainathan, and Katherine Milkman have published an interesting new study titled, "Does counting change what counts? Quantification fixation biases decision-making."  They asked the question: "Do people decide differently when some dimensions of a choice are quantified and others are not?"

The scholars conducted a series of experiments.  Each decision that the research subjects encountered involved some tradeoffs.  Some dimensions of the tradeoffs were described quantitatively and others qualitatively.  The results of the experiments demonstrated that people tended to prefer the alternatives about which numerical data was offered, rather than qualitative information.  Thea authors explain that, "This 'quantification fixation' is driven by the perception that numbers are easier to use for comparative decision-making."  

The scholars argue that we face many decisions in business and in life in which some dimensions of the tradeoffs can be quantified, but others simply cannot.  The qualitative information may be rich and useful though.  The numbers may tell only a portion of the story.  Think about a manager facing a decision about a brand extension.  Numbers may be readily available demonstrating the potential for sales growth, market share increases, and profitability enhancement.  On the other hand, the risks around brand dilution may be more readily described in qualitative fashion.  Do managers pay less attention those very real brand dilution risks simply because they can't easily produce numbers about how dilution may arise and impact the business?

The scholars conclude, "Those who structure decision contexts ignore quantification fixation at their peril. As quantification becomes increasingly prevalent, people may be pulled away from valuable qualitative information toward potentially less diagnostic numeric information."

How Good is the Second Act for a Leader?

Last week, I examined Mike Vrabel's path to the Super Bowl as a head coach in the National Football League.  I noted that 33% of Super Bowl winning head coaches had achieved their championship after failing to win a title with their first team.  The data suggest that a coach's second act can be more successful than the first, perhaps because leadership is a learned capability.   All-time great coaches such as Andy Reid, Bill Belichick, Mike Shanahan, and Don Shula all seemed to have learned from their successes and failures during their first tenure as a head coach.  

Today, I decided to examine whether this phenomenon was unique to the NFL.  Does the same pattern apply in the other major sports in the United States?   The table below shows the data for the past 50 years in each of the four major sports leagues.  As it turns out, the NFL is not unique.  In fact, the other sports show an even more dramatic positive effect for coaches in their second (or later) act!  In Major League  Baseball and the National Hockey League, more than 60% of championship coaches in the past 50 years did not win during their first tenure as a head coach.  All-time great hockey coaches and baseball managers in this group include Scotty Bowman, Al Arbour, Joe Torre, Dusty Baker, Terry Francona, and Tony LaRussa.   

By the way, during my original analysis of the NFL, I also noted that the sport's championship coaches demonstrated that the curse of expertise is very real.  The curse of expertise means that people with specialized knowledge who have achieved remarkable success often struggle to teach others, because they cannot easily put themselves into the shoes of someone for whom results do not come as easily.  In the NFL, only one Super Bowl winning head coach earned entry into the Hall of Fame as a player.  Is the curse of expertise also evident in the other sports?  Indeed!  Few Hall of Famers won championships in the last 50 years as a head coach: NFL (1), MLB (1), NHL (2), and NBA (4).  

Interestingly, second act success stories seem quite rare in business.  Most CEOs seem to achieve their most prominent success during their first tenure as a leader.  A few people stand out as having more successful second acts.  These include Reed Hastings, Eric Schmidt, and Stewart Butterfield.  The question that I'm not sure I can answer is:  Why are there more highly successful second acts in sports than in business?  Perhaps companies simply don't give many people that opportunity for a second chance if they have struggled during their first tenure as a chief executive.  Others would argue that talent matters more than coaching in sports, and that coaches win championships when they find the right fit between awesome talent and their good leadership skills.  Perhaps we simply attribute too much of a company's success or failure to the CEO, and therefore, we do not see through the struggles of a firm to identify the strong leadership capabilities of its top executive.  

Training Your Team Members Boosts Your Productivity

How much does your company invest in training and development for your employees?   Is the ROI positive?  Many executives scrutinize training and development programs closely.  They want to know if the payoff justifies the investment.  Typically, people measure ROI by examining the impact on the employees undergoing the training.  We ask questions such as: Are they more productive?  Are they more engaged? Do they stay at the firm longer?  

A new study examines another potentially important impact of training and development programs.  Miguel Espinosa and Christopher T. Stanton studied 526 frontline workers and 129 managers in Columbia who had undergone a 120-hour, 16-week training program.  According to HBS Working Knowledge, the scholars concluded:

"Goal achievement among frontline workers increased by roughly 10% after training.  Managers completed 3% more of their goals related to strategic tasks.  Supervisors who worked most closely with trained workers benefited the most, boosting productivity by about 8%.  An examination of email data explains why: After the training, frontline workers sent fewer emails to their managers—an indication that the training had given them the knowledge and confidence to pursue their work independently.  Trained employees enjoyed additional benefits, including career stability and growth. For example, they were more likely than their non-trained counterparts to remain with the organization over the next three years. And they were about twice as likely as their untrained counterparts to receive promotions."

Now this study examined frontline workers.  Other research should examine development programs for employees at higher levels of the organization to examine the productivity benefits.  Perhaps the benefits will not be as widespread.  However, this study certainly provides food for thought.  Executives may be looking at ROI all wrong when it comes to leadership development programs at all levels. 

Don't Just Observe Customer Pain Points; EXPERIENCE Them!

When I joined Staples as a young MBA graduate, I spent part of my first week working in one of the retail locations.  I worked in the checkout lane, unloaded shipments, stocked shelves, and answered customer questions.  Tom Stemberg, Staples' founder and CEO, believed that we had to walk in the shoes of our store associates and interact directly with customers to understand the business. He was right.  I was reminded of that experience when I read a recent Fast Company story by Christine de Wendel, CEO of sunday, a company that provides a payment platform to restaurants.  De Wendel insists that every employee must work a restaurant shift during the onboarding process. She explains why: 

Using our industry as an example, the restaurant space can’t be disrupted from a distance. It’s intensely human. A server manages six tables, remembers who wanted dressing on the side, tracks which kitchen orders are running late, and still needs to radiate warmth when checking on the anniversary couple at table twelve. When we ask them to adopt new technology, we’re not just changing their workflow, we’re asking them to trust us with their tips, their table turn times, and their relationship with guests.  You can’t design for that kind of stakes without understanding them viscerally.

De Wendel argues that there is a critical distinction between OBSERVING customer pain points and EXPERIENCING them yourself.  It is not sufficient to just interview users or watch them in action.  You have to live their experience, filled with its obstacles, emotions, and frustrations.  

Perhaps the most interesting point that De Wendel makes in her article is a statistic about employee turnover.  She explains, 

"Here’s what surprised me most: this policy has become one of our best retention and recruiting tools.  We’ve had a 94% retention rate among employees who complete the restaurant shift program, compared to 78% at my previous tech companies. Employees consistently rank it as one of their most valuable onboarding experiences." 

Lessons from Patriots Coach Mike Vrabel's Leadership Journey

What can we learn from the leadership journey of New England Patriots coach Mike Vrabel?  This week, I sat down with Bryant University writer Bob Curley to share my thoughts, including some interesting data about other coaches in NFL history. 

Using AI to Create a "Fantasy Board of Directors" for Yourself?

What would it be like if you could have Steve Jobs and Warren Buffett serving as advisers as you lead your team and make difficult decisions? Matt Blumberg, CEO of Markup AI, decided to use AI tools to create what he calls a "fantasy board of directors." Preston Fore reported on Blumberg's invention in Fortune this week. He writes,

"To build the fantasy board, Blumberg used a mix of ChatGPT, Gemini, and Claude to create 5,000-word profiles for each person. The profiles were trained on items in the public domain—with the goal of enabling the AI to respond to problems the way real board members might—grounded in how those business leaders viewed leadership, governance, and performance."

Blumberg describes how it only took a few hours to create this AI-generated fantasy board of directors. He uses the chatbot to prepare for board meetings, garner feedback on proposals and plans, and build better presentations to his company and his actual board. Blumberg said, "I’ll say things like: Hey, I’m doing a presentation for our kickoff meeting next week. What do you think are the top three themes I should hit?" He even used the AI tool to provide him with an annual review of his performance as CEO. Blumberg notes that the feedback was right on the mark.

Why Big Projects Run Over Budget and Behind Schedule

Have you been involved in a major project that ran well over budget and way behind schedule?  I'm sure the answer is yes.  We all have experienced this misery at times.  Why do so many large projects encounter these problems, while failing to deliver the expected benefits as well?  University of Oxford Professor Bent Flyvbjerg and journalist Dan Gardner wrote a terrific book about this topic.  The book is titled, How Big Things Get Done: The Surprising Factors that Determine the Fate of Every Project, From Home Renovations to Space Exploration, and Everything in Between.  

The book is chock full of insights about why projects go off the rails, and how we can approach projects more effectively.  They argue that a bias for action gets many project leaders in trouble.  They rush to execute before planning adequately.  "Just do it" becomes a dangerous mantra.  Moreover, they argue that some project leaders engage in strategic misrepresentation.  In other words, they know the budget and schedule are not reasonable at all.  Yet, they "start digging a hole" knowing that it will be hard for those providing resources to not fund the overruns once the project has begun.  

The authors argue that experience is essential in managing large projects.  They are big fans of the practical wisdom and learning that emerges from experience.  However, they argue that many project funders and leaders marginalize experience.  Why?  One key reason is what they call the "uniqueness bias."  In short, people always seem to believe that their project is unlike any other that has been done.  Thus, they think there's little to learn from others.  Moreover, many of them strive to produce something that is the first of its kind or the "biggest, tallest, longest, fastest" of its kind. This desire to produce something unique means that they can take huge risks, and they fail to learn from the experience of others.  Thus, we should all ask ourselves:  Is our project truly unique?  Moreover, do we need it be unique?  Is it ok if it is NOT the tallest, biggest, or first of its kind?"  

Don't Use AI to Brainstorm for You!

Do you often use AI chatbots such as ChatGPT, Claude, CoPilot, or Gemini to brainstorm for you?  How effective do you find this process?  Kellogg Professor Brian Uzzi ran an experiment with his students to examine the efficacy of these models and student attitudes about them.  Uzzi administered the Divergent Aptitude Test (DAT) to his students.   In four minutes, they had to generate a list of ten words that were as different as possible from one another.  He compared the students' creativity to the AI models.  

Uzzi found that the humans produced more unexpected responses than the AI models.  In other words, creativity flourished among humans, while the AI models produced average answers.   Unfortunately, Uzzi discovered that the students tended to prefer the responses generated by the AI chatbots.  Why?  Simply put, the students are impressed by the efficiency of these models.  Uzzi says, "They get sucked in by the efficiency.  Someone in class will say, ‘The bot’s score is no better than mine, but I get it in 10 seconds instead of several minutes.’ To them, that feels like a good trade-off.”

Uzzi doesn't believe that this simple experiment argues against all use of AI models.  Instead, he argues that we have to think carefully about HOW we use the models.  He explains, "To get the most out of a bot, don’t ask it for answers.  Ask how to approach a problem. You want advice on how to think, not what to think.”  In short, don't ask the AI model to replace your original thinking.  Ask it to complement or supplement your way of working.   

Let me offer an example from my use of AI to develop teaching plans and materials.  I don't simply ask one of the chatbots how to teach a certain topic.  Instead, I tend to think creatively about how to teach a subject, drawing on my years of experience as a faculty member. Then, I will ask AI to help me develop certain teaching materials that will achieve my goals.  Thus, I'm engaging in the creative act, while asking AI to help with the implementation of my ideas.   In this way, I'm combining human creativity and AI efficiency.