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.