The Six Most Popular Stories of 2024 — So Far

When I interviewed Phillip G. Clampitt in early 2024 about how leaders could better handle employee pushback, I sensed that he had much more wisdom to offer on the topic. One particular pain point we discussed: Leaders often encounter pushback in the form of informal meetings that happen just after formal meetings. It’s akin to sports fans recapping — and critiquing — what a coach did during a game. How can leaders handle this inevitable phenomenon? That question gave birth to MIT SMR’s most popular story of 2024 so far. Read it to get sage advice from Clampitt, a leadership consultant and the John P. Blair Endowed Chair in Communication at the University of Wisconsin-Green Bay.

What else has resonated with our readers? Not surprisingly, sorting through the noise on artificial intelligence, especially AI trends, has been brutal, but Thomas H. Davenport and Randy Bean’s article will help you make sense of the trends that matter. And at a time when too many AI and machine learning projects are failing, Eric Siegel shares advice on how to avoid deployment mistakes by using business metrics wisely.

Without question, leaders are still grappling with the best ways to handle hybrid work, even after the pandemic lessons they learned. I wholeheartedly agree with Brian Elliott’s take on return-to-office mandates (and welcome your comments on this one). Finally, don’t miss Stefan Tams’ advice on how managers can better support a multigenerational workforce.

We hope these six articles provide you with practical, evidence-based advice that you can apply this year and beyond.

#1
Hard Truths About the Meeting After the Meeting

Phillip G. Clampitt

We’ve all experienced the meeting after the meeting — when people have candid conversations about the meeting they just attended. These informal gatherings are inevitable. A key question is how you, as a leader, will participate. These post-meeting discussions produce moments of clarification, grousing, and pushback. The way a leader handles those responses can make the culture more supportive — or toxic. Explore five strategies to transform post-meeting dynamics in a positive way.

#2
Five Key Trends in Data Science and AI for 2024

Thomas H. Davenport and Randy Bean

Thanks to generative AI, artificial intelligence and data science became front-page news in 2023. So, what’s on leaders’ agendas this year? Three surveys of data executives identified five big trends: the push to get value out of generative AI, the industrialization of data science models, the domination of data products, the rethinking of the data scientist role, and the C-suite shakeup affecting data and AI leaders.

#3
Return-to-Office Mandates: How to Lose Your Best Performers

Brian Elliott

Productivity is a top concern for leaders, but return-to-office demands intended to boost employee effectiveness might do more harm than good. Mandates have been shown to have a detrimental effect on employee engagement and often don’t add any financial value. Typically, the core issue is that trust hasn’t been paired with accountability. Better productivity emerges when organizations are driven by measuring outcomes instead of monitoring employees.

#4
Eight Essential Leadership Tips for 2024

Laurianne McLaughlin

Jump-start becoming a better leader with these tips from MIT Sloan Management Review authors. Consider which advice you can apply to your current challenges, from change management to communication.

#5
How Tech Fails Late-Career Workers

Stefan Tams

As workforce demographics skew older, managers must attend to the well-being and job performance of workers aged 60 and over. Age-related cognitive changes and complex technology, in particular, can hinder older workers’ job performance, but managers can take a number of actions to better support a multigenerational workforce.

#6
What Leaders Should Know About Measuring AI Project Value

Eric Siegel

Should you deploy that machine learning model — or will it fail? Most leaders making these decisions are focusing on the wrong metrics, which dooms many projects. In this article, adapted from the book The AI Playbook: Mastering the Rare Art of Machine Learning Deployment, learn how and why you should use business metrics rather than technical ones to evaluate how well a machine learning model will perform — and how much business value it will deliver.