‘Firefighters are heroes.” We hear it all the time, from children, the media, and young people looking for a rewarding career. It’s probably something you’ve said or thought yourself at one time or another. These brave men and women put their own safety on the line every day to protect their communities.

Yet, amazingly, one of the most dangerous aspects of the job isn’t the fire itself, but the protective clothing they wear on the job. According to the Firefighter Cancer Support Network, firefighters are significantly more likely to develop cancer due to their exposure to carcinogens.

There is no shortage of books critical of business schools. The titles leave little doubt about how much disdain the authors have for the schools meant to prepare future leaders in business. Consider books like Shut Down the Business School: What’s Wrong with Management Education (Pluto Press, 2018), or Nothing Succeeds Like Failure: The Sad History of American Business Schools (Cornell University Press, 2019).

For criticisms of a specific school, there is The Golden Passport: Harvard Business School, the Limits of Capitalism, and the Moral Failure of the MBA Elite (Harvard Business, 2017 reprint).

These books lament the failure of business schools to develop ethical business leaders and to address societal concerns.

Let’s consider how to build a data analytics community. Many organizations want to establish communities of practice or other structures with a similar aim, fostering best practice and collaboration, often with analysts working in different parts of a corporation.

A data analytics community can bring real value to people across your organization. But how do you set one up? What challenges will you face? And how can you make it as successful as possible?

I learned a lot from setting up a data analytics community in my last role. Here are the top three areas I recommend focusing on to make it a success.

1. Identify your content and your audience

This is the first step. What is your community for?

Most white-collar employees have spent the bulk of their career working in teams. However, the rise of hybrid work environments is changing work paradigms in ways that make us wonder whether we still need teams. We’re not saying this lightly: Between the two of us, we’ve spent more than 40 years examining the ins and outs of teams in organizations.

Our recent conversations with employees at all levels have made something clear: While concern about work-life balance, burnout, employee disconnection, and turnover is common, those who seem to worry the most are those leading or working in teams.

It’s good to take a step back and remember that teamwork—to the extent that it’s used now—is relatively new. Enabled by technological advances, teamwork only became the norm for knowledge work during the early 1980s, in response to globalization.

The world fell in love with teams because when they work, they really work. Great teams can generate creative solutions to complex problems. They can provide camaraderie and the right level of challenge for employees. Indeed, high-performing teams don’t just produce great results; they also underpin some of the most desirable organizational cultures out there.

Welcome to the season that many leaders face with more than a little trepidation: midyear reviews. It’s the point on the calendar that serves as a reminder that the time remaining to deliver desired 2022 results is finite. It’s also the point when managers find themselves working (and worrying) overtime in preparation for conversations with staff to calibrate results and effort—and ensure that everyone is well poised to support success for the remainder of the year.

Even before the enormous changes ushered in by Covid-19, remote and hybrid working configurations, and the retention crisis facing many organizations, the value of the traditional review ritual was in question. Busy managers were challenged to find the time. And employees reported feeling that the exercise was an administrative necessity to be endured rather than a motivational touch point.

There is Alexa sitting on the kitchen counter waiting for your next query. But before she tells you how to make a perfect avocado salad, would you like to know something about the person who invented her?

As the use of automated assistants and other AI agents becomes more pervasive, how humans interact with them is increasingly a subject of debate and research. Now, a new study reveals that when people think about the humans who create these tools, they view the robots’ work as more authentic.

The study was conducted by Stanford Graduate School of Business professor Glenn R. Carroll, his University of Washington colleague Arthur S. Jago, and Mariana Lin, a writer and poet (and Stanford d.school lecturer) who helped create the voice of Apple’s Siri. Their paper was published in March 2022 by the Journal of Experimental Psychology: Applied.