10 Jul. 2015 | Comments (0) Share Follow @Conferenceboard
People make big, difficult changes for two key reasons — to reap rewards and to avoid pain.
But what about entire teams that are deeply entrenched? How do you shake them up? As an HR executive, I’ve found that you sometimes have to show them future rewards or pain, especially if they’re comfortable and successful now. Though you may be able to see the writing on the wall, it can be tricky to get them to see it. That’s where data-driven experiments come in. They help shine a light on the opportunities and risks ahead, which can motivate stagnant teams to start thinking and behaving differently.
Here’s an example. In a prior role, I was heading up HR at a fifty-year-old company. Though we were in tech, the average age of our workforce was approximately 47, and turnover was extremely low. In fact, it wasn’t unusual for employees to celebrate 30 or 40 years of service. That set us apart from most other Silicon Valley firms, in both good and bad ways. The company was stable largely because of its healthy culture and loyal employees — but I worried about its future. What would happen when large portions of intact teams retired? Where would the knowledge go? Also, the innovation and speed of the R&D teams had begun to decrease. Were these factors linked to tenure, too? I thought they might be.
The analysis: HR and the R&D leaders looked for correlations between length of service and levels of engagement, innovation, and productivity on teams. HR also did predictive analysis for retention, creating a heat map of sorts to see where we had concentrated areas of risk.
We found that we had a few teams that had been intact for more than eight years without a single new hire. They had, on average, lower engagement scores than teams with more recent changes in membership. (We typically saw a 5 to 15 point difference in surveys.) They also had longer product development cycles, which potentially signaled lower productivity and slower innovation. What’s more, the stagnant teams hadn’t made any plans to add new members. Anywhere from 20% to 50% of their members would be eligible to retire at the same time — in just three to five years. I was worried.
Even though we were seeing correlation but perhaps not causation, I believed there was enough of a link to do a little test.
The test: For the summer, we brought in an undergraduate or graduate intern for each team that had gone more than eight years without an infusion of fresh blood. We encouraged larger teams to take two or three interns, as we didn’t want the new voices to get drowned out by the more experienced team members.
Our hypothesis was that with hungry, talented individuals now on board, these teams would learn how to teach others again. They would need to respond to questions about why things were done in certain ways. Through their mentoring, we hoped, the more seasoned members would also begin to spot opportunities for improvements that they wouldn’t otherwise see.
The results: As hypothesized, engagement went up — by eight points, on average. In a post-intern survey, team members said they had more energy and reported greater group participation in problem solving and knowledge sharing. And about half the teams elected to convert their eligible interns into regular full-time employees upon graduation — they loved having fresh eyes and minds in their midst. These hires helped mitigate the risk of talent drain a few years out. Because the teams had to educate their new colleagues, they started doing a much better job of documenting core processes, which of course improved knowledge transfer.
They also thought they became more efficient and innovative, specifically in R&D — though it was hard to gauge direct impact, since the cycles for product development remained relatively long. In any case, the fresh questions and the eagerness to solve problems and collaborate across teams were believed to contribute to better quality. Team leaders consistently saw an increase in discretionary effort, which they felt led to better problem solving.
The value of “seeing is believing”: The team analysis pointed me to areas of the organization that needed a bit of a recharge. The key to driving change in behavior was to highlight future rewards and risks — and to disrupt current patterns — in ways that didn’t threaten the teams personally. They’d have the interns for a summer, and if they didn’t see any benefits, that would be the end of the experiment. Even so, the change wasn’t completely accepted out of the gate. I did have to agree to fully fund all the interns from the HR budget the first year. To do this, I had to delay other initiatives in my function, but I felt the risk/reward ratio was worth it. By year two, we knew we’d made an impact when the teams set aside funds in their own budgets for new interns.
Who doesn’t love fresh eyes and passion? Once the teams had that energy, they wanted to keep it. All we had to do was share the data and the rationale for change, test a theory, and see if we got the desired results. To keep the change going, we knew it was important to continue testing impact, gauging acceptance, and looking for new improvements to make. That allowed the team leaders to tweak the program — it gave them a feeling of ownership.
If you think you need to lead a team through change, look to the data for future risks and rewards. Then create nonthreatening experiments that give the team a taste of the success they’ll enjoy if they make the change. Keep testing — and keep sharing what you learn. Once the team is in there, trying the new path, you’ll gain momentum. And if it’s the wrong path, that’s good information to have. Try another.
This blog first appeared on Harvard Business Review on 07/03/2015.
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