In bottoms-up cultural transformation initiatives, how things are done is equally as or more important than what is done. Feedback loops and other methods of data-driven storytelling are our favorite way that people analytics makes culture transformation happen. Often, facts can change the conversation from tired head-nodding to curiosity. One people analytics team in an engineering company was struggling to help develop the company’s managers, for example. Managers often perpetuated a “sink or swim” culture that didn’t fit the company’s aspirations to be an inclusive, humane workplace. The data analysis found that teams whose managers spent at least 16 minutes of one-on-one time with each direct per week had 30 percent more engaged direct reports than the average manager, who spent just 9 minutes per week with directs. When they brought that data-driven story to the front lines, suddenly a platitude was transformed into a useful benchmark that got the attention of managers. In this way, data storytelling is a lightweight tool to build trust among stakeholders and bring behavioral science to culture transformation.
Top-down strategic transformation is often made necessary by market and technology factors outside the company, but here people analytics is a critical factor for execution. A people analytics team can serve as an instrument panel of sorts to track resources, boundaries, capacity, time use, networks, skill sets, performance, and mindsets that can help pinpoint where change is possible and can measure what happens when you try it.
One people analytics team at a financial services company was trying to help the CEO manage growth while he worked to instill a new culture in which departments would be asked to run leaner and more competitive in the market—“scrappy” and “hungry” were terms that often came up. As the transformation accelerated, teams were asked to do more with less, generate more data, and make decisions faster. Amid this, department leaders began to hear anecdotes about burnout and change fatigue and questioned whether the pace was sustainable. To address this, the people analytics team provided their CEO with a dashboard showing the number of hours that knowledge workers were active for in different teams. When an entire team is over-utilized, he knows they can’t handle more change, while under- or unevenly utilized teams might be more receptive. He can also slice the dashboard by tenure, to learn whether recent hires have been effectively onboarded before approving new hire requests to absorb extra work.