Many organizations build extensive dashboards to track key performance indicators but often do not examine whether the data they collect are actually informing their decisions or just creating noise. Build your data strategy using key hypotheses, or ‘end statements’ 1 Based on more than 1,000 respondents to a behavioral-insights survey conducted at the multinational aerospace organization during an approximately six-month period in 2022. These are employees who, after previously reporting little or no change in their daily behaviors, later reported material changes in their behaviors, as well as a strong desire to continue improving. For instance, this three-pronged approach helped the aerospace organization increase the number of capability-building “champions” in the company by almost 40 percent. Finally, leaders should ensure that any employees who are working with data are also trained to understand the key terms and principles of behavioral and organizational science.įocusing on all three areas can help organizations and their leaders unlock next-level insights and analytics. ![]() Second, to better understand when behavioral changes could be meaningful and in what context, leaders can use comparative analytics to look at important statistics over time. ![]() Based on our experience, there are three concrete ways that business leaders, working with IT, HR, and other functional leaders throughout an organization, can structure their analytics programs to reflect a behavioral-insights approach.įirst, to set a long-term data strategy, leaders can create “end statements” that define the kinds of business questions they are seeking to address and, therefore, the kind of data they need to collect. Before considering trades, contract renewals, or other organizational changes, analysts in the MLB or NBA can use the contextualized data from behavioral-insights models to differentiate between a good player on a bad team and a weaker player whose performance is buoyed statistically by the team’s success.īusiness leaders can similarly use behavioral-insights models to assess employee performance and support corporate change initiatives. Teams in Major League Baseball (MLB) and the National Basketball Association (NBA) use analytical models that consider players’ individual in-game statistics alongside intangibles such as performance under pressure or contribution to team chemistry. Perhaps the best examples come from the world of sports. It takes patterns of human behavior into account when analyzing raw data. This is where the field of behavioral insights can be a game changer.īehavioral insights is a relatively new approach to analytics pioneered by psychologists and social scientists. And without this comprehensive view, organizations may miss meaningful opportunities to instill new ways of working, which can ultimately lead to stagnation. The data that leaders typically use to measure progress on capability building-metrics like user clicks and progress rates through learning modules-often do not paint a full picture of how and whether behaviors are changing. By and large, however, the employees’ day-to-day behaviors were not necessarily changing. The data on these capability-building efforts showed that employees were completing a high percentage of the modules and feeling positive about their instructors and the overall learning experience. ![]() They launched a series of training modules to help employees build new capabilities in communications, prioritization, problem solving, and meeting hygiene. This disconnect may not be related to an unclear strategy or intention in many cases, it may simply be a data problem.Īt one aerospace organization, for instance, leaders wanted to boost the effectiveness of individuals and teams. But leaders are often at a loss to understand how investing in capability building can enable the necessary behavior change. Corporate transformations are unlikely to succeed if people can’t change their behaviors.
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