New findings with old variables

Given we’ve been doing research in organizations since the 1920s, what do you imagine modern ‘people analytics’ is likely to find > new variables or new findings with old variables?

Love the question, Jason. Thank you. First, you appreciate that the work of looking into individual, team, group, and organizational behavior has been going on for a long time. You also appreciate that there’s a lot that’s been discovered; and that now, with the generation of new data, there’s more to discover. Such discoveries might discredit long held beliefs based on the research of the time (Why people leave organizations is a popular example – the replies are route, yet the best answer exists within the system to be studied at a certain point in time). Other discoveries might strengthen some insights or theories, and still others will be completely, or almost completely, new. So, to your question, both.

What’s new and exciting to me is the sustainability and scalability of people-related insights. Whether the variables be old or new, the ability to learn and take appropriate action at scale is a game changer; and this is especially true when the benefits not only go to the supervisor and/or organization, but to the individual him or her-self. Taking the example I eluded to before: the key variables (potential drivers) associated with voluntary turnover might be different in one job family to the next, from one group/cohort to the next, from one location to the next, etc. The ability to access, on demand, the appropriate insights (based on the best available variables) then take appropriate action is here to stay. What will continue to evolve for the better will be the definition of what’s appropriate. This is where the creativity comes in. I’ve written about this in almost every reply today. So, while there’s more to say on this topic, I believe we need to embrace the “and.” We must leverage and continually validate the research and analysis of yesterday while continually creating and crafting what’s most appropriate given the analysis we want to conduct, the insights we want to generate, and the experiences we want to deliver. Hope this helps; and thanks again for your question!