A short monologue (by Ashish Kothari) arguing against one-size-fits-all employee development programs. It recommends using granular, data-driven diagnostics—at team or individual levels—to identify interventions that actually improve outcomes, and enabling local autonomy so individuals and teams can pull and deploy targeted development rather than relying on centrally imposed, delayed programs.
Chapters
As you're looking at surveys, as you're studying this problem, let's not focus on what we are weak as the only factor. Let's look at what we are good at or which actually increases the probability. Because in the end, there's only so many things we can focus at at one time. It's important to understand which ones significantly improve the results that we are looking for. And they might be different by a team or individual and an organization. And so let's try and take granular approaches to really optimizing our human assets. Just as you take granular approaches to optimize store productivity the way you use granular approaches to study diagnose manufacturing systems, lines, equipment. We don't do one size fits all, let's not do one size fits all interventions here as well. Let's really use the science to understand and choose the right interventions and also enable individuals autonomy to take the actions. We're not driving it from the center a year after the survey, a program that is one size fits all. We really support individuals to be able to pull and deploy. And so there's what I would call a breakthrough approach here that can really be created using this level of granularity and actionability of data.