Recently I went down a Google search rabbit trail and discovered the works of Saras D. Sarasvathy. She researches and writes on entrepreneurship, cognitive science, and behavioral economics. I’ve found myself referring several times since then to one paper in particular that compares her effectuation framework for decision making and firm strategy to several others. What to Do Next? The Case for Non-Predictive Strategy
In several discussions lately around LEV companies, at DelMar, at MatchBOX, and even church I’ve seen myself and others request data to make decisions. They want past data to help them make a decision about where the organization should go in the future. To make a purchase. To hire a new employee. To increase a budget line item.
I’ve found myself in conflict, at least within my own head, with some of these folks. It isn’t because I believe the data they have is inaccurate. So why do I feel this conflict?
I think the paper helps explain it. They believe the data helps them to make a prediction. But I don’t believe the data has predictive power.
So what is it good for? I believe the data is useful to understand the past so that the future can be controlled (transformative). Or in some cases I don’t even think the future can be controlled but that the past data will help the organization adapt to whatever future happens (adaptive).
So while we are looking at the exact same data, the reasons we look at it and what we propose doing with really depends how much emphasis we place between prediction and control.
I discussed this with Daryl. I assessed him as usually in the visionary quadrant (predicting and controlling his future) or in the transformative quadrant (not predicting but controlling his future). I self assessed as being mostly in the adaptive quadrant (neither predicting nor controlling my future) but sometimes in the transformative. Agree? Disagree?
What quadrant are you most comfortable operating in?