METACOGNITIVE TOOL is one nice chunk of jargon.Metacognition is “learning about learning.” When we have a tool for it, that tool teaches us about how we learn. When we have some understanding about that, we can start to look for new ways to use the tool to learn more effectively.This is where something called “double-loop learning” comes in.When we use the kanban in our daily work we are employing several real-time techniques and strategies to get work done. “I’m going to make my tasks so they’ll take less than a few hours to complete.” “Today I’m going to work entirely on the City of Pelentagagagua proposal.” “I will do the work for my lawyer after I get this thing out of the way for my boss.”But while we are working, we are basing those decisions on a variety of assumptions. The kanban shows us, in real-time, the impacts of our assumptions. If we begin with an assumption that our office work is more important than getting things done for the family, after a while we’ll end up with a lot of aging family tickets and a DONE column filled with work tasks.When we see this, we’ll see that there is a cost to that assumption. That cost is a lot of pent up work for the house and likely an angry spouse.Other assumptions we might be making is that one client is more important than another, that if we do large tasks first we’ll get more done, or that if we deliver product at two-week intervals we’ll have a more predictable delivery schedule.We can use the real results from the kanban to question these basic assumptions, then alter our assumptions and see the results of that.As we do this, we learn:

the results of our actions (single-loop);
the effects of our basic assumptions (double-loop); and
how that understanding impacts how we work, how we create experiments, and how we react to change (metacognition).