I’ve noticed lately that we tend to lump a bunch of things into the idea of “trying something”.

Your team commits to continuous improvement.

What might help? Perhaps…

1. Knowing¹ what better might look like
2. Knowing where you have leverage to make things better
3. Knowing how to intervene to apply that leverage
4. Knowing how to support that intervention
5. Knowing how to measure/detect if the intervention is working
6. Knowing when to amplify/dampen your efforts
7. Securing the tools, support, freedom, and bandwidth to do #1–#6²
8. Throwing #1–#7 into a heady mix of complexity and luck These points describe a set of highly overlapped areas of sensemaking. My aha the other night was that we tend to lump these things all together. Some examples:

• We assume an unclear sense of #3 (how to intervene) equates to an unclear sense of #1 (what better might look like).
• We confuse “best practices” (where and how), with our ability to support those practices in the current environment (#4,#6,#7).
• We assume that a team needs a prescriptive how, when we might be better served at growing experimentation skills (#2,#5,#6)…the cliche “learn how to learn”
• We assume that all a team needs is experimentation skills, when in fact they also need support, a sense of better, and contextually relevant experience.
• We might mistake a team as being incompetent, when they are lacking support. They “know” the right point of leverage, but they don’t have the freedom to address it head-on.
• Etc. Nothing earth-shattering here, but I do find it helpful to think through these points #1–#6 and ask:

1. What do we know? What do we need to learn? How can we learn?
2. How can we leverage our diversity of knowing?
3. Are we making assumptions about this point that should be challenged?
4. Who can help us? What do we need? Can we improve our skill(s) in this area? Can we reduce the noise, and boost the signal?
5. Are we accidentally lumping this point in with other points? Does looking at this separately help us?
6. Are we making this possible? (See #7). Is it possible?
7. Can we devise smaller experiments, and tighten our feedback loops? ¹ Knowing involves continuous learning. We never completely know. You could argue that knowing grows/fades through successively exploring #1–#8.

²#7 moves beyond knowing. It asks whether the tools, support, etc. are, in fact, made available (the output of #4).