Why don't people use issue trees, even when they help?

The biggest barrier to adopting structured thinking tools — SCQH, issue trees, hypothesis trees, LTP trees — is that they are psychologically and organisationally confronting rather than intellectually difficult.

There are several layers to this.

It takes discipline

Even with AI, building a proper issue tree takes real effort: slowing down, clarifying assumptions, resisting the urge to jump straight into action. Doing it well can still take a couple of days.

I don't always do it myself. I think "I know what I want to do" and go straight into execution. But if I'd done the work, I might have found a different constraint, or a much better way in. Most of us shortcut this thinking even on projects that will run for months or years — a strange kind of short-termism, given the stakes.

Part of this is fear of the scale of the problem. There's a story about Kahneman and Tversky planning to write a textbook together. They thought it would take a year or two. It took six. Afterwards they surveyed other textbook authors and found the average estimate, going in, was about ten years. Had they known that at the start, they might never have begun.

I think many of us avoid fully understanding what a piece of work involves for exactly this reason: we're afraid that if we saw the real scale of it, we wouldn't start. I don't think that fear is justified. But it sits in the background all the same.

It forces choices, and the choices expose misalignment

A good SCQH is concise. That means deciding what's actually relevant and what isn't — you can't write a good Situation-Complication for "how do we make money?" without narrowing it down to what's really going on. Making those choices exposes your assumptions about how the world works and what actually matters.

This is the deepest layer, and the most important one. In my experience — especially in nonprofits — the hard part of strategy is rarely the intellectual work of laying out the situation and the complication. The hard part is that a group doing this properly discovers it doesn't agree on the goal.

Staying vague lets everyone keep doing their own thing. Nobody has to reconcile their different theories of change, their different priorities, their different implicit goals. Getting precise forces coherence — and cohering is painful.

I know a funder in our field with something like a hundred million dollars in capital. They've been in a strategic planning process for three or four years. They haven't distributed grants at any scale. Their CEO left. Their strategy is still, in effect, "increase love in the world" — no operational substance at all. That's not a lack of capability. That's the discomfort of precision, playing out at scale.

The same thing happens with metrics

The same is true with metrics. People often avoid clear metrics not because they dislike measurement, but because metrics create the possibility of failure. We easily confuse failing to achieve a goal with being a failure. That ontological confusion creates enormous resistance to the very practices that improve performance.

If my goal is to jump two metres and I clear one metre ninety, that's a performance failure — I didn't hit the target. The ego turns this into "I am a failure." Those are completely different claims, and most resistance to metrics comes from confusing them.

There is huge untappted potential

Ironically, this means that organisations systematically underinvest in exactly the work that would make them dramatically more effective. They sacrifice years of execution because they are unwilling to spend days thinking clearly.

And AI can help

The opportunity is obvious. If we can make these disciplines easier and more accessible—using AI where appropriate—we can create a substantial benefits. The challenge is not primarily technical. It is helping people overcome the psychological and organisational resistance to clarity.

Appendix: Adoption is subtler than I used to think

Not everyone who resists this has an ontological problem with it. Some people just aren't lit up by it the way I am. I get excited about designing the playbook — working out what actually lets the team win. Other people get excited by getting onto the field, encouraging the players, moving things forward. Both are needed. But it means you can't assume shared enthusiasm just because someone sees the value, and after years of bringing issue trees and SCQHs into meetings and watching them not land, I've mostly stopped.

At Life Itself we had SCQHs and issue trees in the loop back in 2017, 2019. Over time they mostly disappeared — not because anyone decided they didn't work, but because it was hard to keep insisting on them.