Economics Had to Change Its Mind About People. Organisational Design Is Still Catching Up.

In short: we write policies, targets and delegations for a person who reads them as intended and acts on their spirit. That person doesn't exist, and the distance between them and the people we actually employ is where a great deal of organisational trouble starts. Economics spent a century making the same mistake before it corrected course.

This is the idea underneath why capable teams get bogged down — the long version of why the systems around good people so often work against them.

In 1979 two psychologists published a paper in Econometrica, the most technical journal in economics, telling the discipline it was wrong about people.

Daniel Kahneman and Amos Tversky weren't economists. Their argument was that the rational actor at the centre of economic theory — the one who weighs all available information and reliably chooses the optimal outcome — didn't correspond to any human being they had ever tested. Real people, they showed, feel losses far more sharply than equivalent gains. They answer differently depending on how a question is framed. They take the default. They are systematically, predictably strange about risk.

Economics did not rush to agree. Kahneman received the Nobel for that work in 2002, twenty-three years later. Tversky had died in 1996 and the prize isn't awarded posthumously, so Kahneman accepted it alone and spent the rest of his life pointing out that the work had been joint.

Twenty-three years is a long time for a discipline to accept something it can test.

Why a serious field held on so long

The interesting question isn't why they were wrong. It's why the correction was so slow — and the answer isn't stubbornness.

The rational actor wasn't decoration. It was load-bearing. Assume people optimise, and you can model markets mathematically, prove things, and make predictions. Assume instead that people are loss-averse and framing-sensitive and inclined to take whatever's in front of them, and the mathematics gets very hard very quickly. Giving up the model meant giving up tractability.

So the profession did what any of us would do. It kept the assumption that made the work possible and treated the anomalies as noise — special cases, poor experimental design, interesting but peripheral. That held until the anomalies stopped being peripheral.

What eventually changed things wasn't a better argument. It was that the exceptions accumulated until the model couldn't hold them, and the field had to choose between its assumptions and its evidence.

We design organisations the same way

Every policy, every delegation, every performance measure is written with a person in mind. That person reads the policy and applies it in its spirit. They understand what the KPI stands for and pursue that, not the number. They know when a procedure was never meant for the case in front of them, and they use judgement accordingly.

That is the assumption economics had to give up, and we are still making it. We hand our systems to real people — who are busy, who are accountable, who would rather not be the only name on a decision that goes badly, and who respond to what a rule actually rewards rather than what it was intended to achieve.

Take the most ordinary example there is. You add a second sign-off to catch a rare serious error. The intention is a safety check. What you have actually created is a way for anyone to get another name onto an ordinary decision — and since being wrong is visible and personal while being slow is diffuse and belongs to nobody, people use it for exactly that. Not through cynicism. Because you have made it the sensible thing to do.

Nobody designed that outcome. Everybody produces it.

And we do the same thing economics did with the anomalies: we file it under execution. The transformation didn't land because change management was weak. Engagement is down because leadership needs work. The new process isn't being followed because people need training. Each explanation preserves the model of the person and blames the implementation. It is a great deal more comfortable than concluding that we designed the system for someone who was never going to turn up.

What the correction would actually involve

Behavioural economics didn't fix its problem by declaring people irrational — that's the caricature, not the work. What it did was more disciplined: it stopped assuming how people would respond and started testing it, then built the findings back into the models.

The organisational equivalent isn't complicated to state. Before you introduce a rule, a target or an approval step, ask what it will actually reward — not what it is meant to encourage, but what the fastest, safest, most defensible response will be for the person who has to live with it. Someone stretched thin, short of time, carrying a dozen other things that day, and reasonably keen not to be the name on a decision that goes badly. Then assume you'll get that, because you will.

That's the whole of it, and it's harder than it sounds, because it requires designing for the people you actually employ rather than the ones the policy imagined.

My own interest is narrower. The behavioural work that has reached a wide audience points outward — nudge units and behavioural insights teams, doing careful things with defaults, framing and form design, aimed at citizens and customers. What interests me is the machinery pointing inward: the delegations, the sign-offs, the performance measures that decide whether a capable person feels able to make a call. In every organisation I've worked in, those were still written for the compliant idealised officer.

The thing I look at first there is decision-making speed. Not because speed matters more than judgement, but because it's the most honest available signal that the incentives have come apart. When a decision that should take an hour reliably takes three weeks, something in the system is rewarding delay, and the elapsed time is the visible edge of it. I call that resistance decision friction, and it's usually findable in specific places rather than spread everywhere at once.

Arriving from other directions

Gary Hamel and Michele Zanini have written about the cost of bureaucratic drag and reached conclusions that overlap with mine from a different direction. Amy Edmondson's work on psychological safety measures one of the conditions I care most about. Organisational economists have formal results showing that where only some tasks can be measured, incentives on the measured ones crowd out the rest.

When several people working independently, from different disciplines and different starting points, keep arriving at the same conclusion about how organisations behave, the sensible reading is that the conclusion is about organisations rather than about any one of us. A field corrects when the anomalies accumulate. They are accumulating.

Where I'd differ from the general version is in scope. This doesn't require a transformation programme or a new operating model. It requires finding the specific places where your own rules are producing behaviour you never asked for, and changing those. That's a much smaller piece of work than it sounds, and a much more targeted one.

There is a version of this you can try on any rule in your own organisation — one of the ones everybody follows and nobody defends. Don't ask whether it's necessary; that only invites a defence. Ask what it actually rewards, for the person who meets it on an ordinary Tuesday with too much else on. Most of the time the answer is not what anyone intended, and never was.

That gap — between what a rule was for and what it actually produces — is where this work lives.