- Formulation of goals
- Formulation of models AND gather of information
- Prediction and extrapolation
- Planning of actions, decision making and execution
- Review of effects and revision
This is a great model for several reasons, but the most important thing that Doerner has in his model that is left out of many other models is the first element in the second step: the formulation of, exactly, a model. It is essential to problem solving, and far too little time is usually spent on it — because it is hard.
So what does it mean to develop a model? Let’s look at a practical problem. Let’s assume that I want to win an election. That is my goal. Now, what has to happen next is not that I run out and look at stats and opinion polls and good knows what, but rather that I agree with my team on how elections are won. What is the model we are working with? Do we believe that the electorate consists of three different categories of votes, for example? Right, swing and left? If so, do we care about the left and right or only the swing vote? How do we think someone decides if they are a swing voter? What matters most? If one member of the team thinks it is about the appearance of winning (i.e. the sharp jaw, the great hair) and another thinks it is the issues, and specifically the economy their gathering of information and planning will look very different. If it is a little bit of both, maybe that is a good thing to agree on too.
A weak model will almost guarantee a weak outcome. If you want to beat a chess master or a karate fighter your model will be chess or karate as a formal system, and you will try to figure out if they favor an opening or a special kick through gathering information. You will not expect the chess player to kick you, or the karate fighter to move his queen.
Yet still many people have only very hazy models of what the game they are playing looks like. So a new generation of problem solvers have recommended that you think about your problem as a game. What does playing the game look like? How do you win? How do you keep score? Any more complex problem deserves being turned into a game if for no other reason than the utility in showing you your model, and examining it with others.
Whether you do it by formal gamestorming or just by thinking about this as a systems science challenge (as in systems thinking) does not really matter, I think. But being explicit about my models is one of the things I am working hard on – and I think an exciting thing to think about.
A classical example of model failures is perhaps found in politics. It is the case where someone believes that they are right on the substance, and cannot understand why the system still comes to the wrong conclusion. When that happens frustrations ensues and people start calling each-other names, claim that they are irrational or evil. But that is rare. It is far more common that people have different models of reality than that they share your model and are evil.
Model disconnect is probably a very common phenomenon, and a very upsetting one. I can think of several examples of this in economics, climate change and information policy that would do well from recognizing that.
Perhaps we should introduce a new foul in the theory of rational argument? Just as we have outlawed argumentum ad hominem we could introduce argument from different model as a foul – but for both parties.
If they do not agree on the model, well, then they are not really arguing at all. They are just loudly misunderstanding each-other.
There is a lot of that, though, I fear.