Munger's mental models #2: Being approximately right (not precisely wrong)

Mental models

In this short series of blogs and videos, in honour of the late Charles Munger, I take a look at some of his most powerful mental models.

Being approximately right

John Maynard Keynes once said that he'd rather be approximately right rather than being precisely wrong.

Just because you can easily attach numbers to an investment or a business strategy, doesn't mean it's a good idea.

For example, a factory or property generating a yield of 9% is not necessarily a good investment opportunity.

You need to think about how the investment will look a decade from now, what type of tenants you can expect to attract, the potential for rental price growth and vacancy periods, the prospects for local economic growth, how reliable the local property managers are, flood risk, and so on.

You might not be able to answer all of these questions accurately, but at least you'll be asking the right questions.

In this case, being directionally right is much more important than focussing on a specific number at a point in time.

Pick a simple strategy that allows for you being basically right, rather than relying on one that required exact predictions or timing. 

Accuracy matters

It’s simple enough to build “as if” models that make forecasts into the future, and these may be alluring because they can give precise inferences about the future.

There’s just one problem: the real world gets in the way, and the assumptions often don’t hold up in real life situations.

The future is inherently uncertain, so models and forecasts need to be questioned,  because the more you know, the more you don’t know (which is an important distinction).

Rather than precise projections, the most important thing is a high level of accuracy in asking and then answering the right questions.

It’s clear, then, that getting hung up on precise metrics and values can be self-defeating and isn’t time well spent…so what is?

Predictions

Buffett once said that if their predictions had been better than those of others, it because they tend to make fewer of them.

As the old saying goes, predictions are very tricky to make, especially if they're about the future.

Tips for the future

Asking the wrong questions can be as bad as doing no research at all, so here are 3 questions that you should ask:

(i) Actions not words – will people actually do what they say they will? All too often, they don’t!;

(ii) Gut feel – what do your instincts tell you? Gut feel may be no replacement for hard information, but unconscious responses can also be a useful sense-checking tool; and

(iii) What if…? – what might happen instead if the models and forecasts are wrong?

Don’t sacrifice accuracy for illusory precision, and be prepared to update your views as new information comes to light.

To paraphrase Aristotle and Keynes, it is better to be approximately right than precisely wrong!

I discussed this a little further in the short video below:

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