What The Model Says

What The Model Says: The Strategist’s Guide to Listening to Models, by Mark Chussil

Preamble. This essay is the sequel to All About Models. In that essay we covered several points:

  • Models describe how we believe the world works.
  • Models may be in our heads (mental models) or computer-based.
  • Computer-based models are always based on mental models, though they can calculate more and better.
  • A model is always involved, though perhaps unconsciously, when we say or compute if we do this we will get that.
  • No model is perfect. The test for whether a model is useful is whether we can make a better decision with it than without it.

You don’t have to read that essay before this one, but it wouldn’t hurt. End of preamble.

So you’ve got a model, whether mental or computer-based. Or several models, put forth by several people or several computers. Congratulations! Your brainstorming, calculating, visioning, calibrating, and/or programming has paid off. Now you’re ready to get value and insight.

So, what do you do next? How do you get that value and insight?

Not so fast. It’s not so easy. In fact, you may be shocked a few paragraphs from now.

Before we listen to what a model says, we must figure out whether it speaks well-founded wisdom or well-intentioned folly.

Model V versus Model M

In All About Models I posited two models for a large manufacturing business. Both models acknowledged that our business has high fixed costs and that we must cover our costs to be profitable. They diverged from that point.

  • One model said costs per unit go down as we produce and sell more units, and that selling more units also brings in additional revenue. We’ll call that Model V, for volume.
  • The other model said it’s easier to cover our costs if our prices are high, and that excellent quality and a strong brand give us pricing power. We’ll call that one Model M, for margin.

Model V and Model M could be implemented as computer-based models or remain as mental models. It doesn’t matter right now.

For Model V, “what the model says” is to increase volume. For Model M, “what the model says” is to increase margin. Notice:

By listening to what the model “says,” we listen to the model’s design
at least as much as we listen to the numbers sifting through
our mental or silicon calculators.

We made the most important decision of all when we built the model: we chose which way, volume or margin, is the correct way to think about (i.e., to model) our large manufacturing business. Any subsequent analysis and action issues from that chosen paradigm. If we’ve chosen Model V, for instance, and if our profits underperform, we will look for other ways to boost volume. Why volume? Because the model we adopted, which codified the way we thought, shows us that volume drives profits.

The power to speak

What we hear from the model depends on which model we’ve given the power to speak. Choosing the wrong model messes up a lot, perhaps even everything. (See also Predictable Competitors and Predicting Competitors.)

In this example, neither Model V nor Model M is right. They’re not right because each misses something important, namely, what’s in the other model!

And that’s not all. For example, neither takes competitors’ actions and reactions into account. Sure, your unit sales may go up if you cut your price. But what if competitors cut their prices too? Okay, perhaps total demand will grow. Will it grow enough to compensate for the lower prices? Maybe yes, maybe no. The point is that we won’t even get to that question if our model ignores competitive dynamics.

The situation isn’t necessarily quite as dire as it sounds. We can take dubious, indulgent comfort in the notion that our competitors may make the same mistakes we do. If a whole industry adopts a way of thinking (and many industries do), no single business suffers a competitive disadvantage due to choosing the wrong model. On the other hand, a business could potentially enjoy the benefits of a different model if it can find one. That’s what those upstarts coming out of left field do. That’s what we call “game changing” action. Changing the game means changing our models and starts by changing our minds.

This discussion of Models V and M is highly and vitally practical. But rather than lengthen a series of long essays by reciting my evidence, I’ll just provide a link to real-life war stories. (Look about halfway down that post.) See also the story of Shell that begins Putting the Lesson Before the Test, a chapter from Wharton on Dynamic Competitive Strategy (Day and Reibstein, editors, 1997).

Does it make sense?

There is always a model when we estimate, assert, or calculate that this action will lead to that result.

The challenge in developing an effective strategy begins long before we decide what actions to take and how to execute them. The challenge begins when we decide what model to use. By selecting a model we frame the way we see and evaluate our strategy options.

Prudent strategists want to make sure a model is valid before they select it and thereby entrust their businesses and their careers to its advice. Based on what we’ve discussed about Models V and M, I suggest that “valid” refers first and foremost to whether a model makes sense.

For example:

  • A model that looks only at price does not make sense if customers perceive differences in product or service quality.
  • A model that calculates changes in market share does not make sense if it ignores customer loyalty, inertia, and switching costs.
  • A model that accounts only for our business’ actions does not make sense if we have competitors.
  • A model that extrapolates the past into the future does not make sense if we expect (or want) the future to look different from the past.

And so on. Those statements reflect what ACS calls principles of competition.

Three things to notice about that brief “a model that” list. First, none of those statements is particularly controversial. Second, none of those statements is particularly complicated or arcane. Third, according to those statements many of the models commonly used in strategy development violate the does-it-make-sense criterion.

Sensible models are difficult to handle in our heads, partly because of the arithmetic and partly because of the number of we do this, then that happens, then that, then that, then… connections. That’s why I favor computer-based models for many applications. There are times, though, when computer-based models are overkill or even a distraction.

In my next and final essay in this series, The Model Whisperer, we’ll explore when to use mental and computer-based models. We’ll apply those models in qualitative business war games, quantitative business war games, and strategy decision tests (sometimes called decision tournaments).

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