To illustrate, I'm going to use a forecasting tool called Scenario Planning to determine my chances of dating Milla Jovovich.
First we must figure out the causal structure of the scenario. The desired event, "Milla and I live happily ever after," we denote by $M$. Using my subject matter expertise on human relationships, I postulate that $M$ depends on a conjunction of two events:
- Event $P$ is "Paul Anderson – her husband – runs away with a starlet from one of his movies"
- Event $H$ is "I pick up the pieces of Milla's broken heart"
So the scenario can be described by $P \wedge H \Rightarrow M$. And probabilistically,
$\Pr(M) = \Pr(P) \times \Pr(H).$
Now we can use information from the philandering of movie directors and the knight-in-shining-armor behavior of engineering/business geeks [in Fantasyland, where Milla and I move in the same circles] to estimate $\Pr(P) =0.2$ (those movie directors are scoundrels) and $\Pr(H)=0.1$ (there are other chivalrous nerds willing to help Milla) for a final result of $\Pr(M)=0.02$, or 2% chance.
Of course, scenario planning allows for more granularity and for sensitivity analysis.
We could decompose event $P$ further into a conjunction of two events, $S$ for "attractive starlet in Paul's movies" and $I$ for "Paul goes insane and chooses starlet over Milla." We could now determine $\Pr(P)$ from these events instead of estimating it directly at 0.2 from the marital unreliability of movie directors in general, using $\Pr(P) = \Pr(S) \times \Pr(I).$
Or, going in another direction, we could do a sensitivity analysis. Instead of assuming a single value for $\Pr(P)$ and $\Pr(H)$, we could find upper and lower bounds, say $0.1 < \Pr(P) < 0.3$ and $0.05 < \Pr(H) < 0.15$. This would mean that $0.005 < \Pr(M) < 0.045$.
Of course, if instead of the above interpretation we had
- Event $P$ is "contraction in the supply of carbon fiber"
- Event $H$ is "increase in the demand for lightweight camera tripods and monopods"
- Event $M$ is "precipitous increase in price and shortages of carbon fiber tennis rackets"
the same scenario planning would be used for logistics management of a sports retailer provisioning.
Which brings us to the three different competencies needed for scenario planning, and more generally, for thinking about something:
Thinking skill is, in this case, knowing how to use scenarios for planning. It includes knowing that the tool exists, knowing what its strengths and weaknesses are, how to compute the final probabilities, how to do sensitivity analysis, and other procedural matters. All the computations above, which don't depend on what the events mean are pure thinking skill.
Subject matter expertise is where the specific elements of the scenario and their chains of causality come from. It includes knowing what to include and what to ignore, understanding how the various events in a specific subject area are related, and understanding the meaning of the events (as opposed to just computing inferential chains like an algorithm). So knowing that movie directors tend to abandon their wives for starlets allows me to decompose the event $P$ into $S$ and $I$ in the Milla example. But only an expert in the carbon fiber market would know how to decompose $P$ when it becomes the event "contraction in the supply of carbon fiber."
Information, in this case, are the probabilities used as inputs for calculation, as long as those probabilities come from data. (Some of these, of course, could be parameters of the scenario, which would make them subject matter expertise. Also, instead of a strict implication we could have probabilistic causality.) For example, the $\Pr(P)=0.2$ could be a simple statistical count of how many directors married to fashion models leave their wives for movie starlets.
Of these three competencies, thinking skill is the most transferrable: knowing how to do the computations associated with scenario planning allows one to do them in military forecasting or in choice of dessert for dinner. It is also one that should be carefully learned and practiced in management programs but typically is not given the importance its real-world usefulness would imply.
Subject matter expertise is the hardest to acquire – and the most valuable – since it requires both acquiring knowledge and developing judgment. It is also very hard to transfer: understanding the reactions of retailers in a given area doesn't transfer easily to forecasting nuclear proliferation.
Information is problem-specific and though it may cost money it doesn't require either training (like thinking skill) or real learning (like subject matter expertise). Knowing which information to get requires both thinking skill and subject matter expertise, of course.
Getting these three competencies confused leads to hilarious (or tragic) choices of decision-maker. For example, the idea that "smart is what matters" in recruiting for specific tasks ignores the importance of subject matter expertise.*
Conversely, sometimes a real subject matter expert makes a fool of himself when he tries to opine on matters beyond his expertise, even ones that are simple. That's because he may be very successful in his area due to the expertise making up for faulty reasoning skills, but in areas where he's not an expert those faults in reasoning skill become apparent.
Let's not pillory a deceased equine by pointing out the folly of making decisions without information; on the other hand, it's important to note the idiocy of mistaking someone who is well-informed (and just that) for a clear thinker or a knowledgeable expert.
Understanding the structure of good decisions requires separating these three competencies. It's a pity so few people do.
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* "Smart" is usually a misnomer: people identified as "smart" tend to be good thinkers, not necessarily those who score highly on intelligence tests. Think of intelligence as raw strength and thinking as olympic weightlifting: the first helps the second, but strength without skill is irrelevant. In fact, some intelligent people end up being poor thinkers because they use their intelligence to defend points of view that they adopted without thinking and turned out to be seriously flawed.
Note 1: This post was inspired by a discussion about thinking and forecasting with a real clear thinker and also a subject matter expert on thinking, Wharton professor Barbara Mellers.
Note 2: No, I don't believe I have a 2% chance of dating Milla Jovovich. I chose that example precisely because it's so far from reality that it will give a smile to any of my friends or students reading this.
