Consilience

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What is consilience?

Consilience is the concept that evidence from independent and uncorrelated sources can converge to create stronger conclusions.  It’s commonly described as requiring independent methods of measurement.  A simple example is the difference between measuring the distance between two objects with a laser and a tape measure.  If the two measurements are the same you can have a higher degree of confidence the measurement is correct.  If they are not in agreement, the average of the two is your best best.  Adding additional forms of measurement would further increase confidence in the accuracy.

This example is simple enough and probably sounds like overkill.  Why would you measure the living room with more than one form of measurement?  The facts are you wouldn’t.  Units of measure are standardized and reliable which creates a high degree of certainty in your result.  But there’s more to the story.

Combining independent inputs to draw stronger conclusions isn’t relegated to physical measurement.  There are multiple iterations of this concept in the real world decision making and they all lead to stronger results.

Consilience in the Real World

For starters, diversification is the bedrock concept of the wealth and investment management industry.  Simply put, by combining assets that are uncorrelated into the same portfolio investors can create stronger portfolios as measured by return per unit of risk.

Research on high performing teams in a business context indicates that having a team with cognitive diversity results in better performance.   In other words, teams comprised of individuals with different thinking and problem-solving styles outperform those that are more homogenous.  This is having a consilient team.

The Sante Fe Institute (SFI) is a great example of an organization built on a foundation of interdisciplinary thinking.  SFI was founded in 1984 by a group of scientists with the goal of conducting research outside of traditional academic boundaries on what is now known as complexity science.  Coincidentally, just today they posted this article on LinkedIn from Quartz.

“…when it comes to economic forecasting, more and different views are better than those of any one expert.” – Scott E. Page

In a nutshell, the article confirms Phillip Tetlock’s work on the ability of experts to predict (they stink at it) and explains that having more diversity/consilience in the forecasting process would likely improve their accuracy.  Not unlike the research on high performing teams from above.

Still don’t believe the potency of this concept?  Just look at the fintech company Estimize.  Their crowdsourced earnings estimates are more accurate than Wall St >70% of the time.  Given the self-selection bias in the crowd they are sourcing from, I’d bet that increasing diversity would further improve their accuracy.

Getting more Abstract…

Charlie Munger, Warren Buffett’s older, less well known right-hand man has a cult-like following in some circles of the investment world.  His following stems from the unique approach to decision making that he ascribes to: a system of mental models.  A quote from the man himself:

“What are the models? Well, the first rule is that you’ve got to have multiple models because if you just have one or two that you’re using, the nature of human psychology is such that you’ll torture reality so that it fits your models, or at least you’ll think it does…

And the models have to come from multiple disciplines because all the wisdom of the world is not to be found in one little academic department. That’s why poetry professors, by and large, are so unwise in a worldly sense. They don’t have enough models in their heads. So you’ve got to have models across a fair array of disciplines.” – Charlie Munger

Essentially, what Munger’s been doing for decades is putting tools into his problem solving and decision-making toolbox.  Tools that allow him to look at problems from different, uncorrelated angles.   Tools with independent perspectives as to what the correct answer is.  Tools that increase his odds of finding the right answer or best solution.

Summing it up

The takeaway here is clear.  The strength of a conclusion is directly related to how many independent inputs are supporting it.  There are a variety of ways to leverage the mental model of consilience in your own or your organization’s decision making.  The hurdle to doing so is breaking from the status quo, exhibiting patience, and shifting to a longer-term perspective.