Decision-makers need an “insight” map, not academic models

Have you noticed how much the business world increasingly talks about “insight’, but in vague, undefined and often murky ways?  The term is becoming ever more common as the perceived value of raw information goes down. What does it mean?

Insight is that flash of recognition when you see something in a fresh way. What seemed murky becomes clear. What seemed confusing now has regularities, or at least patterns. It is about recognition and intuitive understanding of what action needs to be taken.

That’s why I’ve been talking about research into decision-making recently. It isn’t because of academic interest. Decisions are a very practical matter, about specific situations rather than generalities. But for twenty years I saw the brightest policymakers and leading market players make decisions that went terribly wrong. And I noticed when they got things very right.  What made the difference between success and failure?

To answer that you need to recognize the patterns, and that means you need to look at grounded, empirical research.  Of course, experience is essential. But you need to learn the lessons from experience, too.

All research involves taking an abstract step back and trying to find patterns.  The trouble is most academic research in economics and finance is centered around models which seek to explain things in general terms.

But a model isn’t the only way to identify the important features in a situation (despite what many academic economists believe.) In fact, most problems confronting decision-makers are more like “how do I get from A to B” or “What are the major risks just ahead of me and how do I go round them?” For most real problems, a map  is more useful than an abstract model. You can see the lie of the land and where you need to go. You recognize and name the features of the landscape.  You know which direction to head next. That’s what you need if you want to go places.

How is thinking in terms of maps different? Maps retain more useful detail relating to particular purposes and tasks. They are specific about facts on the ground, but they have the right scale and representation of the problem. For example, you use a road map for driving from New York to Boston. It leaves out most of the detail of roads in urban subdivisions or farm tracks, but Interstate 95 is very clear. You use a nautical chart for taking a sailboat into Mystic Harbor.

Models offer generalized “explanation” based on a few easily quantified variables. But if you want to reach harbor safely you are better off with a chart showing the actual, very specific rocks in the channel, instead of a mathematical model of boats.

Maps can show the appropriate scale of detail for the task in hand. They can show shorter routes to your destination. They are less reliant on assumptions. They orient you on the landscape and let you know where you are, even when the outlook is foggy and unclear.  They are traditionally drawn by triangulating from different viewpoints rather than a single perspective.

So I’m looking at research on this blog which helps map the territory, and find the blindspots – the cliffs, the marshes, the six-lane interstates to your destination.  You need to see what people have already observed about the landscape. (The actual reports for clients don’t go into the research, just the results – the map itself, not the why. I just find it fascinating and love writing about it)

Decision-makers are like explorers. You can wander off into the desert yourself. But it helps if you have a map.  Insight means you’ve  recognized how to get to where you want to go.