The “Mathematics” of the Doom Loop!

Believe it or not, the “Doom Loop” rests on a pretty solid mathematical foundation!

One has to be creative, however, and perhaps a little abstract to see the connection.  After all, we’re dealing with “Qualitative Data” and applying it to a “Quantitative analysis.”  So keep that in mind.

Start by assuming that any individual may be described by a mathematical equation.

This means:

A Person = f(x,y,z,a,b,c, . . . lots and lots of variables . . . “Preferences,” “Performance”).

This means that the person is a function of a LOT of variables plus two key variables which we will use in the analysis of “Preferences” (like/don’t like) and “Performance” (good at/not good at).

As we can in virtually any mathematical equation that has many variables, we can hold many of the variables CONSTANT and see what happens to the equation over time by just looking at one or two variables that are NOT CONSTANT.

That is what the “Doom Loop” does.

We hold all of the individual’s variables (his/her favorite color, favorite movie, etc., etc., etc., and anything else you can think of) CONSTANT and look only at what happens when Preferences and Performance vary over time.  In a sense, we are doing partial differential equations – differentiating preference and performance over time.

The result – while we cannot actually put quantitative numbers to it – is the “Doom Loop.”  The curve goes up while the individual is learning and still likes what he/she is doing, levels off as the learning is complete, and then begins to fall down as time goes on and he/she gets bored with the work.

Where the “slope of the curve” is zero, i.e., at the top of the curve, the individual is “Doomed.”

It’s a fun way to think about what is going on!