Engineers and others attracted to comprehensive systems views often fail in a predictable way: they translate all their objectives into multi-factor optimization models and trade-off curves which then yield spectacularly mediocre results. I commented on this pathology as part of a recent answer to a question about choosing among multiple job offers on Quora and I figured I should generalize that answer.
Why is this a failure mode? Optimization is based on models, and this failure mode has to do with what you have left out of your model (either consciously or due to ignorance or a priori unknowability). If there are a couple of dozen relevant variables and you build a model that uses a half-dozen, then among those chosen variables, some will have more coupling to variables you’ve left out than others. Such variables serve as proxies for variables that aren’t represented in your model. I’ll overload a term used by statisticians in a somewhat related sense and call these variables fertile variables. Time is a typical example. Space is another. Money is a third, and particularly important because ideological opinions about it often blind people to its fertile nature. Physical fitness is a fourth.
Fertile variables feed powerful patterns of action based on what I will call rich moves.
In complex situations, where you suspect you’ve left out more than you’ve included in your models, it is very useful to decide what to do purely in terms of fertile variables, maximizing or minimizing them in some way. This goes against the instincts of most modelers, who want to build complicated multi-factor formulas based on multivariate models.
A move based primarily on manipulating a fertile variable while neglecting others is what I call a rich move. The prototypical example from which I derive the term is to decide you simply want to get rich, no matter how, and ignoring other aspects of a “well-rounded” life.
This is because if you succeed in this “rich” move, other problems will tend to sort themselves out. Once you are rich for example, you can hire a personal trainer and personal chef to take care of your health. And this is not just an arrival fallacy of the “life will be better once I am rich” sort. I know many rich people who’ve done exactly this, and are now healthy and happy. Yes, money can buy happiness if used properly. It is a fertile proxy variable for most variables involved in the murky and hard-to-model idea that is happiness. There is plenty of research showing that money does not increase happiness beyond a point, but I suspect that’s because most people don’t know how to use it. I know enough rich people who are far above the “happiness plateau” threshold (about $60,000 or so in income per year in the US if I recall correctly; I forget where I heard the figure) and also much happier than regular 60k/year schmucks, because they know how to deploy the money very effectively (so it is partly a matter of spending skill, which most of us don’t acquire because we don’t get enough practice).
Another example, if you are in the technology sector, is deciding to move to San Francisco. It moves one variable (or rather 2: latitude and longitude) without much thought to other variables like cost of living, closeness to markets and so forth.
How Rich Moves Work
In formal mathematical modeling, you often start with higher-order models involving dozens or even hundreds (in the case of computer-aided models) of variables and reduce them to lower-order ones using systematic techniques (if you are interested, they have names like “balanced model order reduction” and involve advanced mathematical techniques such as singular value decomposition).
But far more often, your modeling uncertainty is unknown-unknown. You don’t know what you left out, let along consciously and carefully doing the pruning.
For such situations, the behavior of your model in practice will yield hints about what you don’t know, because some variables will seem to have impact beyond what your model predicted.
The key to identifying and pursuing action patterns built around rich moves is to resist the temptation to maximize learning. The actions that help you learn fastest (and therefore build out and complicate your model the fastest) are generally not the same as the ones that help you gain rewards fastest. The reverse is often true. Rich moves may allow you to further simplify the models you already have.
Rich moves, rather than maximizing learning, herd the most variables into positive regions. Moving to San Francisco also gets you good weather, great food, close access to great natural beauty, a good deal of cultural diversity, other talented people, great universities and so forth. Yes, you also get earthquake risk and a certain amount of groupthink and cultural smugness, but overall “move to San Francisco” moves far more variables into the right regions than into the wrong regions for someone who wants to build great technology.
On the other hand, if you want to actually understand how the world of technology works (learn the best possible model), spending too much time in San Francisco can be very dangerous. You go to San Francisco to get rich off technology, not to understand it better. This is one reason I’ve not (well, not yet anyway) moved to San Francisco. I am more interested in understanding technology than getting rich off it. I’ve found some of the best insights into the nature of technology in strange and obscure corners of the world.
Here are some common examples of fertile variables and rich moves:
- In physical fitness, treating each muscle as a variable, a few are far more fertile than others (chest, back, thighs) and exercising them using rich moves (benchpress, military press, squats) yields dividends far faster than other more complicated moves.
- In jobs, your manager is a fertile variable (based on Gallup research). If you have a great relationship with a great manager, most other problems will sort themselves out. So a rich move is to find a job where you’ll be reporting to a great manager.
- In life in general, money is a rich variable, as I’ve already said. But due to its artificial nature, it comes with many weird traps that you have to be wary of.
- In decision-making, tempo is a fertile variable. While driving tempo up is not always a bright idea, generally iterating faster improves a lot of things.
- In healthy eating, proteins and green vegetables appear to be rich variables, but I am a little bit more doubtful here, and don’t know enough to make strong claims.
- In the world of languages, knowing English is a fertile variable. Moving to an English-speaking country is a rich move. Or used to be.
- In mental development, some (appreciative, not just manipulative) knowledge of college-level mathematics is a fertile variable. People who know a certain amount of mathematics in the right way, generally think better on all questions, including ones involving no mathematics (the pathology I pointed out at the start of this post is the sort of danger that mathematical knowledge can bring; the key is to develop an appreciative understanding of mathematics alongside a manipulative one). A fertile move for any student is to move to an environment with a lot of good mathematics in the environment. So educational settings that lack mathematics are dangerous.
What other fertile variables and rich moves do you know of?