Less Is More

Less Is More

The less-is-more idea in decision making can be traced to Spyros Makridakis, Robyn Dawes, Dan Goldstein, and Gerd Gigerenzer, who have all found in various contexts that simpler methods for forecasting and inference can work much, much better than complicated ones. Their simple rules of thumb are not perfect, but are designed to not be perfect; adopting some intellectual humility and abandoning the aim at sophistication can yield powerful effects. The pair of Goldstein and Gigerenzer coined the notion of “fast and frugal” heuristics that make good decisions despite limited time, knowledge, and computing power.

I realized that the less-is-more heuristic fell squarely into my work in two places. First, extreme effects: there are domains in which the rare event (good or bad) plays a disproportionate share and we tend to be blind to it, so focusing on the exploitation of such a rare event, or protection against it, changes a lot of the risky exposure. Just worry about Black Swan exposures, and life is easy.

A complex system, contrary to what people believe, does not require complicated regulations and intricate policies. The simpler, the better. Complications lead to multiplicative chains of unanticipated effects. Because of opacity, an intervention leads to unforeseen consequences, followed by apologies about the “unforeseen” aspect of the consequences, then to another intervention to correct the secondary effects, leading to an explosive series of branching “unforeseen” responses, each one worse than the preceding one. Yet simplicity has been difficult to implement in modern life because it is against the spirit of a certain brand of people who seek sophistication so they can justify their profession. Heuristics are simplified rules of thumb that make things simple and easy to implement. But their main advantage is that the user knows that they are not perfect, just expedient, and is therefore less fooled by their powers. They become dangerous when we forget that.

Less is more has proved to be shockingly easy to find and apply—and “robust” to mistakes and change of minds. There may not be an easily identifiable cause for a large share of the problems, but often there is an easy solution (not to all problems, but good enough; I mean really good enough), and such a solution is immediately identifiable, sometimes with the naked eye rather than the use of complicated analyses and highly fragile, error-prone, cause-ferreting nerdiness.

Some people are aware of the eighty/twenty idea, based on the discovery by Vilfredo Pareto more than a century ago that 20 percent of the people in Italy owned 80 percent of the land, and vice versa. Of these 20 percent, 20 percent (that is, 4 percent) would have owned around 80 percent of the 80 percent (that is, 64 percent). We end up with less than 1 percent representing about 50 percent of the total. These describe winner-take-all Extremistan effects. These effects are very general, from the distribution of wealth to book sales per author.

Few realize that we are moving into the far more uneven distribution of 99/1 across many things that used to be 80/20: 99 percent of Internet traffic is attributable to less than 1 percent of sites, 99 percent of book sales come from less than 1 percent of authors … and I need to stop because numbers are emotionally stirring. Almost everything contemporary has winner-take-all effects, which includes sources of harm and benefits. My claim is that, when vulnerabilities are this concentrated, 1 percent modification of systems can lower fragility (or increase antifragility) by about 99 percent—and all it takes is a few steps, very few steps, often at low cost, to make things better and safer.

For instance, a small number of homeless people cost the states a disproportionate share of the bills, which makes it obvious where to look for the savings. A small number of employees in a corporation cause the most problems, corrupt the general attitude—and vice versa—so getting rid of these is a great solution. A small number of customers generate a large share of the revenues. I get 95 percent of my smear postings from the same three obsessive persons, all representing the same prototypes of failure (one of whom has written, I estimate, close to one hundred thousand words in posts—he needs to write more and more and find more and more stuff to critique in my work and personality to get the same effect). When it comes to health care, Ezekiel Emanuel showed that half the population accounts for less than 3 percent of the costs, with the sickest 10 percent consuming 64 percent of the total pie. Bent Flyvbjerg showed in his Black Swan management idea that the bulk of cost overruns by corporations are simply attributable to large technology projects—implying that that’s what we need to focus on instead of talking and talking and writing complicated papers.

As they say in the mafia, just work on removing the pebble in your shoe.

There are some domains, like, say, real estate, in which problems and solutions are crisply summarized by a heuristic, a rule of thumb to look for the three most important properties: “location, location, and location”—much of the rest is supposed to be chickensh*****t. Not quite and not always true, but it shows the central thing to worry about, as the rest takes care of itself.

Yet people want more data to “solve problems.” I once testified in Congress against a project to fund a crisis forecasting project. The people involved were blind to the paradox that we have never had more data than we have now, yet have less predictability than ever. More data—such as paying attention to the eye colors of the people around when crossing the street—can make you miss the big truck. When you cross the street, you remove data, anything but the essential threat.1 As Paul Valéry once wrote: que de choses il faut ignorer pour agir—how many things one should disregard in order to act.

Convincing—and confident—disciplines, say, physics, tend to use little statistical backup, while political science and economics, which have never produced anything of note, are full of elaborate statistics and statistical “evidence” (and you know that once you remove the smoke, the evidence is not evidence). The situation in science is similar to detective novels in which the person with the largest number of alibis turns out to be the guilty one. And you do not need reams of paper full of data to destroy the megatons of papers using statistics in economics: the simple argument that Black Swans and tail events run the socioeconomic world—and these events cannot be predicted—is sufficient to invalidate their statistics.

We have further evidence of the potency of less-is-more from the following experiment. Christopher Chabris and Daniel Simons, in their book The Invisible Gorilla, show how people watching a video of a basketball game, when diverted with attention-absorbing details such as counting passes, can completely miss a gorilla stepping into the middle of the court.

But simplicity is not so simple to attain. Steve Jobs figured out that “you have to work hard to get your thinking clean to make it simple.” The Arabs have an expression for trenchant prose: no skill to understand it, mastery to write it. What I propose is a road map to modify our man-made systems to let the simple—and natural—take their course.

I discovered that I had been intuitively using the less-is-more idea as an aid in decision making (contrary to the method of putting a series of pros and cons side by side on a computer screen). For instance, if you have more than one reason to do something (choose a doctor or veterinarian, hire a gardener or an employee, marry a person, go on a trip), just don’t do it. It does not mean that one reason is better than two, just that by invoking more than one reason you are trying to convince yourself to do something. Obvious decisions (robust to error) require no more than a single reason. Likewise the French army had a heuristic to reject excuses for absenteeism for more than one reason, like death of grandmother, cold virus, and being bitten by a boar. If someone attacks a book or idea using more than one argument, you know it is not real: nobody says “he is a criminal, he killed many people, and he also has bad table manners and bad breath and is a very poor driver.”

I have often followed what I call Bergson’s razor: “A philosopher should be known for one single idea, not more” (I can’t source it to Bergson, but the rule is good enough). The French essayist and poet Paul Valéry once asked Einstein if he carried a notebook to write down ideas. “I never have ideas” was the reply (in fact he just did not have chickens***t ideas). So, a heuristic: if someone has a long bio, I skip him—at a conference a friend invited me to have lunch with an overachieving hotshot whose résumé “can cover more than two or three lives”; I skipped to sit at a table with the trainees and stage engineers.2 Likewise when I am told that someone has three hundred academic papers and twenty-two honorary doctorates, but no other single compelling contribution or main idea behind it, I avoid him like the bubonic plague.

1 Recall that the overediting interventionist missed the main mistake in Chapter 7. The 663-page document Financial Crisis Inquiry Report by the Financial Crisis Inquiry Commission missed what I believe are the main reasons: fragility and absence of skin in the game. But of course they listed every possible epiphenomenon you can think of as cause.

2 Even the Nobel, with all its ills of inducing competition in something as holy as science, is not granted for a collection of papers but rarely for more than a single, but major, contribution.