What problem are you trying to solve?

Legend says Isaac Stern was once confronted by a middle-aged lady after a concert. She gushed “Oh, I’d give my life to play like you!”

“Lady”, said Stern acidly, “That I did!”

In 1965, Adriaan de Groot did a series of experiments with chess players of various levels. He found out that the experts could see patterns of play that would work even before actually consciously thinking about them. After practicing for many years and over thousands of games, many patterns became second nature to the experts.

In an interview for the Harvard Business Review, the climber Alex Honnold also mentions having to learn to think in patterns. He comments on the above research on chess grandmasters and explains how he remembers large blocks of sequences in a climb. Because of this work, he said he has all of El Capitan’s 3,000 foot climb memorized.

What these stories have in common are the years of practice people put into their craft to get better at it. We have decades of evidence and research showing us that it is not years of experience but of deliberate practice that leads us to better problem solving skills. See, for example, the works by Pólya 1945, Adriaan de Groot linked above, Hamming 1997, Ericsson 2008, and Clear 2018.

But could this approach of practice and repetition work for every problem? The folks at The FLUX Review don’t think so. They talk about two classes of problems. The first one, they argue, can be better handled with practice: better skills, more experience and by staying focused. According to them, this is the case for problems in domains like chess, math, or software engineering.

There is a second class that “feels different, more slippery, harder to define.” They put in this class the problems related to management. No two problems in this class are the same so it is hard to get more efficient at dealing with them. The authors call them unsolvable because there won’t be a solution for these in the concrete sense that there is, say, for software engineering problems.

Back in 1973, Rittel and Webber called these unsolvable problems wicked. In contrast, they defined the problems of a chess player or those in engineering as tame because their mission is clear and their solutions are well-defined. A best answer is possible in tame problems. But wicked problems have none of those traits. We often can’t even clearly define such problems, or their definition will change with the context or depending upon whom you ask.

Perhaps it is easier to exemplify this lack of clarity in wicked problems with two stories. The first is an old parable that you may have heard before. Here is how Richard Hamming tells it in his book The Art of Doing Science and Engineering:

A man was examining the construction of a cathedral. He asked a stone mason what he was doing chipping the stones, and the mason replied, “I am making stones”. He asked a stone carver what he was doing, “I am carving a gargoyle”. And so it went, each person said in detail what they were doing. Finally he came to an old woman who was sweeping the ground. She said, “I am helping build a cathedral”. (p. 195)

Wicked problems have no definitive formulation. In the parable above, are we trying to make stones as cheaply as possible, to carve the best gargoyle possible, or to finish the cathedral on time? Wicked problems have no “true-or-false” solutions but a fuzzy and contextual “good-or-bad” scale. For whom will the cathedral be good? Each wicked problem is unique and we often have only one shot at solving it. We can’t build two cathedrals at the same time and in the same place to compare which one is better. And they have no stopping rule. The Sagrada Família is still under construction 140 years after it began.

Another way to look at it is through the lens of Chesterton’s Fence, our second story. Here is how it goes:

There exists in such a case a certain institution or law; let us say, for the sake of simplicity, a fence or gate erected across a road. The more modern type of reformer goes gaily up to it and says, “I don’t see the use of this; let us clear it away.” To which the more intelligent type of reformer will do well to answer: “If you don’t see the use of it, I certainly won’t let you clear it away. Go away and think. Then, when you can come back and tell me that you do see the use of it, I may allow you to destroy it.

If we are in the midst of the grind, busy with our day-to-day work, it is easy to miss the forest for the trees and to come up with a solution to a symptom or to a smaller part of the problem. If we don’t realize we are dealing with a wicked problem, it is easy to fall into the trap of trying to brute force our way out, and to fix it as if it were tame. But this may only create more problems. As Donald Norman puts it in his book The Design of Everyday Things, “a brilliant solution to the wrong problem can be worse than no solution at all” (p. 218).

Instead, the actual solution to dealing with wicked problems is unintuitive. The FLUX Review folks suggest that “rather than continue to run in the same direction, we need to sit with it.” This means slowing down and taking our heads out of the sand to look at what is around us. Rather than try to solve any immediate hardship we are facing, we should instead try to understand the problem. To Rittel and Webber, somewhat paradoxically, doing so will lead us to a solution for it:

If we can formulate the problem by tracing it to some sorts of sources — such that we can say, “Aha! That’s the locus of the difficulty,” i.e. those are the root causes of the differences between the “is” and the “ought to be” conditions — then we have thereby also formulated a solution. To find the problem is thus the same thing as finding the solution; the problem can’t be defined until the solution has been found. The formulation of a wicked problem is the problem! (p.161)

To do this intertwined work of defining the problem and finding a solution, we need to take the time to process crucial information. Otherwise, we risk overloading our brains and making mistakes. Adam Robinson lists seven factors that are detrimental to solving wicked problems. These are:

  • being outside of your circle of competence,
  • stress,
  • rushing or urgency,
  • fixation on an outcome,
  • information overload,
  • being in a group where social cohesion comes into play, and
  • being in the presence of an “authority.”

The first thing this list tells us is that we can’t get away with not getting better at solving the tame type of problems for the domain we work in. If I don’t have a clue about how to play chess, pausing and relaxing won’t help me much to play my next move. The second thing it tells us is that competence alone is not enough. The context in which we find ourselves matters for an effective resolution of the wicked problem, because it can play a role in the above factors.

And while some of these factors are in our control, others may be prevalent in our organizations or in society at large. Even if we can’t control these factors, being aware of them helps. If we need to solve a wicked problem and we are in the presence of any of them, then we don’t have to try and solve it just yet. We can sit with it first.

Sitting with it gives us time to also address two other factors not on the original list by Adam. These are working in isolation, and misfortune. Working alone on a wicked problem increases our chances of missing crucial information and of not finding the right solution to it. Rittel and Webber hint at this in their paper. They propose “an argumentative process” where critical thinking participation is encouraged in order for an image of the solution to gradually emerge.

As for misfortune, we can’t control it but we can reduce its chances — or increase our chances of getting lucky. Taylor Pearson argues that we can do this by shifting our focus from finding a breadth of solutions to focusing on a smaller subset of them with a higher chance of exponential success. For example, when looking to promote his book, Taylor spent about 50% of his marketing resources on 1% of the potential readers he deemed most important. He says two email responses he got out of this effort accounted for over half of his book’s sales. We might say it’s luck, but he focused his resources to significantly increase his chances of getting lucky.

For others to help him promote his book, it had to first have its merit. This shift to increase our chances of getting lucky is not a hack to avoid getting better at what we do. What it means is that we have to continue to get better AND we have to make sure we tell the right audience about it. To Jason Roberts, if we plot how well we do something and how effective we are at telling others about it, we increase the “surface area” of our luck.

In her book Thinking in Bets, Annie Duke states quite powerfully that there are exactly two things that determine the outcomes in our lives: the quality of our decisions, and luck. That means we are not playing a game of chess in life, but one of poker. Winning at chess is a tame problem, where the best decision can be derived by the current state of the game. Winning at poker is a wicked one.

John von Neumann explained the difference between the two games to Jacob Bronowski as follows:

“‘Chess is not a game. Chess is a well-defined form of computation. You may not be able to work out the answers, but in theory there must be a solution, a right procedure in any position. Now, real games,’ he said, ‘are not like that at all. Real life is not like that. Real life consists of bluffing, of little tactics of deception, of asking yourself what is the other man going to think I mean to do.’”
(The Ascent Of Man, p. 432)

John realized that the situations we encounter in real-life do not have the precise solutions that chess or engineering do. That is, what does “winning” the game mean for the problems we are dealing with? Are we trying to make stones as cheaply as possible, to carve the best gargoyle possible, or to finish the cathedral on time? Knowing what problem we are trying to solve will help us determine the right actions to take and increase our chances of actually solving it.

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Ricardo Lage

Ricardo Lage

Building products. PhD in machine learning. Currently leading the engineering efforts to grow BlaBlaCar Daily, BlaBlaCar's commute carpooling service.