THE BLOG
02/07/2017 10:01 am ET

Stop Guessing: An Interview with Nat Greene

Some of my favorite books address decision making and human biases. It turns out that we're generally not very good at making decisions--even relatively simple ones. Indeed, the entire field of behavioral economics is arguably based upon the notion that we're suboptimal and inconsistent decision makers.

Against this backdrop, I recently sat down with Nat Greene, founder of Stroud International and author of Stop Guessing: The 9 Behaviors of Great Problem Solvers.

PS: What was your motivation for writing the book?

NG: There is so much opportunity for better problem-solving in the world. The outcomes of poor problem-solving are visible everywhere, and it drives me nuts to see it. I've spent a long time learning how to approach hard practical problems. That experience has helped me see that most of the hardest problems people face in their lives, businesses, and community can be resolved with simple, elegant solutions. There is incredible opportunity everywhere, and I want to help people realize it.

Until now I have focused on helping large businesses solve very valuable problems, and on coaching a few people in my business to be elite problem-solvers. We've solved problems worth billions of dollars, and problems that have had pretty dramatic impacts on the environment. I am still excited by this. But it also seems time to share what we've learned more broadly. I wrote Stop Guessing to help many more people solve many more problems.

Most people aren't great at solving valuable, important hard problems. Their inability to solve them means they either live with those problems or throw money and resources at them to create patches and workarounds. When they live with a problem, they just bear the ongoing cost, whether it's money, emotional wellbeing, time, or a larger societal impact such as health, poverty, or even death. When they throw money and resources at the problem, they often simply fail to make an impact, and waste all of those resources. When they do make at impact, it's at much greater cost than was necessary.

This pattern wastes untold billions across businesses. It leaves huge societal problems like global poverty unsolved. It means individually that people struggle to get control of their time, their health, their finances.

But these problems are not impossible. They can be solved if people change their approach. I want people to understand how they can solve these problems, so they can unleash themselves.

PS: Why does guesswork ultimately fail to solve a problem?

NG: Guessing can work to solve easy problems, because easy problems have only a few root causes, and these are readily apparent. If your problem-solving skills have not been honed or trained, then trial and error could be faster than actually thinking about the problem. This is what most people are used to.

Hard problems, on the other hand, have hundreds or thousands of potential root causes. They exist in complex systems that have many different elements, and can be difficult to understand. Often people are so intimidated by these problems that they don't even begin trying to solve them. But when these hard problems are dire or costly enough, people will attempt to. Still, the same intimidation remains, and the fear causes them to do the opposite of what they should: Instead of digging in to understand how the problem manifests or how the system works, they rely on their experience to guess at what might be wrong. But the probability that you're going to guess the right solution is exceedingly low.

Other problems with fewer key variables have resisted this guessing approach and remain unsolved. If the problem were easy enough to guess into submission, in most cases it would have already been done. Because most people use this guessing approach as their primary problem-solving tool, they give up once they have exhausted all of their guesses.

When most people try to solve a problem, they come up with dozens of "ideas" -- that's another word for guessing -- and then try them out. They often cover the fact that they're guessing with scientific language, like "hypotheses" or "possibilities," but in the end, each of these is just a guess. When they try these out, they burn through time and money. The problem is still causing them headaches or losses the entire time. Worse, many of these ideas people try out will create new problems on implementation, because they don't understand what's really going on.

Here's an example: A food business had a product quality problem. They'd been working on this problem for months; it was a crisis and lots of resources had been thrown at it. They had brainstormed a list of 200 possible fixes, and had tried about a third of them. They'd spent hundreds of thousands of dollars just on the materials and labor to implement those fixes -- in addition to everyone's time to work on the problem. None of the fixes worked, and a few created brand new problems to solve. By actually studying the problem and the system, rather than trying stuff out, the problem was eliminated in just a few weeks, without any new expensive equipment.

Here's another from my personal life. One morning I was helping get the kids ready for school only to find that one of them was apparently sick. I was quite suspicious as he was not getting on so well at school, and he had to do something that day that didn't exactly excite him. I think it might have been recitation day. He had missed quite a bit of school and I felt he was suffering from senioritis. The staff at school all seemed aligned that he was just faking it. We were all guessing as to the cause of his symptoms.

My wise and patient wife decided to take his temperature, which until then hadn't been mentioned at this point during our "problem solving" discussions. Lo and behold, he had a fever over 101℉. Not the end of the world, but the thermometer certainly confirmed a day at home. Good thing she didn't just go with the popular guess.

 

PS: Most of us have heard of Occam's Razor. What are the benefits of simple solutions?

NG: I love Occam's Razor. It's particularly useful in situations where you have to guess --when you're unable to gather data and investigate a problem directly. For example: if you're trying to figure out why someone acted the way they did, people often come up with a complex hypothesis for the motive, whereas the actual reason is probably very simple.

The great thing about a simple solution is that it's easy to rally people in support of it, and implementation is simple, inexpensive, and relatively quick. The trap that people fall into is thinking that a simple guess is the same as a simple solution. Your guess might be simple, but implementing that guess is highly complex.

For example: let's go back to the quality problem above. If you are producing bad product, your simple guess could be that your production line is old and obsolete, so you need a new one. You can see that the implementation of this solution would not be simple: it requires capital, it's detrimental to profit, and there will be delays in implementing it. It is also hard to align people on guesswork -- perhaps why there is so much trouble getting people motivated to take action. Of course, it's highly likely that your guess is wrong, so you'll probably spend all of those resources and not fix the problem. There is nothing simple about trying out an idea that is totally wrong.

Ultimately what's different about Occam's Razor and a simple solution is that Occam's Razor is used to select between different causes that are already readily apparent. The definition is: Among competing hypotheses, the one with the fewest assumptions should be selected.

Remember that "hypothesis" is an informed guess. For hard problems, it's probably the case that none of your current hypotheses are accurate. The trick to solving them is to put aside hypotheses and understand the problem and the process. But we can use the principle behind Occam's Razor to tell us that there's probably a simple solution to our problem, and that's great news. This simple solution comes out of solving the problem to root cause by understanding the problem and the process -- when you find the root cause, the simplest solution will become apparent.

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