Have you ever had trouble starting something? I’m not talking about starting a car in winter, but some work, maybe a new project or a blog post. Beginning new projects can be difficult. Can you remember thinking, saying, or hearing any of the following?
“I’m still planning it.”
“I need to do some more research.”
“My idea isn’t polished enough yet.”
“I wasn’t sure on the best way to do it.”
The sticking point
These snippets have something in common. At best they suggest indecisiveness, at worst they can be symptoms of analysis paralysis. This state—of being unable to progress past the point of thought and analysis—is not uncommon. A quick Google search of “analysis paralysis” brings back over three million results.
As a software developer, there are two situations in which this state often arises: choosing “what” to do and “how” to do it. In a personal project where we act as both the product owner and developer, we have to address both. Contractors are often spared having to deal with the “what” since product or business owners will exist to make that choice. The “how” is ever present, and is typically where most of a developer’s time is spent.
Not long after starting to program, we realise that there’s often more than one way to solve a “how” problem. This means that a programmer will spend some time considering the various implementation options. There is certainly value to this thought process—some ideas can often be ruled out quickly with some simple thought. The difficult part comes when the obvious options have been ruled out. From this position we want a way to determine which option is the best one.
The paradox of choice
Barry Schwartz speaks about the paradox of choice in his 2005 Ted talk. He identifies that while freedom of choice is a positive opportunity, the multitude of choices in society has “left us not freer but more paralyzed, not happier but more dissatisfied.” Why is having more choices a bad thing?
Analysis paralysis is stressful—it brings with it feelings of anxiety and self-doubt. These feelings, despite having no tangible output, are using valuable cognitive resources. Driving while using a mobile phone is well regarded as dangerous, as it reduces our ability to notice hazards on the road. In the same vein, when we distract ourselves by worrying, we lower our ability to think critically or creatively about the problem at hand.
The second key factor is decision fatigue. The more decisions we make, the more difficult they become. Successful people including Steve Jobs, Carrie Donovan, and Mark Zuckerberg are well known for wearing the same clothes everyday. When this was queried, Zuckerberg replied:
“I really want to clear my life to make it so that I have to make as few decisions as possible about anything except how to best serve this community.”
Given all these negative consequences to over-analysing, what can we do to prevent it?
The quick decision
Having reduced an implementation decision into some sensible options, what can we do to prevent paralysis setting in? One idea is to flip a coin:
“When faced with two choices, simply toss a coin. It works not because it settles the question for you, but because in that brief moment when the coin is in the air, you suddenly know what you are hoping for.” —Kevin Purdy
While this quote tends toward less important decisions, I believe the concept holds true. Sometimes our instincts can become clouded when we spend too long analysing our decisions. A coin toss can provide some much needed clarity when the decision isn’t obvious. In cases where an underlying instinctive choice doesn’t come forward, follow the coin toss, because there’s a good chance that the outcomes will be equally viable. The additional benefit here is in reducing the amount of time we spend thinking. In doing so we can maximise the time we have with more information.
“But what if I do the wrong thing, or make the wrong decision?”
In software development, unlike lots of other situations, the cost of making the wrong decision initially is extremely low. The capabilities of current version control systems mean that undoing the actual implementation is trivial. When we make the wrong decision we only lose time. We can reduce the lost time by minimising the time we spend analysing a decision. However, that does not mean I am advocating rushing into the production of mediocre code every time you have a difficult decision. Making a decision is the first step, not the last.
When we over-analyse we have to compute the expected outcomes from each decision and compare them. Now that we have something implemented, we have something tangible to assess. This puts us in a much better place to make decisions. We can now look at the code and say whether or not we like how it has turned out.
We can also use this opportunity to improve the code. Seeing the implementation might bring to light opportunities to refactor, improve naming, or make the code drier.
This idea parallels a number of existing software practices. In Clean Code, Robert Martin describes a process he called Successive Refinement, wherein one writes rough code first before making improvements in its quality. This is reinforced by his Three Rules of Test Driven Development, which help to ensure that you don’t take on big decisions, but make small incremental steps to introduce tested production code.
Similarly, in following Kent Beck’s Four Rules of Simple Design, we ensure that our code passes a test in the simplest way possible before iterating over the code again.
It is not clear whether these principles were designed to defend against paralysis, but each of them goes some way to help prevent it.
The last decision
Over-thinking is detrimental to our productivity. To avoid it, we should try to reduce the number of choices we have, timebox our decision making, and ultimately put something on paper in order to build upon it.
Taking the small leap to try the first option produces evidence upon which we can make better informed decisions. By working in small iterative steps, we ensure our decisions are cheap and changeable. We are not making a frivolous decision in order to avoid difficult questions, we are making a quick decision in order to make a better one.
Making the decision to start solving a problem quickly does not affect the quality of its outcome. In our iterative process, we control quality by deciding when to stop.