What is Bikeshedding?

Bikeshedding is our tendency to address menial, simple problems over complex ones — regardless of their urgency or importance.

This tendency is also known as Parkinson’s law of triviality and has a tremendous impact on how we spend time both communicating problems as well as prioritizing decisions.

The concept of bikeshedding was first presented with the example of a committee tasked with making budget decisions around a nuclear reactor. Of course, nuclear reactors and the foundational concepts involved in even understanding how they work are quite complicated, so the committee spends its time discussing trivial details instead of addressing the complex, impactful variables.

“The time spent on any item of the agenda will be in inverse proportion to the sum [of money] involved.” — C. Northcote Parkinson

For anyone who has worked on large, complex projects, this probably resonates. We tend to spend an incredible amount of time and energy on trivial details. We do this because we gravitate towards clarity and understanding over uncertainty.

How does this impact decision making?

Bikeshedding impacts how we prioritize and collaborate on decisions. We naturally avoid ambiguity and complexity regardless of how urgent or important a decision or problem is.

Like in the nuclear reactor example, we spend a disproportionate amount of time on things that objectively don’t matter. This is exacerbated by other human tendencies that derail collaboration away from the most impactful, and often uncomfortable problems.

Example: Imagine we’re a mobile payments company and the next quarter is coming up… fast.

We’re trying to understand where we need to focus our digital advertising budget or what new compelling feature is going to drive the most upsells — but we have one big problem.

We need to decide whether or not we’re going to drop our freemium model. This decision has been in leadership’s court for months and it’s the primary blocker to deciding if we’re going to focus on converting free customers or drop the free plan altogether and market to new paying customers.

The importance of this decision appears clear as a team with significant downstream impact, but that doesn’t seem to create a sense of urgency for leadership. Every meeting goes in circles and devolves into conversations about trivial matters. In this situation, we’re more likely to prioritize lower-urgency decisions and address menial problems that are far less complex with ‘known’ factors.

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This kind of ambiguity aversion is best described by the Ellsberg Paradox, which states…

“A decision-maker will overwhelmingly favor a choice with a transparent likelihood of risk, even in instances where the unknown alternative will likely produce greater utility. When offered choices with varying risk, people prefer choices with calculable risk, even when they have less utility.”

In short, we want to attack the highest level of ambiguity and uncertainty first — even when we’re wired to avoid it. Often the more complex problems or lowest confidence assumptions would render the majority of the solution useless if not resolved.

Astro Teller, who leads Google’s X labs, uses the idiom “Tackle the monkey first”. If you’re trying to teach a monkey to recite Shakespeare from a pedestal, it’s clear what the more challenging problem is. We should figure out how to train the monkey, even though bikeshedding would push us to create the pedestal.

How to combat the effects

Bikeshedding will breed indecisiveness and complacency often disguised as a pursuit for more information. We may hear the excuse, “We just need more research before we make that decision”. It will also push us to solve problems that don’t matter in the end if we’re wrong about ambiguous, challenging problems.

Use prioritization tools that focus on urgency and importance over complexity

For example, an Eisenhower Matrix helps identify which decisions need to be made now vs later. Even if decisions clearly need to be made earlier rather than later, one-way and two-way door decisions is a method made popular by Amazon that clarifies whether a decision can be reverted or not. If a decision can be reverted, then we should move quickly — even with imperfect information.

Set a date for the decision

Pick a date for when the decision will be made and stick to it. If the default understanding is that we’ll move forward with the decision with imperfect information, then it forces us to ask the question, “Would any new information impact this decision? If so, can we afford it?” If the answer is yes, then we should be able to justify rescheduling the decision. If the answer is no, then it’s time to decide.

Stack the decision

If the decision is truly complex, identify the riskiest parts that need more information and opportunities to make smaller decisions upfront. Annie Duke, the author of ‘How to Decide’, describes this method as ‘Decision Stacking’. Most large, complex decisions can break down into smaller decisions that build validation and confidence over time.

Focus on the riskiest assumptions and find blindspots

Tools like the Rumsfeld Matrix or Lean Startup’s ‘Leap-of-faith Assumptions’ model help identify where we need to spend time building confidence and addressing important decision instead of being sucked in to the false sense of progress we get addressing known problem areas with low risk.