Why can’t we make more use of the 80/20 rule? I’ll review what the 80/20 rule is, explain how it can be powerful, then give four reasons why we don’t take advantage of it.
What is the 80/20 rule?
The 80/20 rule is amazing when you first learn about it. It says that efforts and results are often very unevenly distributed. You’ll get 80% of your results from the first 20% of your efforts. For example, maybe your top 20% of customers will provide 80% of your profit. Or when you’re debugging software, often 80% of the bugs will be in 20% of the code. Once you become aware of it, you’ll see 80/20 examples everywhere.
There’s nothing magical about the numbers 80 and 20. The general principle applies if 93% of your results come from 22% of your efforts. The numbers don’t have to add to 100. The principle is just that outcomes are unevenly distributed, more unevenly distributed than you may think.
Applying the 80/20 rule
Applications of the 80/20 rule are everywhere. For example, if you want to learn a foreign language, you don’t buy a dictionary and start learning words from page 1 and work your way to the end. Some words are used far more often than others. You’ll be able to use a language much sooner if you learn the vocabulary roughly in descending order of frequency.
Software optimizations can be extreme examples of an 80/20 rule. Sometimes 98% percent of a program’s time is being spent executing just five lines of code. Finding those five lines and tuning them is far more effective than randomly tweaking things here and there in hopes that the changes improve performance.
Why don’t we apply the 80/20 rule?
If the 80/20 rule is so powerful, why don’t we use it more often? Why don’t we concentrate our efforts where we’re likely to see the best results? Here are four reasons.
- We don’t look for 80/20 payoffs. We don’t see 80/20 rules because we don’t think to look for them.
- We’re not clear about criteria for success. You can’t concentrate your efforts on the 20% with the biggest returns until you’re clear on how you measure returns.
- We’re unclear how inputs relate to outputs. It may be hard to predict what the most productive activities will be.
- We enjoy less productive activities more than more productive ones. We concentrate on what’s fun rather than what’s effective.
If you address these issues in order, you might get stuck on the third one. It can be hard to know what is most productive. Our intuition in this area is usually wrong. For example, maybe the most effective thing to do is very simple, but we overlook it because we think the answer must be more complicated. Or maybe we confuse what we need to do with what we want to do. Collecting data is the best way to find out what really works. The results are often surprising.
Sometimes the world changes and we’re stuck doing what used to be most effective. For example, some of the most persistent ideas about the “right” way to develop software come from studies of done forty years ago. It’s not enough to collect data one time.