You need to get to the airport to catch an important flight. In the past, it took you on average about two hours to get to the gate. What do you do? Are you planning to leave the house two hours before the gate closes or are you adding 30 to 60 minutes just to make sure? If you are like most people you choose the second option, because you never know, right? There might be a traffic jam or the security check takes longer than normal. This makes perfect sense. You really want to catch that flight, so you plan in a buffer because you never know…. When it comes to business and design, however, it is shocking how much we rely on averages while planning and building for the normal case.
The problem of designing for average
When designing something for people who are you designing for? In a business school you would probably hear some version of “for the target market”. The target market is often a synonym for the average users. However, reducing a complex system such as a market to an average participant sets us up for disappointment. Most people are by definition not average.
This has two implications. First, if you are designing for average what you are building will be a little bit right for most, however, also mostly wrong unexceptional for all. As soon as there is an alternative that is comparable or just more established you will have a hard time creating excitement for what you developed. To truly succeed and having an impact, Peter Thiel talks about building things that are 10 times better than what already exists. You won’t get there by designing average things that are a little bit right for everyone.
Second, designing for average increases the risk that the design breaks under non-normal conditions. Depending on what you are building the consequences can range from inconvenience to downright danger for users. Nobody wants to hear the excuse “this would not happen under normal circumstances”, because they only care about the results. The hedge fund Long Term Capital Management built a wonderful model to invest in normal market circumstances and got very rich. Until the market did not behave normally anymore and they lost everything and more in a matter of days. The excuses of the LTCM managers that the events were “beyond the fund’s capacity to anticipate” didn’t help all the people that lost their money.
Extreme user theory
If you shouldn’t design for the average case, what should you design for then? The opposite, namely extreme users and extreme cases. If you choose a design that works for both ends of the spectrum (e.g. the digital cracks and the uninitiated) the solution will very likely work for everything in between too. Furthermore, by designing for and testing with extreme cases you are “stress-testing” a solution, which makes it much more robust than aiming for an ideal or average case.
Same is true for other fields, for example marketing. Seth Godin explains in his book This is Marketing how writing your message for the average market waters it down so much that it becomes irrelevant for all. Instead you should aim for an extreme niche with specific needs and problems where you can provide a good solution. If it helps in extreme cases it most often helps in normal ones as well. These extreme users often take the role of leaders in the market and if your product helps them they will bring it to the mass market. So again, go for the early adopters (extreme) first before you aim for the majority (average).
Average is a construct that has nothing to do with reality. If you want to design something that has an impact build for the individuals, the specifics, and the extremes.