Most organizations have several different products aimed at different market sectors. However each product or service is usually designed with one main user in mind. This product or service ends up only supporting a portion of the people it is aimed at. Real life scenarios are ignored because they’re deemed not important enough by the organization, or too complex, or not even recognized. (e.g. A memorable example of the latter is the 2014 release of Apple’s Health Tracker that omitted period tracking.)
The prevalence of these kinds of offerings reminds me of the episode from the 99% Invisible podcast: On Average. In that episode they point out that in WWII, pilots flying in cockpits designed for the “average man” experienced trouble controlling the planes. There were deaths, which lead to investigation and research, and in 1950 they eventually hit upon the solution of adjustable cockpit controls.
So, instead of designing for an imagined average user, you could design adjustable experiences. This, of course, puts the onus on the user, both in terms of attention and cognitive load. My opinion is that several elegantly- and specifically-designed solutions for different peoples’ thinking styles is a better approach. For example, Healthwise came up with three different designs to support three different thinking styles of people trying to lose weight. And the example below, from Caroline Jarret, who is currently writing a book titled Surveys That Work. Pay close attention to how Caroline refers to “average.” It’s called the “mean” or “arithmetic average,” and provides very little help to our design of a solution.
Back in stats class, you probably learned that a ‘mode’ is the value that occurs most frequently, and the ‘range’ starts with the lowest value and finishes with the highest.
So let’s say that I’ve done a little pilot survey with 100 responses to find out whether a recent campaign to attract families with children has worked or not, and I get these answers:
|Number of children in family||Number of respondents|
|10 or more||0|
|Mean (arithmetic average)||2.15|
|Range||0 to 9|
The average number of children per family is just over 2.
If you look at the range, you’ll see there are a couple of very large families, including one with 9 children – perhaps not that surprising when we think about life today with blended families. And perhaps even more surprisingly, some families are turning up with no children in tow at all. So maybe if you’d designed seating in a restaurant to allow for two adults and two children per family, you’d have a lot of empty seats at tables for four, but some much larger groups struggling to organise themselves.
If you look at the most frequent number of children, the mode, then you’ll see that the mode is 1 child, with the group of people who turn up with no children at all the next biggest So if you designed a ticket price that’s aimed at attracting families with 2 kids, you’d fail to cater for the two biggest groups in your audience (and not be all that helpful for the larger families either).
I didn’t learn a lot about modes and ranges in statistics class because they’re awkward concepts mathematically, whereas means have lots of very interesting mathematical properties that are very handy for statistical purposes. But for designers, my experience is the other way around: means can hide a lot of the details that we need for design, whereas modes and ranges can be much more informative.
These sorts of Zipf distributions are everywhere in UX, with the most familiar being the search terms. (by Caroline Jarret)
Caroline’s restaurant example is a good way of demonstrating how eager our culture is to design for the mean, and how much of a hassle an “average” design turns out to be for most people. If you expect several different groups at the restaurant (and assuming this is a restaurant that anticipates lots of kids), you’d design multiple solutions: tables for pairs of adults, tables for adults with one kid, and configurable tables pre-arranged in anticipation of adults with 2-4 kids and with 5-9 kids. (Ignore for purposes of this example the fact that it’s rife with assumptions around how a kid behaves and how to support a kid versus an adult. Focus on the average versus mode part of the example.)
Product managers have more and more resources, and since October 2016 Karthik Vijayakumar has hosted a podcast called Design Your Thinking. He invited me to speak with him last month, and produced two episodes about researching the problem space from our conversation. (Each episode is about 30 minutes.)
In episode066, we discuss the larger ideas that have nothing to do with what an organization is offering, and taking time to understand what’s going through people’s minds to see what the patterns are, measure the strength of your support, and map out your focus and priorities for the next few years. For example, it allows start-ups to focus and recognize when they are trying to solve the wrong problem and pivot. Our conversation continues in episode067 exploring the how to address the needs of what shows up in a tower in a mental model diagram, which is a representation of the stages of people’s thinking as they work their way towards an intent or purpose they have. (Karthik follows a specific format across all his guest interviews, so you can compare answers across many different experts.)
Also last month I got into conversation with the producers at the Wisconsin Public Radio show, To the Best of Our Knowledge, about the Against Empathy book by Paul Bloom. Paul did an interview with the host of TTBOOK, and it purported the opposite of what I practice. Paul said that empathy leads to bad decisions because you put the story of one person over the stories of the multitudes. Quite the opposite of what I do, which is bring the stories of the multitudes into the room with product managers, designers, and developers via the cognitive empathy I develop with participants and distill into mental model diagrams. Check out my interview, along with another engineer’s response, in the segment “Does Empathy Have a Design Flaw?” (21 minutes. Transcript available here.)
In the 10 minutes of my half of the interview, I cover the following topics:
- We’ve gotten good at checking out our ideas & making sure they work. Now it’s time to understand implications first.
- It’s not a deficit of empathy—it’s a deficit of breadth when we are designing solutions.
- Ideas are sexy. You get a lot of credit for good ones. We gravitate towards solving as opposed to understanding.
- Understand the different kinds of thinking and map out how we can support them over the next 5-10 years.
- People design from their own experiences. I bring a whole lot of other people’s experiences into the room.
- Ability to support other perspectives, beyond those they’re familiar with.
- Focus on the lack of emotional education in our culture, the lack of ability to listen to & recognize other people.
- A start-up has a short runway; they can’t solve everybody’s problem. I get them to focus down to a particular subset.
- Single-minded design/function is bad in that it leaves the majority of people unsupported.
Austin, Texas, USA, 03-Apr-2017 – Problem Space Research Workshop at the Designing for Digital conference. (Still amazingly good prices!)
What’s our best fit?
“We’re trying to explore the problem space, but we’ve run into problems. Can you double check what we’re doing?”
“We want to make sure we do the research right. And we want the skills in-house so we can keep exploring.”
mentor the team
“We want to explore something, but we don’t have the cycles to get involved. We want answers that are credible.”