It’s easy to believe them when clients ask us, designers, to make recommendations. We want to believe they love us for our wisdom, knowledge, and experience. They want our advice. And we love giving them advice. It makes us feel smart—like they finally “get” what we’re about. They want to do the right thing and we know how to help them. So, why is it bad to make design recommendations? They want it. We want it. Why shouldn’t we make the recommendations they’re asking us to give?
Simple: The recommendations don’t work. We end up looking bad. Clients lose faith in our skills. And the design doesn’t get better. Interestingly, in our research, the best teams don’t use recommendations. Instead they use an experimentation approach.
Patient, flexing his arm: “Doctor, doctor! It hurts when I do this.”
Doctor, checking the patient: “Hmmm. Well, I recommend you stop doing that.”
The Easy Out
Making recommendations is an easy out. You say, “Do this. Change that.” then wipe your hands clean of it. If they don’t do it, they’re obviously idiots. If they do, you’re brilliant. The best case scenario is they follow your great recommendation and it improves the design. But it turns out, that only one out of four possible outcomes.
|They follow your recommendation and the design improves||They don’t follow your recommendation and the design improves|
|They follow your recommendation and the design doesn’t improve (or it degrades)||They don’t follow your recommendation and the design doesn’t improve (or it degrades)|
What happens if they follow your recommendations and it doesn’t improve the design? What happens when they choose to not follow your recommendations and the design improves anyways? In either case, your future attempts to work with them becomes more difficult.
Changes cost resources. If the design doesn’t improve, then the organization has spent energy, money, and time on something that didn’t pay off. Are we considering that when we put the recommendations on the table?
Playing “Bet Your Salary”
UX Researcher Extraordinaire, Meghan Ede, has a rule of thumb she applies to her research team’s recommendations. The team members can only submit a recommendation if they’d be ready to put a full year’s salary down as a guarantee that the design will show improvement.
Would you be willing to do what Meghan does with your next set of recommendations? Go ahead: take out your checkbook. Write out a check for your take-home salary, after taxes. Pass it in with your recommendations, while telling them that, if the design doesn’t improve, they can cash the check. How confident are you feeling about those recommendations?
The Experimentation Approach
What our preliminary research has found is a typical recommendation looks something like this: “Users had trouble seeing the field labels. I recommend you put the label on the top of each field, instead of on the left.”
However, some teams are using a different approach: “We’re seeing that our users have trouble with the field labels. We’d like to try an experiment and see if moving the labels to the top of each field makes an improvement.”
It’s a subtle difference. And it was the approach we saw most in use amongst those UX professionals who had a solid track record of consistently improving their designs. These professionals told us they refuse to make recommendations, but love to experiment.
Discussing the Meaning of the Observations
I found the process from these high-performance teams quite interesting. It starts with a team discussion of the underlying observations and what it means. The team explores all the different interpretations. “Is it possible the users didn’t see the labels because they are too far away? If the font hard to read? Are the users not recognizing the terms? Were we measuring the wrong tasks?”
Then the team guides the conversation to other research that may fill in any holes, group discussion of alternatives, and measures to signal when the users’ behaviors change in the right direction. Often, this is followed by further research, then more discussion.
This process is very different from the recommendation approach, where the local UX expert makes a pass at the design and puts together a list of things that need changing. Instead of putting the onus on someone to come up with winning solutions, the entire team pushes the design into improvement, one experiment at a time. Some changes will work as intended, others won’t, but with each change the team learns something.
The result is that the entire team becomes better informed about the design they are building. No one person carries the burden of improving the design. Nobody has to be in the position of being all-knowing, always right. Changes are not seen as final, but as an ongoing process of improvement.
A Change in Mindset
Making the move away from recommendations is very hard. As I said, making recommendations is the easy way out, so it feels like the best path. But, in the long run, it’s a trap. The house odds are against you and eventually, it will all come crumbling down.
Both experience and research are telling us that experimentation, where constant changing and measuring gives the team guidance and insight, is the approach that leads to long-term success and better designs.
That’s my recommendation. I’m sticking with it.