How I’ve Let Go of Delight

Or How I’ve learned to Let Go of Delight

(An excerpt from a blog posted on July 13th, 2016 on nomensa)


Stephen Hawking, in writing the introduction to “A Brief History of Time” reported the long-standing folk rule about science writing for lay audiences: Sales cut in half for every equation he introduced in his book.  Two things about that: A) I can’t find any authoritative source for the original notion and 2) what does that mean for this article when the title is an equation?

Quick a snap quiz: Raise your hand if you got the memo that UX owns emotion and delight.

A really stupid search through google showed the first inklings of this meme back in 1994, with a slow ramp through the 90s until it burst out in the mid-2000s as a thing. By 2010 it was decided, UX owns emotion and delight. Who wants to argue with that? I’m happy to bicker about the verb “own”, but surely, if UX and design aren’t responsible for injecting emotion into experiences, what discipline is?

Photo of smiling man

Photo Credit: Lesly B. Juarez

All right. How about this one: “Make it a ‘Wow!’ Delight our users!” Raise your hand if you haven’t heard it from your stakeholders.

Who else is starting to feel like Charlie Brown facing Lucy’s (American) football?

Now, don’t get me wrong: I’m just as passionate about crafting emotional experiences as I’ve ever been. It’s not that UX shouldn’t own emotion and delight; it’s that few organizations actually have what it takes to invest in delight. Building delightful experiences means restructuring how products are defined, designed and delivered.

So this rant is not about letting go of delight as the aspirational goal of UX. Quite the opposite.

Equation: s is proportional to satisfaction divided by effort

where S means Satisfaction, R means Results and E means Effort. Satisfaction depends on how much effort you require to get the results you desire.

Let me break that down a little.

I’ll start with Results. This equation has a lot to do with big data, data analytics and information visualization. The first question is: Can I even get the answer I need from this analysis? More interesting questions include: How good are the results? How many different types of analysis can I do? But Results could just as easily apply to accomplishing a task, or in its most torqued form, upleveling on a game. Clearly the richer the Results, the higher the Satisfaction.

Effort is fairly straight forward. The less effort, the more Satisfaction. In fact, mathematically, satisfaction approaches infinity when the effort approaches zero. How true! In the case of information visualization, the less effort required to manipulate the visualization, the greater the satisfaction. Good visualizations take advantage of the thousands of parallel processors sitting at the back of our eyeballs. When data patterns are displayed appropriately, the analyst requires virtually no effort to gain insight. Very high satisfaction.

The two right-hand terms work together: no matter how good the results, if the effort is too large, satisfaction will always be low. Paradoxically and obversely, no matter how poor the results, if there is virtually no effort, satisfaction will be high.

Read more on nomensa’s site…