Measuring the Design Process

Both John Gruber and Buzz Anderson have commented on the experiences of former design lead at Google, Doug Bowman. Doug's observation is that at Google, every design decision must be backed by data. In essence, you must prove you're right. The post is quite short, but it resonates with me because I've seen the same thing at other companies.

Let me say first that I have enormous respect for Google. Not only have I benefitted from their products, but also their culture. The company is famous for being an unapologetically engineering-centric environment. And this is at the core of the discussion.

The most contentious point between software engineering culture and visual design culture is the question of whether important things can be always seen in absolutes. The engineering approach values measurable, reproducible results which can be represented in a graph or a checklist. Unit tests and benchmarks illustrate progress.

The nature of computers calls for this kind of mindset — it's a good match. Computers are incapable of making true judgement calls or subjective decisions. And inconsistent crashes are the hardest to debug. Predictability in computers is a very good thing because we would be in a lot of trouble if routers got bored, for example.

Packets, thankfully, also don't have an preference for which kinds of routers they pass through. But when we talk about end-user software that humans directly interact with, things change quite a bit. If you want to have a successful end-user product, you need to involve a designer.

Visual design is often the polar opposite of engineering: trading hard edges for subjective decisions based on gut feelings and personal experiences. It's messy, unpredictable, and notoriously hard to measure. The apparently erratic behavior of artists drives engineers bananas. Their decisions seem arbitrary and risk everything with no guaranteed benefit.

Designers, though, are just as frustrated by the apparent blind allegiance to data at the cost of human experiences. They often feel as if engineers lose sight of the actual goal. Artists see data as a tool only, not a purpose onto itself. The reason for this is simple: data in isolation makes no guarantees about whether the correct thing is being measured, or whether the measuring itself is skewing the results.

If the decision affects humans, a human must intervene to interpret the results. Humans are willing to risk being wrong if it means there's a chance of finding something better. Artists are used to working on these terms.


A Map Doesn't Help You in the Dark

I've seen some quite negative reactions to Doug Bowman's post, which insinuated he was ungrateful for his position at Google. Most of this seemed to hinge on the phrase "I can't operate in an environment like that." But I think this phrase was widely misinterpreted. It doesn't mean "I don't like working in this environment". Rather, it means "You are forcing me to deliver an inferior result based on a flawed belief."

That belief is that data can't lie.

Even though individuals in Doug's position are brought in as experts in their field, eager to share their insights, they are often hired under the incorrect assumption that a designer has amassed information in his or her career, not experiences. That assumption leads to a second flawed assumption: that all decisions will be based on hard facts.

An experienced designer knows that humans do not operate solely on reason and logic. They're heavily influenced by emotions and perceptions. Even more frustratingly, they often lie to you about their reactions because they don't want to be seen as imperfect.

But it's not just empathy that data lacks. The one indisputable advantage humans have over data is imagination. I realize this is often overplayed and sounds like hyperbole. But I mean it literally. The ability to step outside of what you've seen and consider how something that doesn't exist yet may yet exist is at the center of everything we do. Imagination is what allows us to consider if we should try to gather a different kind of data.

If a designer in Bowman's position has to spend every day trying to educate an unreceptive audience, that person will eventually no longer be able to do the job they were hired for. It's no surprise, then, that designers gravitate towards places where they can skip the education step and get right to work.

History books portray Einstein as a brilliant physicist, which he was. His understanding of scientific methods allowed him to refine and articulate his ideas. But that alone wasn't the reason he changed the world. His genius was imagining things that no one else had thought of, which he then set out to describe. He was two things in one: a scientist and a dreamer.

Data and measurements are essential in software, and can take you a long way on their own. But feelings and instincts are necessary too if you want to do something remarkable.

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