The following line is from an e-mail I recently received from Georgetown’s HR department. It references “GMS,” the slick new database system they installed to unify all employee services:
Please remember to log in to GMS a few times each day to check your Workfeed for any items requiring your attention and/or approval.
Among the tenure-track faculty, the message was a source of amusement: the idea that professors at a research university should be checking with the HR department several times a day, just in case there is some administrative task waiting for them to complete, runs counter to everything we’ve ever been taught about how people succeed in academia.
I’m mentioning this note here, however, because I saw it as an example of a deeper principle currently shaping the American knowledge work environment — a principle with destructive consequences.
Earlier this week, after three days of trying, I proved an interesting theorem. I was studying a certain type of scheduling problem in graphs. I was finally able to prove that without lots of knowledge about the graph no algorithm can solve the problem fast.
This morning I set out to extend this result. I wanted to know what happens if you have more knowledge. After about an hour, I had a partial answer: If the graph is small in a certain way there is an algorithm that can solve the problem fast — I know this because I found it.
Unfortunately, for more general structures I couldn’t make the math play nice. I had a hazy intuition, but attempt after attempt to make it concrete failed. I couldn’t hold the pieces straight in my head. (See here for more on the style of problem I’m talking about here.)
After another 3 – 4 hours I had to stop for the day.
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While designing the original Macintosh, Steve Jobs became frustrated with the title bars. As Malcolm Gladwell summarizes in a recent essay on industrial innovation:
“[Jobs] forced the developers to do another version, and then another, about twenty iterations in all, insisting on one tiny tweak after another, and when the developers protested…he shouted, ‘Can you imagine looking at that every day? It’s not just a little thing. It’s something we have to do right.'”
Gladwell told this story to emphasize a truth about Jobs that many found frustrating: “He needed things to be perfect.”
A Different Type of Practice
Like many in the advice community, the death of Steve Jobs drove me to a period of morbid, posthumous anthropology, seeking some insight into what made this icon who he was. In this scavenging, it was the tales of perfectionism — emphasized by many different commentators — that caught my attention.
Jobs’ quest for perfection made him “complicated and exhausting,” but it also made him and his team really good at what they did.
On reflection, this makes sense. When we declare something to be “good enough,” we are declaring that we have reached the limits of our comfort zone. A “good enough” outcome, in this respect, is a snapshot of our current ability level. Pushing something beyond this point crosses a threshold into an ambiguous and uncomfortable territory, where we need skills we don’t yet have and which might be difficult to acquire and apply.
This is a territory most of us avoid.
People in the orbit of Steve Jobs could not.
And they became the best technologists in the world.
Defusing the Dangerous Allure of Perfect
We have now entered a precarious situation. Perfectionism, I’m arguing, can be a powerful technique for injecting deliberate practice into your working life, as the quest for perfection forces you to strain and develop new abilities in a way that you would otherwise naturally avoid. Because of this, it provides a nice case study of our deliberate practice hypothesis in action.
But perfectionism is also dangerous. It’s the source of workaholism and the bane of elite college students. It drove Harvard’s happiness guru, Tal Ben-Shahar, to write a book with the subtitle, How to Stop Chasing Perfection and Start Living a Richer, Happier Life.
To harness this technique, therefore, requires nuance.
In the early 1990s, a trio of psychologists descended on the Universität der Künste, a historic arts academy in the heart of West Berlin. They came to study the violinists.
As described in their subsequent publication in Psychological Review, the researchers asked the academy’s music professors to help them identify a set of stand out violin players — the students who the professors believed would go onto careers as professional performers.
We’ll call this group the elite players.
For a point of comparison, they also selected a group of students from the school’s education department. These were students who were on track to become music teachers. They were serious about violin, but as their professors explained, their ability was not in the same league as the first group.
We’ll call this group the average players.
The three researchers subjected their subjects to a series of in-depth interviews. They then gave them diaries which divided each 24-hour period into 50 minute chunks, and sent them home to keep a careful log of how they spent their time.
Flush with data, the researchers went to work trying to answer a fundamental question: Why are the elite players better than the average players?
The obvious guess is that the elite players are more dedicated to their craft. That is, they’re willing to put in the long,Tiger Mom-style hours required to get good, while the average players are off goofing around and enjoying life.
The data, as it turns out, had a different story to tell…
