Jerry Uelsmann, a photography professor at University of Florida, conducted a fascinating experiment with his photography class. He divided his students into two groups:
At the end of the semester, contrary to all expectations, the best photographs were produced by the “quantity” group.
While the “quality” group was busy researching the best techniques and thoughtfully planning everything, the “quantity” group gained a considerable amount of actual practice and experience, which lead them to win both in quantity and quality!
“Perfectionism” as a concept is anti-productive. While I don’t deny the inherent good in working hard and producing good work in whatever domain that interests you, there is a huge difference between “doing great work” and “trying to do perfect work”.
Although this might seem like a semantic exercise, the difference between “great” and “perfect” is psychologically important to me. I think striving for “perfection” may mislead, and sometimes paralyze. When only the perfect will do, how can one justify a sub-par brush stroke, an ill-fitting prose, a good-enough model? I think the key to great work is to satisfice, then optimize. The order of operation is important!
To me, this is a discussion of efficiency. I think we should all strive to produce quality work, but trying to be perfect every step is too rigid and inefficient. As we’ve seen from Professor Uelsmann’s photography class, the path to perfection is often rough and iterative and unglamorous, the complete opposite of the end product.
Unless you are a maestro already, allow yourself to be rough! In the case of writing, allow yourself to write utter garbage (what I am doing right now). If you are a product developer, make a minimum viable product first, then make it better.
A thought came to me recently that is somewhat related to our discussion above. I’ve been teaching myself web development, and it occurred to me that I have a deeply ingrained preference for learning slowly and methodically.
This is perhaps a relic of my education training. If I’m learning a concept, I want to make sure I grasp it 100% before moving on (95% is not good enough!). The benefit of this approach should be self-evident in my GPA. The cost is all the time I’ve spent learning some tangentially related concept that I’ll most likely never encounter again, and that I have since completely forgotten.
While I agree learning for mastery if important, I am again talking about efficiency here! Perhaps we can view our different methods of learning as sorting algorithms. My predilections and OCD tendencies drive me towards bubble sort, but perhaps a messier quick-sort would be more efficient!
This might sound crazy and backwards, but I am convinced it is better pedagogically to do a task before you learn how to do it! To put it another way, do it in a terrible, hacky, inefficient way first! Only then is it possible to fully appreciate and deeply understand when you finally learn the right way.
Richard Feynman talks about this a lot in his book. To give a concrete example, we are taught in school that a hammer can be used to drive a nail into pieces of wood. On the exams, we are rewarded for knowing what a hammer does. However, in the real world, when we are given two pieces of board and a nail and asked to attach them together, we won’t know how. Perhaps it’s conventional learning that is backwards.