On Quantum Pricing and Intellectual Debt, and how to train yourself to think like an artist
Clawed back on reading as the summer nears an end, and still left with a long set of unread books. But, thankfully, the reading cut across several topics. Here are some stories from last week that I found interesting:
This week a short but very good piece appeared on the phenomena of pricing consumer goods. Have you noticed that sometimes prices of even dissimilar goods (wallets, shoes and shades at H&M) are often under the same bucket (say $9.99)? Often these buckets take a jump from one price category to another ($9.99 to $19.99) – this is informally referred to as ‘quantum pricing’, where prices are ‘separated by large, economically meaningful, distances’. I believe the idea behind these quantum jumps on pricing is to ease consumer decision making by reducing cognitive load of comparing a wide range of prices. Anyhow, what happens when the cost of production goes up, or prices are under pressure (say during deflation)? Firms have two options to keep their margins: increase prices (which they are reluctant to do, often) or cut costs. Cutting costs is not always about improving productivity, or squeezing the last from your resources, but could simply be about providing less to the consumer – as Toblerone did two years back in the UK by cutting the amount of chocolate per bar but keeping the same prices (product redesign to meet the price). In labour intensive business, applying this principle is more difficult. For example, how do you reduce the level of service to the customer? Well, one way to ‘cut chocolate’ is to reduce labour needed, for example, by eliminating human touch-points via automation. Seemingly, most economic models do not account for such quality variations, and the jury is still out on how the economic data be interpreted considering such trends.
If you have any creative pursuits on top of your work life, and struggle to act on them, then one book worth reading to nudge yourself is Steal Like an Artist (Austin Kleon). Steal Like an Artist’s main theme is to remain free from the burden of trying to be completely original, and that we should let ourselves be influenced from others’ ideas. A few useful ways of working that I took away from the book are:
Chew on one thinker/artist at a time: Understand everything about this person’s work, what she did and why, why people liked her work, what’s the big idea behind her work. Once done, then repeat with another one who you admire. I remember doing that with Rushdie’s work many years back, followed by Kerouac’s. In many ways, my earlier travel writing from that time borrowed heavily from their styles.
Try to replicate the thinking of that thinker. While doing so, don’t just copy the style but copy the thinking behind the style. The underlying idea is not to become a duplicate copy of your heroes, but rather to train yourself to start thinking like them.
Creativity is subtraction – limitations mean freedom. And how do you do that: by putting artificial limitations. For example, write a story in one hour, or paint a painting with one colour only. I have attached an example from the book on how Kleon used a calendar to force himself to deliver on the content for his first book.
Finally, keep your day job. “if you don’t take money, they can’t tell you what to do”
A new word that I learn this week (apart from ‘quantum pricing’): intellectual debt. Simply put, it’s a way of ‘answering first, explanations later’, i.e., we discover something that works (for example drug discovery is often largely through trial and error without always understanding the underlying mechanism of action). Increasingly, as we search answers to fuzzy, open-ended questions from large data sets using machine learning, we risk gathering more intellectual/technical debt, where we are not able to explain why it works but can trust and put that insight to use immediately. Here is a longer, more detailed explanation. This approach is fine, as long as we are aware of the flip side, which is that the machine learning based systems can be gamed. Here is a piece on how some students fooled a Google algorithm.
A quote I came across last week:
“Can you imagine yourself in 10 years if instead of avoiding the things you know you should do, you actually did them every day? That’s powerful.”