Optimizing things in the USSR 11 May 2016 As a data scientist, a big part of my job involves picking metrics to optimize and thinking about how to do things as efficiently as possible. With these types of questions on my mind, I recently discovered a totally fascinating book about about economic problems in the USSR and the team of data-driven economists and computer scientists who wanted to solve them. The book is called Red Plenty. It’s actually written as a novel, weirdly, but it nevertheless presents an accurate economic history of the USSR. It draws heavily on an earlier book from 1973 called Planning Problems in the USSR, which I also picked up. As I read these books, I couldn’t help but notice some parallels with planning in any modern organization. In what will be familiar to any data scientist today, the second book even includes a quote from a researcher who complained that 90% of his time was spent cleaning the data, and only 10% of his time was spent doing actual modeling! Beyond all the interesting parallels to modern data science and operations research, these books helped me understand a lot of interesting things I previously knew very little about, such as linear programming, price equilibria, and Soviet history. This blog post is about I learned. Balance sheets and manual calculation: Kind of a trainwreck The main task in the centrally planned Soviet economy was to allocate resources so that a desired assortment of goods and services was produced. Every year, certain target outputs for each good were established. Armed with estimates of the available input resources, central administrators used balance sheets to set plans for every factory, specifying exactly how much input commodities each factory would receive, and how much output it should produce. Up through the 1960s, this was always done by manual calculation. Since there were hundreds of thousands of commodities, and since the supply chains had many dependency steps, it was impossible to...