A Brief History of the Beer Game

by Larry Snyder

Opex Analytics
The Opex Analytics Blog
5 min readJul 30, 2018

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I’m getting pretty excited about the upcoming release of the Opex Analytics Beer Game — it’s scheduled to go live in about three weeks! While the Opex version is brand new and uses cutting-edge algorithms and Artificial Intelligence, the Beer Game itself has quite an extensive history. I learned all about it while developing the Opex version and, to tide you over before the release, I’ll share a brief history with you.

Beer Game screenplay.

So… What is The Beer Game?

The Beer Game is a widely used in-class game that’s played in supply chain management and system dynamics classes. Instructors use it to demonstrate the Bullwhip Effect, the impact of hidden information and the importance of coordination across the supply chain.

It all began in 1956 when managers at General Electric noticed huge swings in production levels at one of their factories — swings much larger than the swings in consumer demand. A few years later, motivated by their discussions with the General Electric managers, professors at MIT began developing the original Beer Game.

It started with MIT professor Jay Forrester, regarded as the founder of system dynamics and author of the well-known book Industrial Dynamics. First, Forrester developed a simulation of a production–distribution system inspired by the GE factory. Forrester’s simulation was essentially a pen-and-paper spreadsheet. In the summer of 1958, MIT’s summer session used this production–distribution system as an in-class demonstration, rather than as a competitive game.

Schematic diagram of a three stages of production–distribution system described by Forrester, HBR, 1958.

Forrester’s 1958 Harvard Business Review article showed this model (left), which used a three-stage supply chain consisting of a retailer, a distributor and a factory.

Increase in order volatility due to 10% increase in retail sales. Forrester, HBR, 1958.

Forrester’s article demonstrated that a small increase in the volume of retail sales can make the retailer’s orders more volatile, the distributor’s orders even more volatile and the factory’s production more volatile still. This pattern came to be known as the bullwhip effect, though it wasn’t named that until a few decades later.

During MIT’s summer 1960 session, Forrester’s simulation became an actual game; players used a physical board and cards. Over the next decade or so, various aspects of the game evolved, including the number of stages (players), lead times and costs.

MIT professor J. Miller first specified the product in the simulation/game as beer in 1973. Miller explained this choice of product by noting that:

“In order to meet customer demand, many beer companies have to maintain large inventories of beer,” and that, “a significant activity of the beer company is to maintain the minimum amount of beer necessary to satisfy customer demand reasonably quickly.”

(To be honest, I always assumed the game was given its name as a mild attempt to pander to college students. We professors think we’re pretty clever when we do this sort of thing.)

The “standard” version of the Beer Game, if there is such a thing, was codified by another MIT professor, John Sterman, in a Management Science article. That version uses four stages, lead times of (mostly) 2 periods, holding and stockout costs of $0.50 and $1.00, and a (mostly) stable demand pattern with a demand “shock” a few periods into the game. This version of the game is the “Classic” setting in the Opex Analytics Beer Game.

While Forrester focused mainly on how dynamics of the system itself causes instability, Sterman was interested in the ways that managerial behavior, especially irrational, “panicky” behavior, causes instability. Sterman proposed a simple formula that captured players’ panicky behavior. Fun fact: the “human-like” computerized players in the Opex Analytics Beer Game follow this formula. In his 1990 book The Fifth Discipline, Peter Senge (another MIT professor) gave two rules to prevent this panicky behavior:

“(1) Keep in mind the beer that you ordered, because of the delay, has not yet arrived, and (2) Don’t panic.”

The System Dynamics Society began selling Beer Game kits in 1992. The Society sold about 20 kits that year; in 2004, it sold over 7,000.

There have been several computer implementations of the Beer Game. The Opex Analytics Beer Game is the latest, plus the only one that includes an AI-powered player. Using Reinforcement Learning (RL), the AI player learns optimal strategies and plays against you or, if you elect to be on the same team, plays alongside you to help improve your score. While testing the game, we found that eight out of ten Opexers failed to beat the AI player. We’re looking foward to watching many others try their hand at it soon.

Sadly, we must admit, no actual beer is involved. But it’s a fun way to learn about supply chain management and system dynamics, plus it uncovers ‘the possible’ in terms of the great value AI (even more specifically, RL) can create when used within operations. What more could you ask for in a game?

Stay tuned for the release of our Opex Analytics Beer Game coming August 9th, 2018!

Crediting: I learned most of what I discuss in this post from the article The Beer Game: Its History and Rule Changes.

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