Beer distribution game
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An example of players at a game board.
|Players||Multiple teams with a minimum of 4 players|
|Setup time||10-20 minutes|
|Playing time||60-90 minutes plus another 60-90 minutes for debriefing|
The beer distribution game (also known as the beer game) is an experiential learning business simulation game created by a group of professors at MIT Sloan School of Management in early 1960s to demonstrate a number of key principles of supply chain management. The game is played by teams of at least four players, often in heated competition, and takes at least one hour to complete. A debriefing session of roughly equivalent length typically follows to review the results of each team and discuss the lessons involved.
The purpose of the game is to understand the distribution side dynamics of a multi-echelon supply chain used to distribute a single item, in this case, cases of beer.
The object of the game is to meet customer demand for cases of beer through the distribution side of a multi-stage supply chain with minimal expenditure on back orders and inventory. There are four stages, manufacturer, distributor, supplier, retailer, with a two-week communication gap of orders toward the upstream and a two-week supply chain delay of product towards the downstream. There is a one-point cost for holding excess inventory and a one-point cost for any backlog (old backlog + orders - current inventory). In the board game version, players cannot see anything other than what is communicated to them through pieces of paper with numbers written on them, signifying orders or product. The retailer draws from a deck of cards for what the customer demands, and the manufacturer places an order which, in turn, becomes product in four weeks.
Verbal communication between players is against the rules so feelings of confusion and disappointment are common. Players look to one another within their supply chain frantically trying to figure out where things are going wrong. Most of the players feel frustrated because they are not getting the results they want. Players wonder whether someone in their team did not understand the game or assume customer demand is following a very erratic pattern as backlogs mount and/or massive inventories accumulate. During the debriefing, it is explained that these feelings are common and that reactions based on these feelings within supply chains create the bullwhip effect.
The game is used to illustrate one of the links between System Dynamics theory and the Feedback Control Theory which inspired it - that systems with negative feedback loops and time delays can lead to oscillation and overload, a pattern of behavior observed in many real-world systems.
For a complete understanding, the game is played not only within a supply chain, but two or three supply chains are set up (when there are enough players and volunteers to help). In real life, more than the understanding one gets by playing as different entities in a single supply chain, it is the learning when supply chains compete with each other that makes clear the real strategic intent.
The team or supply chain that achieves the lowest total costs wins. The game illustrates in a compelling way the effects of poor system understanding and poor communication for even a relatively simple and idealized supply chain. Although players often raise the lack of perfect information about the customer orders as a primary reason for their poor team performance in the game, analysis of the minimum possible score under different conditions shows an expected value of perfect information of 0 for the standard game and simulations that included giving players perfect information still showed poor team performance.
The Beer Distribution Game is cited as an inspiration for at least one business-oriented learning game in the business oriented experimental learning field: The Friday Night at the ER game follows the same 4-player per board, 90 minute gameplay simulating real-world complex system, game session followed by detailed debrief model used by the Beer Distribution Game to teach players systems thinking concepts.
Recently an artificial intelligent system is proposed to play the game. The model plays as one of the agents and plays to minimize the total cost of the system, while it does not see any information of other agents. It is known that the Clark and Scarf (1960) algorithm is optimal for beer game, when all agent follow the policy and only retailer has stock-out. Since there is no optimal policy in general, this AI algorithm is pretty useful and can be applied to more complex supply chain problems.
- Sterman, J. D. (1 March 1989). "Modeling Managerial Behavior: Misperceptions of Feedback in a Dynamic Decision Making Experiment". Management Science. 35 (3): 321–339. doi:10.1287/mnsc.35.3.321.
- Thompson KM, Badizadegan ND, 2015. "Valuing information in complex systems: An integrated analytical approach to achieve optimal performance in the beer distribution game." IEEE Access 3:2677-2686. doi: 10.1109/ACCESS.2015.2505730.
- Croson RTA, Donohue KL, Katok E, Sterman J, 2014. "Order stability in supply chains: Coordination risk and the role of coordination stock." Prod Oper Manage 23(2):176-196.
- Oroojlooyjadid, Afshin; Nazari, MohammadReza; Snyder, Lawrence; Takáč, Martin (2017-08-19). "A Deep Q-Network for the Beer Game: A Reinforcement Learning algorithm to Solve Inventory Optimization Problems". arXiv:1708.05924 [cs].
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