Fruit Beer Game

Step into a live supply chain and manage your node — as a Retailer, Wholesaler, Distributor, or Factory — making ordering decisions each round while balancing costs and service levels. The Fruit Beer Game offers a rare opportunity to experience the Bullwhip Effect firsthand, and to walk away with a fundamentally different way of thinking about supply chains.
Academic Partner:
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LEVEL
Undergraduate, MBA, Executive Ed, Graduate
TYPE
Multi Player
DURATION
60 mins
DISCIPLINE
Operations Management
Introduction

The Fruit Beer Game is a digital, multi-round supply chain simulation built upon the classic MIT Beer Game. Four players each manage one node in a linear supply chain — Retailer, Wholesaler, Distributor, and Factory — placing orders upstream each round to meet downstream demand while striving to minimise total supply chain costs and maximise service level. AI bots automatically fill any unoccupied roles, ensuring the supply chain remains complete at all times.

The simulation vividly demonstrates the Bullwhip Effect: how small variations at the retail level create massive order  amplification upstream. This dynamic mirrors real-world episodes such as Procter & Gamble's Pampers supply chain in the early 1990s, where modestly fluctuating retail demand produced severe order swings across wholesalers, distributors, and  raw material suppliers — tying up working capital, disrupting production schedules, and degrading service levels. The Fruit  Beer Game recreates these dynamics in a controlled classroom setting and concludes with a personalised automated debrief that helps each participant connect their in-game decisions to broader systemic insights, making the learning both experiential and analytically grounded.

Learning Objectives
  • Bullwhip Effect diagnosis
  • Systems thinking mindset
  • Inventory trade-off management
  • Information asymmetry awareness
  • Local vs. global optimisation
Key Features
  • Configurable demand patterns: stable, seasonal, stepped, or fully stochastic
  • Adjustable parameters including initial stock levels, holding and backlog costs, lead times, and demand visibility
  • AI bots automatically fill unoccupied roles, keeping the supply chain complete regardless of participant numbers
  • Rich simulation outputs: inventory levels, backorders, total cost breakdowns, and order-quantity charts across all four nodes
  • Personalised automated debrief generated for every participant at the end of the session



Educational Outcomes
  1. Shift from blaming individuals to recognising that system structure drives collective outcomes
  2. Ability to diagnose the Bullwhip Effect in real supply chains
  3. Capability to design information-sharing mechanisms that reduce demand amplification
  4. Skill to evaluate ordering policies through a systems lens rather than local optimisation
  5. Internalisation of the central insight: no individual made irrational decisions, yet the system as a whole behaved irrationally
Topics Covered
Bullwhip Effect
Systems Thinking & System Dynamics
Inventory Management
Information Asymmetry
Local vs. Global Optimisation