Upgrade Your Teaching Game

Supply chain management (SCM) is one of the operations management practices that is abundantly present in our modern daily life. Almost any merchandise we purchase is a product of some supply chain. Even people who don’t consider themselves to be supply chain professionals experience some aspects of SCM in their daily life. One can simply experience transportation management when tracking the delivery of an online order, logistics planning when moving between apartments, inventory and warehouse management while walking through large stores like IKEA or Costco, and demand forecasting when planning an extended family dinner or a party. The list goes on. Knowing this, one would think teaching SCM concepts can almost be effortless. After all, we’d be teaching with examples from students’ lives begging to be used. Unfortunately, this is not usually the case.

While the concepts are generally accessible and examples are abundant, having students truly internalize what SCM is and appreciate the system complexity and interdependencies found within it is a different level of challenge. Enabling students to critically think of SCM issues and address them with organically developed solutions proves to be an even more challenging endeavor. This can be attributed to the high level of complexity found in typical supply chains, and the fact that very few people actually have a view of the entire process to comprehend its true nature.

The identification of this challenge is not new. Educators tried to address it through various approaches, however, one proved to be especially effective: educational games. Perhaps the first well-known example is the “Beer Game” [1], which was devised by Jay Forrester in the 1960s while investigating supply chain system dynamics at MIT. The game design is simple – each player assumes the role of a station manager at one of four stations: manufacturer, distributor, wholesaler, retailer. The game is played in turns with each simulating a week in the supply chain. Players decide on orders to their supplier to meet customers’ demands. Through this interaction, they experience some of the challenges found in real supply chains, and through competition with other teams, they develop and test strategies to address these challenges in an attempt to raise their supply chain performance above that of their competitors. Performance is commonly measured in demand fulfilment and operational cost minimization.

While the game itself is simple, learning and deploying its mechanics in a single class period can be hectic, especially during an intense session of competition, which frequently is the case. The additional mental effort spent on keeping up with the game’s mechanics inhibits the students’ ability to think strategically about solutions to issues that extend beyond their own station. Naturally, several computerized online games came up to address this issue. This article discusses the use of a recent addition, the X-Supply Game (XSG) [2,3], in SCM education. While XSG builds on previous game designs, its contribution is highlighted after discussing its use in education. 

Figure 1: Examples of game topology designs possible in XSG.

The X-Supply Game

XSG is an online, synchronized turn-based and multiplayer cooperative simulation game. It simulates system dynamics found in real supply chain, but on a small-scale suitable for classroom setting. Deploying the game in SCM classes is straightforward. A brief 10-minute introduction and a quick demonstration of the user interface is usually sufficient to introduce the activity to players. Completing a 45-week simulation game typically requires about 60 minutes of class time. The game is played in synchronized turns, with each turn representing a week in the supply chain operations. While time needed to complete each turn can be left to players, it is best to limit it to 90 seconds to add an aspect of realism as decisions are made on deadlines. A side benefit of limiting turn-time is the greater control over total game time to ensure it fits in a class period. In XSG, limiting turn time is a matter of configuration.

Multiple games can be created such that teams of independent supply chains, each made up of several players, one player per station, compete for the best supply chain performance. Each week, players analyze their stations’ standings and decide on orders to suppliers and shipments to customers. Players must complete this while simultaneously dealing with multiple competing objectives. Throughout the game, players strive to minimize their inventory and fulfill their customers’ demands without resorting to backorders, while at the same time attempt to efficiently utilize transportation resources used to ship products.

Players make their decisions based on customer demand, available inventory, current backorder levels and in-transit shipments. Players also take into consideration information on their supply chain setup such as: holding, backorder and transportation costs; ordering and shipping delays; and transportation cost and capacity. Furthermore, players need to engage in some form of demand forecasting to develop their ordering strategy. They also consider previous suppliers’ performance in deciding where to source their upcoming orders from.

The first few weeks are often chaotic as players come to terms with their station responsibilities and realize the impact of their decisions on other players and the supply chain as whole. However, players quickly gain understanding of game dynamics, and by the time the simulation arrives at weeks 15 to 20, they start to devise strategies to improve their supply chain performance. The best teams will realize that communication and coordination are key and will form informal lines of communication around order and shipment planning.

Post-Game Debriefing Session

After game completion, a debriefing session is key to allow students to reflect on and analyze the system dynamics that dominated game results. Clearly, supply chain performance will vary from team to team depending on the quality of team coordination developed between players throughout the game. Still, in most cases supply chain performance will oscillate between two performance states: high backorders and high inventory levels. Perhaps most surprisingly to players is the fact that both states could coexist in the same supply chain at the same time, with some stations starved for inventory and others overflowing with inventory. This combination is typically due to lack of proper communication and planning.

Topics covered in the debrief could include supply chain risks management, impacts of demand volatility, inventory management strategies, multiobjective supply chain performance and the role of network design. Particularly, supply chain risk and demand volatility provide opportunities for creating interesting scenario narratives where sudden demand drops and spikes or ordering and shipping capacity limitations could serve as catalyst for strategy development. For example, in a humanitarian supply chain scenario we use a cease-fire breakdown to simulate shipment blockage, while demand continues to accumulate. Experience shows that running several games competitively while including strategically timed disruptive events provides a fun learning environment that is conducive to the exploration and “borrowing” of best SCM practices across teams. 

More Complex SCM Decisions

While XSG is clearly influenced by the Beer Game and some of its descendants, it takes a different approach to the game. Since XSG automates all game mechanics, players have freedom to explore more complex SCM decisions, raising the bar for what can be pedagogically achieved from the game. XSG allows supply chain topology (i.e., network design) to be created virtually in any design. (Closed loop supply chains are not supported.) This includes arbitrary number of nodes between upstream suppliers and downstream consumers, and the ability to set them up into multiple suppliers and customers per station.

Figure 1 shows two example game topology designs created in XSG. An additional feature of XSG is that almost all of its game setup is configurable including costs, delays, transportation capacity and ordering/shipping limits. This level of configurability in game setup and topology allows a great deal of flexibility to the educator to customize players’ experiences.

In addition, XSG allows the instructor to set up the game such that players have control over ordering, shipping or both decisions. Figure 2 shows the XSG player screen with both decisions enabled. While order decision-making is shared with the original Beer Game, the shipping decision is a new addition and opens up the opportunity to introduce transportation resource utilization and environmental footprint tradeoffs with demand fulfilment as additional performance metrics. This enriches the player experience with additional layer of realism as the complexity of multiobjective supply chain performance measurement is introduced. This also allows the instructor to include the concept of SCM through triple bottom line (TBL) performance measurement, where economic, social and sustainability metrics are simultaneously managed.

(a) Weekly inventory and backorder performance

(b) Overall station performance

Figure 3: Game results reporting in XSG.

Figure 3 shows some of the supply chain metrics used in reporting game results. XSG also allows station decision-making automation using simple order and shipping rules. This allows the creation of larger supply chain networks where players manage only a portion of the stations and still get to experience the effect of a large supply chain on system complexity.

XSG has been used in teaching SCM and operations management courses at the undergraduate and graduate levels at Zayed University since its creation in 2017. Students’ reception of the class activity is overwhelmingly positive. Instructors notice a different level of interaction and discussion of SCM concepts once the class return to regular delivery methods, as students relate to and benefit from their game experiences.

Since its announcement on INFORMS Connect in mid-February 2019, more than 450 users from 30 countries visited the XSG website. The game is available as an open source project on GitHub [4], and readers are welcome to use the server instance hosted by Zayed University at https://istm.zu.ac.ae/xsg in their own classes. Instructor feedback and comments are also encouraged to help fine-tune XSG and widen the range of teaching scenarios in which it can be deployed in.

References

1. Sterman, J. D., 1984, “Instructions for Running the Beer Distribution Game,” System Dynamics Group Working Paper D-3679, MIT, Sloan School of Management, Cambridge, Mass.
2. Salman, S., and Alaswad, S., 2018, “The X-Supply Game,” Proceedings of the 2018 Industrial and Systems Engineering Conference, Orlando, Fla.
3. Salman, S., 2018, “The X-Supply Game (XSG)” (online), https://istm.zu.ac.ae/xsg.
4. Salman, S., 2018, “The X-Supply Game GitHub Repository,” (online), https://sinansalman.github.io/xsg/.