Use of Computer Simulation as a Pedagogical Tool in ...



Use of Computer Simulation as a Pedagogical Tool in

Teaching a Supply Chain Management Course

Ike C. Ehie, Kansas State University

&

Randall G. Chapman, Arizona State University West

Abstract

The use of games and computer simulations as classroom instruction supplements has been widely discussed. A well-designed supply chain simulation provides students with a hands-on learning opportunity in a non-threatening competitive environment similar to the real world. In this paper, the authors share their instructional experiences with the LINKS Supply Chain Management Simulation in a supply chain management elective. Within LINKS, students learn to appreciate balance and alignment in managing supply chain trade-offs in the face of competitive dynamics in an evolving marketplace. LINKS provides a means by which students appreciate information flows, develop their ability to work effectively in teams, enhance fact-based analysis and decision making, and gain hands-on understanding with financial report interpretation. This pedagogy embraces the Blooms taxonomy (Bloom, 1956) by allowing students to apply their supply chain knowledge in a business simulation of real-life supply chain management challenges, make critical supply chain decisions, analyze ensuing results, and evaluate performance of their firms based on the decisions made. The paper also reviews two other widely used supply chain simulations.

Introduction

Supply chain management (SCM) is a term that subsumes the traditional areas that include operations management, marketing, information systems, and strategy. The management aspect of supply chain has largely drawn from the intellectual tradition of logistics and operations management (New, 1997). The development of the supply chain idea can be traced to the emergence of systems theory and associated notion of holism (Cavington, 1992). This is based on the premise that the behavior of a complex system cannot be understood completely by the segregated analysis of its constituent parts (New, 1997). Most manufacturing enterprises are organized as networks of manufacturing and distribution sites that procure raw materials, transform them into intermediate and finished products, and distribute the finished products to customers. The simplest network consists of one site that performs both manufacturing and distribution. More complex networks span multiple sites that may be scattered around the world.

Management simulations and games continue to gain popularity among business schools. The increasing use of simulations is partly due to the changing educational interest level of students. At the 2001 INFORMS meeting, four types of students were identified: (1) the “enthusiastic” student who does everything required in the syllabus and asks for more material; (2) the “practical” student who does everything required in the syllabus, but nothing more; (3) the “efficient” student who wants excerpts or summaries from all sources listed in the syllabus and lectures especially those that matter for the exam; and, (4) the “parent” student who wants to complete all studies during hours convenient with their childcare needs. Hannibalsson (2004) surveyed students in an operations management class and found that whereas 80 percent of his students saw themselves as practical students, only 5 percent of his students considered themselves as the enthusiastic students. Efficient and single parent students accounted for 11 percent and 3 percent, respectively.

A similar study was given in an elective course in supply chain management class in 2006 and the results found that 60 percent of the students considered themselves as “practical” whereas 30 percent saw themselves as “efficient.” Only four percent of the student considered themselves as “enthusiastic.” The interesting aspect of these findings is the huge disparity between the efficient and the practical students. Students prefer to belong to the practical group even though they sometime act as if they belong to the efficient group (Hannibalsson 2004).

Students of modern age who have been described as the “millennia” generation view education as a means to reaching an end rather than an being end to/of itself. The increase in the practical students places some challenges on the traditional form of lecture format in the classroom. These students are better learners in an active learning mode rather than the traditional lecture format that have been used extensively in business schools. Computer simulations or games appear to be more amenable to the practical students who are the majority of students. Hannibalsson (2004) reported that 74 percents of students learned a lot from playing the Manufacturing Game and the Littlefield Technologies simulation as part of their operational management course. Ninety-eight percent of the students felt that the games were helpful tools in training them to deal with uncertainty. The students were very motivated while playing the games and they worked very hard in trying to beat other teams. Students tend to be more involved with their learning and would spend more study time in the course than they would have spent in a traditional lecture format.

The simulation pedagogy is used in non-business fields. Airplane pilots use complex computer-driven simulation to replicate actual flying conditions in extreme and realistic scenarios. This allows the pilot trainee to assess the various levels of risks under the varying flying conditions. In the field of medicine, anesthesiologists use computer-controlled dummies to imitate the psychological responses of humans undergoing anesthesia (Puto, 2004). These simulated learning environments provide a platform in which active learning is enhanced and retained. Likewise, computerized business simulations can be used to expose business students to a wide range of real-world problems and scenarios. Through simulations, business students can be immersed into the inner workings of an organization and learn the interplay among the various business functions. Computer simulations should be used to augment classroom instructions. The more closely the simulation are tied to the ongoing curriculum, the more quickly students will learn the key business concepts (Puto, 2004).

Computer simulation tools are not foreign to the supply chain curriculum. In a survey of attendees of the 2003 Council of Logistics Management Educators Conference, most of whom are college professors, about 64% of the respondents were either currently using or had previously used a supply chain simulation (Hanna, Gibson, & Chapman, 2005). The Beer Game simulation topped the list as the most frequently used simulation in the supply chain curriculum. In most cases, a simulation is used to illustrate specific content or topic in the course. For example, the beer game is a classic illustration of the “bullwhip” effect.

The advantage of management simulations is that they allow more rapid time compression, quick feedback to the learner, and a less risky environment. Lessons learned are evident within hours or days, not months or years. A well-designed management simulation can provide students with a realistic education and training experience in the relative safety of the simulation’s operating environment. Computerized business simulation help students master the skills that are not automatically learned in today’s generally accepted business curriculum (Puto, 2004).

In the following sections, overviews are provided for three supply chain simulations currently used in business schools. Table 1 compares and contrasts these three supply chain simulations.

The Beer Game

The use of simulation in teaching supply chain management gained prominence with the development of the Beer Distribution Game (the beer game). The beer game is a role-playing simulation of industrial production and distribution systems developed at MIT to introduce students of management to the concept of economic dynamics and computer simulation (Sterman, 1989). Different versions of the beer game have evolved and this includes a computerized simulation of the beer game. More recently, an online version of the game was developed that could be freely accessed through the Internet.

The traditional beer game has a playing board that represents four stages of the beer supply chain process: factory, distributor, wholesaler, and retailer. Each position is identical (except for the factory) with an inventory of beer in cases represented as poker chips. Each stage receives orders from the downstream of the supply chain. Orders are placed from the upstream sector. Beer is received after a shipping delay (in the case of the factory, beer is received after a production delay). The beer game process includes these steps: (1) receive shipment; (2) fill order; (3) record inventory/backlog; (4) advance order; and, (5) place order. In the traditional beer game, demand presented to the retailer doubles in fifth week of a 40-50 week simulation runs and remains at that level through the end of the game.

The object of the game is to minimize costs for the team. In computing the systems cost, backorder cost (out-of-stock) cost are weighted twice as much as the carrying/holding cost on a weekly basis. Therefore, each team is penalized twice as much for unfilled orders compared to inventory costs. The cost of each stage (retailer, wholesaler, distributor, and factory) are added together for the total length of the game, which generally runs for about 40 weeks, to determine the cost of the game. The team with the least cost wins the game.

Any form of communication is prohibited during the game between any two sectors, creating substantial uncertainties. The only sources of information to the players are orders placed by the upstream sectors. The information deciphered from the orders tends to be distorted as one moves upstream through the supply chain. This distorted information has misguided the upstream sectors in planning for their inventory and production system. This distortion tends to increase as one moves upstream and this has been labeled the “bullwhip effect.” Distorted information from one end of the supply chain to the other can lead to excessive inventory investment, poor customer service, lost revenue, misguided capacity planning, ineffective transportation, and missed production schedules (Lee, et al, 1997).

Although efficient in illustrating how to manage the operational aspect of the supply chain, the beer game is deficient in better managing the systems-wide supply chain. In many ways, the supply chain is managed in “silos” by different managers at each stage based on their individual intuition, experiences, and objectives (Simchi-Levi, et al. 2003). Their main objective is to optimize the individual performance instead of maximize the system-wide performance. The concept of total value proposition is elusive in the game.

While playing the beer game, students often become so preoccupied with game mechanics (making sure they are following the instructions of the game correctly) that they have no time to develop a competitive strategy for the game. Because of this lack of focus on an effective strategy for playing the game, students are more likely to blame their immediate downstream counterpart for their woes rather than search for potential flaws in their own strategy. The secrecy placed on information sharing is contrary to the collaborative atmosphere that is present in current business practices. In real life, it is unrealistic to expect that managers of each of the supply chain facilities would not be informed of significant changes in the demand pattern (Simchi-Levi, et al. 2003).

The computerized beer game was developed precisely to address the difficulties inherent in the traditional beer game. These difficulties are managed by shortening the cycle time and centralizing information and decision making (Simchi-Levi, et al. 2003). Students that have used the beer game expressed the desire to move further into a simulation experience that would allow them to gain a total appreciation of the value chain and not focus just on their individual performance.

The Supply Chain Game

The Supply Chain Game is a web-enabled discrete event simulation of a network of factories and warehouse geographically distributed across as many as five regions. The game is developed under the guidance of Sunil Chopra and Philipp Afeche, both faculty members at Northwestern University’s Kellogg School of Management.

In a typical setting, students are divided into teams and compete against each other in one or two assignments lasting a week each. To meet different demand patterns in five regions, student teams set production and inventory control parameters, transportation choices, and add new factories and warehouses. The objective of the game is to maximize cash position at the end of the game. The network forms a supply chain that is managed by a single firm producing a single product (drums of a chemical) for regional markets. The online game covers supply chain decisions on forecasting, logistics, advanced inventory control, and supply chain network design. The simplicity of the game enables the game to be played with little or no assistance from the instructor. Students are grouped in teams of two to six members.

The Supply Chain Game has OneRegion and Network assignments. In the OneRegion assignment, students manage inventory and distribution decision in a single warehouse and a single region. Once the game begins, students can add factory capacity and change the reorder point, determine the reorder quantity, and choose the shipping method from factory to the warehouse. The game begins with a factory capacity of 20 drums per day, a reorder point of 300 drums, an order quantity of 150 drums, and the shipping mode is by trucks. At the start of the game, each team has a cash reserve of $2.7 million.

Forecasting demand is the key driver to making good decision in the game. The game begins with a two-year demand history in the main warehouse. Students are privy to the demand history and they could plot out the profile of the demand and perform forecasting to project future demand. With this historical data, students are able to develop forecast for future periods. Once the forecast is generated, students can begin to develop their inventory management system.

In the Network assignment, students are required to make decisions based on their learnings from the first assignment. In addition, students are expected to make decisions that cover the four regions in the network. The learning objectives include forecasting, inventory and production control, supply network design, and logistics.

The LINKS Supply Chain Management Simulation

The LINKS Supply Chain Management Simulation is a comprehensive, competitive strategic supply chain management simulation. LINKS is web-based, with no software to download/install. LINKS is based on a classic build-to-plan manufacturing environment. Inventory pipeline management underlies LINKS, from procurement of raw materials and sub-assembly components, to manufacturing, through to distribution and transportation network design and management. In addition, upstream product development and the downstream customer-facing elements of service and generate demand provide an extended, business-wide view of supply chain management. Information technology options and extensive research studies define an information-rich milieu for supply chain management strategy, analysis, and planning.

A scaled-down LINKS variant, the LINKS Supply Chain Management Fundamentals Simulation, is available for instructors interested in a more “modest” simulation footprint (and time commitment) in their courses. By eliminating product development and service from the full simulation (and automating/eliminating other minor decisions in various parts of LINKS), the “fundamentals” variant can be used successfully in a few as five simulation rounds. LINKS “fundamentals” is targeted at introductory operations management and supply chain management courses.

Student teams are tasked with improving the financial and operating performance of their firms. LINKS provides students with a wealth of financial and operational information to assist in performance assessment. LINKS teams/firms consist of two to five students. A maximum of eight firms comprise each LINKS industry, with simultaneous parallel industries used in larger class sizes.

The LINKS business environment involves the manufacturing, distribution, and sales of “set-top boxes” in a supply network with three regional markets. A set-up box is a high-tech electronic product (telephony applications) purchased by individual consumers for home use and by a wide range of businesses. There are two set-top box product categories, hyperware and metaware. Although these products share many elements in common within the supply chain, the products are different and they appeal to different market segments.

Network design includes a manufacturing plant and a distribution center located in region 1. Products are manufactured in the plant and are distributed through the distribution center in region 1. Products can be finished at the plant as regular production or they could be semi-finished to be finished at a distribution center (i.e., postponement). Markets in regions 2 and 3 can be served in one of three ways. The can receive shipment directly from the distribution center in region 1, build a distribution center in regions 2 or 3 and ship products to the regional distribution center for final shipment to the customers, or lease distribution centers in regions 2 or 3. The distribution center in each region include the warehouse which store inventory of the product and from where orders are filled. The warehouse also carries inventories of sub-assembly components (SAC) which are used as replacement parts for within-warranty failures. There are two market channels, a direct channel which bypasses retailers and an indirect retail channel. The LINKS simulation provides students with an opportunity to have a more system-wide perspective of supply chain.

The LINKS simulation is demand-driven. Performance in the game relies on forecast accuracy and demand visibility. An improvement in the forecast accuracy results in a significant improvement in order fulfillment which translates into bottom-line profitability. Teams have the ability to aggressively shape demand with real-time changes in pricing, marketing spending, product design, or service. With the ability to configure products, teams can balance supply and demand by liquidating old products while ramping up new product configurations, thus transitioning from old to new products with minimum excess and obsolete inventory.

The full version of LINKS could be played over the course of a 16-week semester with up to 12 simulation rounds played during the semester. In each week, after the game is run, students access their financial and operational results via a web browser. KPIs include financial, operational, and customer-facing measures. A multi-factor, balanced scorecard style of grading system exists to assist the instructor in overall firm performance assessment. LINKS includes a wide-variety of instructor-optional switches that permit the simulation to be customized to a particular instructor’s interests and requirements. For example, typical mid-event enhancements include activating an additional product and/or region, changing some underlying cost parameters, or changing demand growth patterns.

In addition to the financial and operational reports, LINKS has an information-rich environment with many optional research studies available for purchase within the simulation. These research studies are one way to drive home some of the supply chain issues faced by businesses in the real world. Students are encouraged to take advantage of the research studies to help improve their performance in the simulation. The LINKS website also provides an ample supply of resource material and a number of tutorials on key concepts such as inventory management, distribution strategy, and postponement strategy.

LINKS is played starting in week 4 of a 16-week semester in a supply chain management elective. Students enrolled in the course are expected to have completed the introductory course in operations management. In the first four weeks of the course, students are provided with an overview of supply chain management and subsequent discussion on supply chain strategy. During this period, the LINKS simulation is introduced and discussed. Students are required to purchase a copy of the manual for a minimum cost. The LINKS manual is available for a free download from the LINKS website. However, to ensure that every student has a personal printed copy of the manual, students are required to purchase a locally-produced photocopy. Quizzes are given regularly during the first four weeks to test student knowledge of LINKS. The students are formed into teams of five members, with the ten teams in the class being grouped into two parallel industries. A syllabus of the course is enclosed in the appendix.

Half-way through the course, each team was asked to prepare a 2-3 page executive summary of their performance to date and the strategy that they have adopted. The team is also expected to provide the strategy they plan to follow for the reminder of the simulation. The team is asked to provide this reflective summary based on the LINKS Supply Chain Strategic Audit exercise completed in class.

At the conclusion of the simulation, each team is expected to provide a written annual report of their LINKS performance and provide a 10-15 minute presentation to their shareholders. During the final presentation, they are expected to conduct a SWOT analysis of their firm and provide recommendation for future firms that will run the simulation. To encourage individual student active participation, the semester exams have a large component based on LINKS. This addresses the issue of student being “free loaders” within their teams. Also, there would be peer evaluation that will be factored into the individual grade each student receives in the course.

Table 1: Comparison of Three Supply Chain Management Simulations

|Criteria |Beer Game |Supply Chain Game |LINKS Supply Chain Management Simulation |

|Overview |Web-based role playing simulation |Web-based simulation in which student |Comprehensive, web-based simulation in |

| |that allows players to assume one of |teams make demand and network decisions|which student teams make decisions |

| |four supply chain roles (retailer, |for a chemical company |covering all aspects of supply chain |

| |warehouse, distributor, and plant) | |management |

|Scope |Narrow |Medium |Extensive (typically played over 9-12 |

| | | |weeks) |

|Major Takeaway |The Bullwhip Effect |Inventory and Network Management |Supply Chain Management Strategy, |

| | | |Analysis, and Planning |

|Level of Difficulty |Moderate |Low |High |

|Period of Play |90 minutes (single class session) |2 weeks |9-12 weeks |

|Size of team |Minimum of 4 students |Minimum of 2 students |Minimum of 2 students, but teams of 4-5 |

| | | |students are typical |

|Cost |Free |$20/student |$45/student ($30/student for |

| | | |“fundamentals” variant) |

|Instructional Support |Low |Moderate |High |

|Source |MIT |Responsive Learning Technologies |Randy Chapman |

| | |pom@ |Chapman@ |

|Financial Analysis |No |Yes (limited) |Yes (extensive) |

Conclusions

Computer simulation can be a powerful educational tool that enhances active learning in the classroom, especially when one notes that the majority of students consider themselves as “practical” students. This implies that students do everything required of them in a course but nothing more. However, efforts need to be made to ensure that simulations help student understand the underlying course concepts and don’t just view the simulation experience as an entertaining diversion.

Simulation designers should not only be cognizant of student learning processes but must understand the need to convey the theories and concepts that are being taught in the course. Although research seems to suggest the possibility that simulation are valuable active learning tools for many students, more attention needs to be paid to connecting theory and practice in simulation design.

References

1. Simchi-Levi, D., Kaminsky, P., and Simchi-Levi, E., Designing & Managing the Supply Chain: Concepts, Strategies, and Case Studies, McGraw-Hill, Irwin, 2003.

2. Lee, H., Padmanabhan, V., and Whang, S., “The Bullwhip Effect in Supply Chains” Sloan Management Review, Spring 1997, pp. 93-102.

3. Lee, H., Padmanabhan, V., and Whang, S. “Information Distortion in a Supply Chain: The Bullwip Effect,” Management Science, Vol. 43, No. 4, April 1997, pp. 546-558.

4. Chapman, R. G., LINKS Supply Chain Management Simulation, , July 12, 2005.

5. New, Stephen, J., “The Scope of Supply Chain Management Research,” Supply Chain Management, Volume 2, Number 1, 1997, pp. 15-22.

6. Bloom, Benjamin, et al., Taxonomy of Educational Objectives: The Classification of Educational Goals: handbook I, Longman Inc., 1956.

7. Puto, Christopher, “The Next Best Thing,” BizEd, May/June 2004, pp. 44-49.

8. Teaching Notes for OneRegion Assignment, the Supply Chain Game, Responsive Technologies, 2005.

9. Teaching Notes for Network Assignment, the Supply Chain Game, Responsive Technologies, 2005.

10. Hannibalsson, Ingjaldur, Classroom case study: University of Iceland Professor Increases Interactive Teaching in Operations Management to meet Changing Demand of Students, OR/MS Today, August 2001.

11. Hanna, J. B., Gibson, B. J. and Chapman, R. G., “Using Supply Chain Management Simulations to Facilitate Active Learning,” Council of Logistics Management Educators’ Conference Proceedings, 2004.

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