One of the challenges of teaching operations management is getting students to think beyond the formulas to solve real-world problems. Simulation games can be very helpful in getting students to think through problems in an environment with complexity, uncertainty and constraints. However, for a simulation game to be effective, it must illustrate specific class concepts, provide an appropriate level of complexity and be user friendly.
This paper reviews Littlefield Technologies, a web-based simulation game where student teams manage a factory. I have found that Littlefield Technologies is an effective teaching tool that the students seem to really enjoy. What I really like about Littlefield Technologies is that the simulation games are strongly linked to class concepts- the students are forced to think logically about the problems that they are facing and they learn from iterative experimentation. This experimentation is in contrast to homework problems, where I often see students plugging numbers into formulas without really understanding the problem.
For the simulation, the students group themselves into teams of three to four and each team receives its own factory to manage for a period of time, typically one to two weeks. The students are told that the objective of the game is to maximize the cash generated by the factory over the product lifetime. The factory assembles digital satellite system receivers from kits of components which are purchased from a single supplier. The assembly process consists of four steps that are carried out at three workstations. At Station 1, components are mounted and soldered onto PC boards. At Station 2, the boards are tested. At Station 3, the components are tuned. Finally, in the fourth step, the boards go back to Station 2 for final testing. Figure 1 illustrates the factory layout as the students see it on the simulation web page. Students can obtain information about their factory and make decisions by clicking on the icons on the factory layout. The simulator runs such that one hour in real time is equivalent to one day in the factory. This allows the run time to represent the product lifetime.
There is also a competitive aspect to the simulation. Throughout the simulation teams are continuously ranked from first to last based on their cash position. Thus, at any time during the game, each team can compare its cash status to that of all the other teams. This competition really motivates a number of teams. Many students get addicted to the game and spend a lot of time checking how they are doing against the competition. On a number of occasions, students have told me that the competition drove them to make decisions that they would have not made otherwise.
Littlefield Technologies has two main assignments: Capacity Management and Customer Responsiveness. In addition, there are several variations of each of these two games to choose from. I run Capacity Management first, after covering forecasting, capacity management and queuing. Several weeks later, I run Customer Responsiveness, after covering inventory management concepts such as the economic order quantity (EOQ), safety stocks, re-order point, lot sizes and set-up times.
I have used Littlefield Technologies in both my undergraduate and MBA operations management courses. Overall, I have used it in three undergraduate classes with a total of 150 students and in one MBA class with 40 students. I run the same Capacity Management game for both the undergraduate and MBA classes, but for the Customer Responsiveness game I run a less complex version for the undergraduate students.
In the Capacity Management game, students can buy and sell machines at each of the three workstations. They can also change the way Station 2 (the testing station) is scheduled. They can choose first-in-first-out (FIFO), give priority to step 2 or give priority to step 4. The purpose of this assignment is for students to utilize queuing concepts and forecasting methods to manage capacity. This game takes 7 days.
In the simulation, customer demand is random and the students are told that demand is expected to grow at a linear rate for the first several months, stabilize, and then decline at roughly a linear rate. Customer orders that are not filled within the quoted lead time incur a late penalty. If the order is too late, then it will not generate any revenue. When the game begins there are 50 days of history and Station 1 is already near 100 percent utilization. Thus, the students are faced with a tradeoff between capacity and waiting time. They can buy machines to reduce waiting time in order to meet the quoted lead time; however, they don’t want to buy too many machines because the machines are expensive.
I find that most students figure out that there is a tradeoff between capacity and waiting time. However, many teams wait until the lead times become so long that they are making little or no revenue before they buy machines. Since these reactive teams generally do not do as well as proactive teams, students learn that it is better to extrapolate station utilization by forecasting demand in order to determine when utilization will approach 100%. In my MBA class, I found that several teams went a step further by estimating the amount of cash that would be lost to delays if they did not purchase a machine and comparing this lost revenue to the cost of a new machine. These teams found that it was better to accept some lost revenue during the peak months of demand rather than buy another machine.
In the Customer Responsiveness game that I run in the MBA class, students make capacity and scheduling decisions as they did in the Capacity Management game. In addition, students make inventory and lot sizing decisions, choose between three customer contracts, and are extended a line of credit from which they can borrow money. The purpose of this assignment is for students to manage inventory, capacity and cash in order to maximize their cash position at the end of the game. This game takes 14 days.
In the simulation, customer demand is random and the students are told that the average demand will not change over the product's lifetime. The students can charge more if they are willing to quote shorter lead times. As a result, the students want to reduce the time that it takes to get orders through the factory. The most obvious way to reduce the lead time is to buy more machines; however, when the students begin the game they face a cash constraint that prevents them from purchasing the machines that they need to meet the lead time requirements for the most lucrative contract.
This game enables students to gain a better understanding of the behavior of production systems. Many students realize through experimentation that their actions sometimes result in outcomes different from what they expected. For example, since their cash position at the beginning of the game limits them from buying capacity, many teams first experiment with reducing the lot size to try to get orders through the factory faster. However, students find that setup times are so significant that smaller lot sizes cause queuing problems at stations 1 and 3, resulting in even longer lead times.
In addition, this game enables students to apply course material in an environment that is somewhat representative of a real situation. For example, since there are setup and inventory holding costs, some teams calculate the economic order quantity (EOQ). However, these teams find that the EOQ is so large that implementation of it at the beginning of the game will significantly deplete their cash. Since they are trying to build up cash to buy machines, most teams who calculate the EOQ conclude that it doesn't make sense to implement the EOQ until more cash is generated.
It is possible for teams to go bankrupt; however, a line of credit becomes available to all teams after a certain period of time, enabling the bankrupt teams to borrow money and get back in the game.
The Customer Responsiveness game that I run in the undergraduate class is a simplified version of the Customer Responsiveness game discussed above. The undergraduate version starts with a large cash position, does not offer a line of credit, and does not allow modification of the lot size. As a result, this game focuses on managing capacity and inventory. This game takes 7 days.
I have found that the undergraduate students tend to perform less quantitative analysis than the MBA students. The undergraduates tend to rely more on experimentation- they make decisions, observe the effects of their decisions, and then adjust their decisions. Although it would be better if they used more quantitative analysis to help in their decision making, I find that this game is a wonderful way to get them to think through problems logically. For example, at the beginning of the simulation the reorder point (ROP) is set low, resulting in stock outs. Most teams recognize that the ROP needs to at least cover the expected demand over the lead time. Furthermore some of these groups will recognize that since there is uncertainty, it makes sense to add safety stock. Other groups do not immediately see the need for safety stock; however they observe that they occasionally stock out and this observation gets them to adjust their ROP to include some safety stock.
For each of the two simulations, each team is required to write up a report that summarizes the actions that they took during the simulation, why they took those actions, and, in retrospect, whether or not they did the right thing. I base their grade on their ability to effectively explain what they did and why and the quality of their analysis. For teams that finish at the top of the standings, I give bonus points. Although I do not penalize teams for performing poorly in the standings, not surprisingly, there tends to be a correlation between the quality of the analysis and the final standings.
On the day that the reports are due, I facilitate a 20 to 30 minute discussion of the simulation. I will ask for volunteers to share what they did during the simulation and why they took those actions. I wrap up with a discussion on the key learnings from the simulation.
In two of my undergraduate classes I have conducted student evaluations of Littlefield Technologies. The students were asked to indicate how strongly they agreed with three statements with 5 representing "strongly agree" and 1 representing "strongly disagree". The three statements and the average results of 67 evaluations are listed in the following table.
|These games contributed to my understanding of
capacity management and inventory management.
|In these games, I frequently found myself actively
thinking about the simulation game and what decisions I should make.
|As a result of these simulation games, my interest
and curiosity about operations management has increased.
The students were also given the opportunity to write comments. Most comments were positive about their experience with the simulations. Some of the students use the word “fun” to describe their experience with the game. A few students criticized the cost of the game, which is $20 per student. (Littlefield Technologies charges $15 and the campus bookstore marks it up to $20.)
I have found the work load for running these simulation games to be very reasonable. The software that runs Littlefield Technologies resides on a central server at the company Responsive Learning Technologies so instructors don't need to worry about software installation, maintenance or platform compatibility. Students access the simulation via the Internet and I have not yet had a single complaint from students about access problems. Also, by using the assignments that have already been created, the instructor doesn't have to worry about creating and debugging assignments.
There is some administrative work prior to the start of the first simulation. The instructor needs to make sure that the student teams register for the game by the time the simulation starts; otherwise, they will not be able to play the game. The registration is web-based and students need to enter an access code that they get for their $20 fee. In order to motivate students to register on time, I tell them that registration is due by a certain date (a couple days before the start of the simulation) and that it is worth one point of the ten point assignment.
The most time consuming part of this assignment for me was grading the reports. Last semester I had 40 undergraduate teams, and I spent many hours grading reports.
To summarize, I find Littlefield Technologies an excellent simulation game for both undergraduate and MBA operations management courses. Students are forced to think logically about the problems that they are facing, they can apply class concepts and they learn from iterative experimentation. In addition, most of the students seem to really enjoy it.