Integrating MS/OR Modeling into an ERP Course - INFORMS ...

FLOWERS Integrating MS/OR Modeling into an ERP Course

Integrating MS/OR Modeling into an ERP Course A. Dale Flowers Weatherhead School of Management Case Western Reserve University Cleveland, Ohio 44106 [email protected]

Abstract ERP is a subject with widespread applicability in industry, and one that presents challenges for companies to successfully implement. In this paper, I describe a graduate course in Enterprise Resource Planning (ERP) systems that integrates a whole series of MS/OR based case studies into the course, where all the cases are from the same company. The cases range from detailed and operational issues such as the bill of material explosion to more strategic issues such as hierarchical production planning and distribution network design. The data rich environment that ERP systems create is very fertile ground for the development and implementation of decision support systems via MS/OR modeling. This is an opportunity our profession should not overlook. This integrated set of case studies is facilitated via the use of one multi-function modeling package that makes it easy for students to use for the semester long course. The course is highly rated in the teaching evaluations that students complete, and the anecdotal feedback is that it is good preparation for the business world.

1. Introduction and Motivation

Table 1: Survey of Technology Usage by High Tech Users for Supply Chain Management.

There are many published articles dealing with the effective teaching of management science/operations research (MS/OR). In this paper, I present an effective way to integrate the use of MS/OR modeling into an enterprise resource planning (ERP) course designed for graduate business and engineering students. The course title is "Enterprise Resource Planning in the Supply Chain." The focus of the course is on the operations management aspects of ERP as opposed to accounting, finance, marketing, or human resource issues. ERP is an important element of success for most companies, so it is an important area of study for business and engineering students. From a Journal of Commerce Online survey (Anonymous,2004), "In the survey, conducted this year among 236 supply-chain professionals, 60.8 percent of respondents said they are currently using ERP (enterprise resource planning) systems to 'advance supply-chain evolution and drive results.'" This was almost double the second ranked technology, as shown in Table 1.

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In spite of the importance of ERP for improving supply chain operations, many companies have difficulty successfully implementing these complex systems and realizing a high return on their investment. In a survey in The Controller's Report (Anonymous, 2003), the discouraging statistics in Table 2 were revealed. It is obvious from that table that many more implementation projects go over budget than under. Given the importance of ERP as reflected in Table 1, education in ERP

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for business and engineering professionals should be a fairly high priority.

wealth of resources in terms of ERP software from supplier companies, and ERP books and articles, but not much about integrating the subject with MS/OR. Given the long term trend to introduce as much science as possible into the management profession, and the obvious relevance of MS/OR decision support technologies as an add-on to the basic ERP functions, this is a surprising void.

Table 2: Actual vs. Planned ERP Project Cost.

Peslak (2005) describes a twelve-step, multi-course approach to teaching ERP. It is based on success factors for ERP implementations, and builds on the KnowDules scheme of Watson and Schneider (1999). It focuses on successful ERP implementation and illustrates the operational integration that such systems afford, but does not integrate MS/OR modeling into the coursework. Draijer and Schenk (2004) describe teaching ERP software utilizing SAP R/3 to both bachelor and master degree students in a business school. I have seen course syllabi from other colleges and universities that take a similar approach. Certainly, graduates of such programs have a familiarity with a specific software system that can allow them to use it in their companies immediately upon graduation, provided the company that they join uses the same system that they studied. Due to the substantial overhead involved in learning a complex ERP system such as SAP, I have chosen not to use a large-scale commercial package. Instead, I choose to focus on the functions that all such packages have to perform in virtually the same manner. For example, the bill of material explosion process should not vary as a function of the software in which it is performed.

Having been a full time faculty member in a business school for 34 years, I have had the pleasure of watching the evolution of information systems and software to the point where use of them is as commonplace as use of a telephone. It wasn't always that way. For many years, MS/OR models could be constructed easily enough, but we couldn't get the data to solve them because company record keeping systems did not collect it. ERP systems are a major part of the solution to this dilemma and, as such, promise to usher in a new age of popularity and effectiveness of decision support systems. Our students need to be prepared to deal with that opportunity, and integrating the MS/OR models into the context of the business functions is an alternative to teaching the models in stand-alone MS/OR courses.

Strong, et al. (2004) describe integrating enterprise decision-making modules into undergraduate management and industrial engineering curricula via a common case scenario. They use Oracle's e-Business Applications Suite to "engage students in making decisions in the integrated, process-oriented, data-rich environments common in today's organizations." They focus on the areas of new product development and supply chain and order fulfillment processes. An important goal of their coursework is to provide students with a capstone experience of integrated decision-making at an operational level, similar to what a corporate strategy course might provide at a strategic level. Their focus is not on developing and using MS/OR decision

In the following sections of this paper, I will review the scant relevant literature for teaching an ERP course with integrated MS/OR modeling, describe the course and its context, the subjects included in the course, the series of integrated case studies utilized, and the benefits of this approach including student evaluation results.

2. Literature Review There has been very little published about how to teach ERP, and I have found no references on how to integrate MS/OR models into such teaching. There is a INFORMS Transactions on Education 7:1(3-17)

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models to guide the sophisticated decisions for which such models are appropriate.

cation exams, so there is a secondary benefit to students if they decide to pursue certification. Figure 1 is adapted from various figures in the text and illustrates the overall concept for the course. Not every subject listed in the figure is treated in-depth in the course. The list of topics included appears in section 4 of this paper.

In an extensive survey of MS/OR content at AACSBaccredited US business programs, Albritton et al. (2003) provided survey responses covering a list of 17 MS/OR topics. ERP was not one of the topics, but that is not surprising since it is a more comprehensive concept than a specific MS/OR methodology. The list did include inventory management and forecasting, two subjects that are often included in an ERP course. There is no indication that the teaching of these subjects is done by integrating the modeling into the application field of study.

The software utilized is the STORM package of Emmons et al. (2001). STORM is an acronym that stands for ST atistics, O perations R esearch, and operations M anagement. Its MRP module is central to the teaching of the ERP course, but clearly other multi-functional packages could be used, just as other texts could be used. It is convenient to be able to use one software package that covers all the modeling areas needed, so that students don't have to spend a lot of time learning a variety of packages.

Bell and von Lansenauer (2000) have stressed the importance of using cases to teach operations research. They state "... the aim of case-based teaching is to develop the student's ability to deal effectively with problems arising in new settings within an everchanging environment. The case method, which is based on the concept of learning by doing, is intended to help students discover things for themselves." In many courses, instructors use case studies from various companies for different subjects covered in the course. For an integrated subject such as ERP, I decided to use a series of case studies written from the perspective of one company so as to maintain the integration element, but to further integrate MS/OR modeling into the subject treatment. I did not do this for the sake of teaching MS/OR modeling. I did it because I believe it's the best way to prepare students to make successful use of ERP systems and modeling capabilities in their work. I was fortunate enough a number of years ago to demonstrate the power of such an integration in a real world application that won a Franz Edelman Finalist Award (Flowers, 1993), so I know the power of MS/OR models combined with large scale, integrated systems like ERP.

The course starts in the middle section of the Figure 1 diagram labeled engine with some of the more detailed subjects. I have found over the many years that I have taught this course and its predecessor (production planning and inventory control) that starting with this detail works better than starting at higher levels such as forecasting and production planning. The reason for this is that without the details of what goes on in the engine and backend sections of Figure 1, students do not understand the full significance of the higher level planning and decision modeling activities; they simply can't fill in the blanks. I have tried both orders, and student grades on assignments and tests as well as course evaluations are higher with the order I now use; first the details, then the big picture. The course grading is based on a 50/50 split between team case studies and an individual midterm and final examination. This division is also based on a lot of experimentation over the years. The team case studies allow for students to help each other learn, and lessen the anxiety often associated with a technical course. Most companies use teams for problem-solving activities, and so gaining experience in teams in their degree programs is valuable for students. Teams are kept small enough in size so that each team member must serve as the lead analyst for at least one case study during the course.

3. The Course and the Context As mentioned earlier, the course described in this paper focuses on the operations and supply chain management aspects of ERP systems. The text used for the course is the Vollmann et al. (2005) book. The book is a widely used one for preparing for the APICS certifi-


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Figure 1: Overall Course Concept. The lead analyst is responsible for coordinating the efforts of all team members; not for doing the case by himself/herself. I recommend that students with either a strong ERP background or strong analytical abilities or both serve as team leaders for the early case studies, and that their less confident teammates do it later in the course.

significant prior real world work experience, and are often concentrating in operations and supply chain management. These students will also have had at least a basic course in statistics and one in management science. The MEM students are generally less experienced, often having had only an internship prior to their graduate program, but all of them have either an engineering or computer science undergraduate degree. So even though they may be less experienced, they have more technical background than the students enrolled in the business program. The MEM students enroll in the course under a different title, "Design for Manufacturing and Manufacturing Management II." The II means this is the second course in a two course sequence, and it focuses on manufacturing management as opposed to design for manufacturing and assembly (DFMA). My course is required for students in the MEM program. There are some differences between how the course is taught for the business versus the engineering students, but for purposes of this paper they can be considered the same.

The examinations allow the most accomplished students to demonstrate their depth, and provide an additional control to ensure that more challenged students don't try to just ride the coattails of their teammates on the case studies. After graduation, many of these students will be the ERP expert in their company, so they have to master the subject matter in a comprehensive way. The examinations help to measure that mastery. There are three primary groups of students that this course serves. They include MBA students, MS students, and students in an integrated degree called the Master of Engineering and Management (MEM) Degree. The first two degrees are awarded by the School of Management at my University, and the last is jointly conferred by the School of Management and the School of Engineering. Students in the MBA and MS programs who enroll in the course typically have INFORMS Transactions on Education 7:1(3-17)

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graduate students to grasp the more qualitative aspects on their own, but they are welcome to ask any questions as needed.

4. The Subjects As mentioned above, the subjects proceed from more detailed and operational to more managerial decision making at a higher level. The order in which they are currently taught is: •

Introduction to ERP

•

The BOM explosion and the files

•

BOM structuring/commonality

•

Lot sizing

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Capacity planning

•

Production activity control

•

Shop loading and scheduling

•

Demand management

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Forecasting

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Inventory management

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Master production scheduling

•

Sales and operations planning

•

Production planning

•

Hierarchical production planning

•

Supply chain management

•

Lean manufacturing

•

Just-In-Time systems

•

Distribution requirements planning

•

Integrated manufacturing planning and control systems

In the classes with business students with more experience, there is good interaction since many of them ask a lot of questions relevant to their work. For the MEM students, there is a prerequisite course that involves them making extensive plant tours of a number manufacturing plants in our region, and so I can stimulate discussion by asking them to relate the subject matter of the day to specific companies they have visited. I am familiar with most or all of the companies, and this common background is a nice feature for working with these less experienced students.

5. The Case Studies I have developed the seven case studies listed below for use in the course. The case studies, the course syllabus, and grading notes for all the case studies are available from me free of charge by emailing me at [email protected] 1. Basic bill of material explosion and interpretation 2. Multi-level lot sizing 3. Capacity planning and smoothing using CRP 4. Forecasting and inventory management 5. Production planning 6. Hierarchical (multi-plant) production planning 7. Distribution network design Several years ago in the MEM program, we developed a relationship with the Royal Appliance Company, Inc. that produces and sells vacuum cleaner products. Vacuum cleaners involve aspects from many different engineering disciplines, and so are a good choice for the MEM program. Royal provides physical samples of the products chosen for study each year for the students to disassemble and study in the DFMA portion of the course. They also provide the bill of material and volume of sales information for the product, as well as other information. I take this information and build the case studies for a particular semester around it. I simply name the case studies Monarch Appliance Corporation I through VII, but they cover the subjects listed above. While the case studies are roughly based

Not all of these subjects are covered in the text, so I supplement it with a few additional readings. Wherever possible, these readings are made available as links at the course website from the University's research data bases. There are PowerPoint slides converted to pdf files that are all posted at the site as well. Most students simply download these pdf files and follow along in class using their laptop computers. Because the subject is technical in nature, my role as the instructor is focused on trying to help the students understand the more complex aspects of the subject matter. As a result, we spend more time on the MS/OR modeling than the more qualitative subject matter. The explanations in the readings are adequate for these INFORMS Transactions on Education 7:1(3-17)

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on the Royal Appliance data, I modify it to protect the confidentiality and extend it to subject areas not included in the information that Royal provides.

criteria that they discover. After that, all grades are final. Case I: Basic bill of material (BOM) explosion and interpretation

The cases are data rich, which is needed for the subjects listed above in a graduate course in ERP. They also raise a number of managerial issues that the student teams are expected to address in their reports. The context for the analyses is that each team is a consulting team to Monarch Appliance, and performs their study and then writes a formal client report. The report is evaluated mostly on content, but it must conform to good business report writing as well. This gives the students the opportunity to practice their report writing skills, and to improve them if needed. It can be argued that a great deal of managing in the modern corporate world imitates consulting, due to the collaborative nature of management as opposed to the traditional hierarchical approach. So this consulting orientation should serve students well to help persuade their colleagues in their companies to implement stateof-the-practice.

Even though the BOM explosion is not generally thought of as a MS/OR technique, I am including it here since I think it meets the criterion that we would normally use for such applications. It is intricate and analytical, and it is probably the single most powerful aspect of ERP systems. In this first case study, all the information needed to fill in the BOM file, the inventory status file, the item master file, and the master schedule file are provided to the students. The case extends the original Royal product to three models, an economy, a standard, and a deluxe vacuum cleaner. The combination of the three results in a BOM file with 40-45 items, which is realistic. The data are often pasted into a Word document case statement as Excel spreadsheets in order to facilitate cutting and pasting them into STORM. Nonetheless, the students learn the very exacting and precise information integration necessary to make ERP systems work. In particular, they have to take the bill of material information from the case statement and enter it manually into the bill of material file in STORM. They learn via this process that if even one data element is incorrect, it can create major errors in the solution.

Many students enrolled in this course have had some experience in doing case studies in other courses they are taking or have completed. However, many of those other experiences do not include MS/OR modeling integrated into the managerial considerations for a case. As a result, I provide a two page suggested approach for the case studies to try to help guide the students toward success. That is attached as Appendix A for the interested reader.

When they successfully get the BOM explosion process to work and obtain the associated report, they see a host of organizational problems to address. The problems include overstocking and understocking, undesirable safety stock conditions, scrap issues, and so on. They review and analyze the explosion report and develop recommendations for the company to address them; so they learn to interpret the results of the explosion back to action items to improve company operations.

Student teams submit their reports as Word documents at the course website digital drop box, and my graduate assistant does the first round of grading based on grading information that I provide. My grading information doesn't cover all the creative ideas that students come up with, so after the graduate assistant has done a first thorough review, we meet for a "management by exception" session where I answer any questions that have come up. The graduate assistant then completes the grading and feedback process for the student teams. For feedback, we turn on "track changes" in Word and then type in the feedback in exactly the section of the report where it is most appropriate. This edited version of the submission is then returned via email to all the team members, so each of them has a copy. Since grading is a human process subject to mistakes, the students have one week to request a reconsideration of any misapplication of the grading INFORMS Transactions on Education 7:1(3-17)

Case II: Multi-level lot sizing STORM's MRP module includes seven lot sizing procedures from which to choose for each purchasing or manufacturing planned order. The students use much of the data they created for their first case study in this one; changing only what is new. Since the product structures for the vacuum cleaners go several levels deep, global cost minimization is a multi-level economic lot scheduling problem of significant complexity. 8



Yet it is a problem that practitioners have to solve every day in industry. To add some interest to this case study, I restrict the time I take to solve it and then challenge the students to beat my final total cost. If they do, they are awarded bonus points above and beyond the total allocated for the case. If they don't, they lose points in proportion to how far off they are from my solution. It adds a little fun to the process.

problem (and the only one they need) is the use of firm planned orders. This case makes students painfully aware of the difficulty of dealing with capacity planning with the infinite loading approach still typical in ERP systems. It sets the stage for the discussion of the available-to-promise system that comes later in the course. Case IV: Forecasting and inventory management

I include lot sizing in the course in spite of the popularity of lean manufacturing and its emphasis on single piece flow and economic lot sizes of one unit. In many manufacturing environments with which I am familiar, the technology of the process precludes even considering a lean approach in terms of the ultimate lean goal. I know of furnace changeover processes that require ten to fourteen days to change from one product family to another; try telling that plant manager to schedule a single piece lot size. In the course, I stress economic manufacturing, and that certainly includes lean and JIT concepts. However, there remain many manufacturing environments for which economic lot sizing is important.

It is at this point in the course that we transition from very detailed engine operations in Figure 1 to some of the higher level planning elements. Until this point, the case studies have assumed that the master schedule is loaded with customer orders for the 13 week planning horizon used in the first three cases. The focus to this point has also been on dependent demand inventory management, rather than independent demand. For this case we provide five years of monthly time series data for each of the three finished vacuums. We also provide a set of notes about particular events that took place during this historical period that might have influenced the data. For example, we share when price increases were announced for the products, and when they took effect. Such events often trigger the need for data cleanup in an operational forecasting data base in industry, so our students get such a simulated experience in this case. They are instructed to first apply the forecasting methodologies to the data base without doing any cleanup to see what, if any, improvements are achieved as compared to the company's current six-month moving average system. They are then asked to perform a careful data clean up and rerun the forecasting analyses to see how the conclusions change.

Case III: Capacity planning and smoothing using CRP In this case three capacity resources are introduced: labor, small part injection molding, and large part injection molding. The parts and assemblies may require none of these resources (purchased items), one, two, or all three of them. Once again, the students modify their data base from earlier case studies to accommodate the new information about capacities in this one, including a new capacity resource file. Since this case is probably the most challenging one of the semester to solve, we simplify it somewhat by using all lot-forlot lot sizing. This allows the focus to be on capacity smoothing.

A second part of this case is a simple safety stock analysis using statistical safety stock concepts. The company is using a familiar time-supply rule (namely, 50% of the forecast for the next three months). The students have to go back to the product structures from the earlier cases to determine the cumulative manufacturing lead times for each of the three products in order to know how to adjust the safety stock computations for the lead times. They can then compare the statistically determined values to what the company is currently doing and make recommendations as appropriate.

When the students complete the data updates and get the explosion report, it now includes a capacity load report that shows uneven utilization of the three capacity resources. Some periods show underutilization, and others overutilization. It is important that students very carefully design their improvement strategies to smooth the utilization, since there are both multi-level effects and multiple resource effects within the same part or assembly. A trial-and-error approach would take much more time than they have available to solve the problem. The only tool they have to attack the INFORMS Transactions on Education 7:1(3-17)

Case V: Production planning

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This is an aggregate planning case that involves setting work force, inventory levels, and capacity utilization for a plant over the course of a year of seasonal demand. The students learned from the forecasting case study that vacuum cleaners do exhibit a seasonal sales pattern. They are provided with all the relevant costs and plant operating policies in terms of overtime usage, part-time hiring, and so on. The problem can be formulated and solved as a mixed integer-linear program. The case statement provides three solutions that represent a level production rate plan, a chase strategy with constant work force and varying overtime, and a chase strategy with varying work force. An example of this case study and its grading notes are included in Appendix B.

the modifications mentioned above can only accommodate a limited production volume in the new territories. Using a three year planning horizon, the students are asked to evaluate whether modification or new construction makes sense, and if so to propose a specific plan. This problem can be formulated and solved as a mixed zero-one linear programming problem. The instructor can change the cost parameters so that the conclusion reached and the optimal plan vary from year to year. In fact, I change the data to some degree every year for all the cases to make sure each year's group of students gain the full learning experience. For this case study, we have a two-stage submission process. First, each team submits their initial mathematical formulation for the problem. Immediately after the deadline for these submissions, we email the correct formulation to all members of the class so they can proceed to work on the analysis portion of the case. Both the first formulation submission and the final analysis portions of the case are graded. These are weighted 20% for the formulation and 80% for the additional analysis.

For a few hours of work to formulate and solve the mathematical program, the students learn that they can save the company thousands of dollars versus the best schedule of the three that the company was considering. However, they also learn that the inventories that result from this schedule are much too large at times to be practical. In addition, work force sizes in the optimal solution vary so much that morale would be a problem if the company attempted to implement the solution. So they are expected to notice these aspects and deal with them. The simplest way to deal with them is to add additional constraints that limit these factors in some intelligent way. STORM makes it particularly easy to do this, since it automatically inserts two rows that allow an upper and a lower bound value to be specified for each variable. So if a student team wants to force some minimal ending inventory to serve as a safety stock, but limit the maximum value to fit in the storage space available, they can use these rows and don't have to add in two additional constraints per inventory variable. This case illustrates how easy it is with MS/OR models to accomplish good managerial practices and to evaluate the cost tradeoffs associated with them.

Case VII: Distribution network design The final case study goes outside the manufacturing realm and into distribution systems planning and design. It presents a scenario where a central depot serves a set of warehouses, that in turn serve a set of retail customers. Fixed and variable costs of the current operations are provided. The student teams are challenged to come up with any revisions to the network to reduce the costs of the entire operation, including fixed plus variable costs. For this project, the students are limited in the scope of alternatives that they can consider to closing some of the warehouses (ensuring that enough capacity remains to meet all the retail demand) and to optimizing the use of the different network designs that they evaluate. This problem can be formulated and solved as a mixed zero-one linear programming problem, but it would be too large scale for the scope of this course. Instead, students solve this problem via repeated use of the transportation method of linear programming for the optimization of a network and then add back the fixed costs based on which warehouses are open. The cell costs for the transportation problems must use the landed cost (total variable cost required to get the product to its final destination) in order to properly optimize the network.

Case VI: Hierarchical (multi-plant) production planning In this case study, Monarch Appliance Corporation has been purchased by a parent company. The parent company has plant operations in territories closer to customer demand than the current Monarch facility, but the parent facilities would have to be modified at a substantial cost in order to produce the Monarch products. New construction is also a possibility, since INFORMS Transactions on Education 7:1(3-17)

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bilities, multi-level lot sizing, and capacity requirements planning), exponential smoothing forecasting (including the four basic forecasting models, model validation, smoothing constant optimization), linear and integer programming, and the transportation module. There are 15 other modules in the package that I don't use in this course. It would be incomprehensible to expect the students enrolled in the course I have described to program the four modules that they use into a spreadsheet, and it would not be a good use of their time in any event.

6. The Benefits The benefits can be considered from both the student's point of view and the instructor's, although clearly it is the student view that is most important. I believe that one of the greatest benefits for the student is to have an integrated view of several different aspects of ERP systems. The reality is that most students will go to work for one company, and they rarely see the integration within one company that needs to occur in their graduate coursework. As faculty, we talk about the need for such integration, but we don't always deliver it in our courses.

A final benefit that I see for students coming out of a course like this is that they are sensitized to the potential benefits of integrating MS/OR models into their decision making processes. The decision support world that awaits us due to the data and information available from ERP type systems presents a unique opportunity for the companies that have the skilled professionals to exploit it.

A second benefit is that students gain experience going from the verbal descriptions of problems and the associated data to an MS/OR model and analysis with it. This helps them perceive organizational problems that have structures that are amenable to MS/OR models; a skill that they can carry over to their job experience. This experience also builds the confidence that they can do it. If they don't have the confidence that they can do it, they won't try once they're in industry.

One fair criticism of the approach that I take is that students don't come out of the course knowing how to use one of the big ERP packages such as SAP or Oracle. I have performed consulting projects wherein I have helped companies implement those type of packages. I consider the overhead costs of learning them as being simply too high for a graduate course in ERP. I could not include many of the subjects that I do if I also had to spend a lot of time in software training covering all the many screens that these complex systems possess. I believe that a student is far better off understanding the functions that the systems perform rather than how to run any one system. If one software vendor enjoyed a near monopoly position and was expected to maintain it, it would create a much stronger case for teaching a specific large-scale ERP package. That is not the case today, nor is it expected to be anytime soon

A third benefit is that the problem sizes that can be used are realistic. This is due directly to the use of some MS/OR modeling software. Early in my career, we were forced to assign problems that could be solved with hand held calculators. Students often took a dim view of our profession, since they could guess the right answer by inspection, and they resented the laborious calculator computations as well. They reasoned that MS/OR couldn't be worth much; since it was easier and faster to guess than to apply the methods. With the kind of case studies described above and the amount of data each contains, the initial feeling on the part of the students is often one of being overwhelmed. We coach and nurture them through that, and when they realize that creating the problem formulation in the software is really pretty easy, and allows them to perform many managerial "what if" analyses, they really begin to see how this can differentiate them in the marketplace.

From the point of view of the instructor, I believe one great benefit is the simple knowledge that you have helped prepare your students well for the corporate world they will face. I receive a good bit of anecdotal feedback from former students who have taken this course. A number of them have told me that their knowledge from this course was very instrumental in their interview process to get their first professional position. I have one former student who is with HP that emails me at least once a year to explain how significant his experience in this course was to the

A professor could try to achieve similar results by building all the case studies listed above into spreadsheet models. However, spreadsheets often do not contain all the sophisticated algorithms that have been pre-programmed as MS/OR software does. In the ERP course, I use the material requirements planning module (including its bill of material explosion capaINFORMS Transactions on Education 7:1(3-17)

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considerable success he has enjoyed in his career at HP. I have another former student who is a Lead Consultant at Oracle that flatly states this course was the best he ever had. He tells current students that when he comes back to visit our campus and talk to them. Since a number of students in the MBA and MS program are part time evening students, I routinely hear from them during the semester in which they are completing the course how much it is helping them in their current work environment. Many former students have told me that after completing this course, they passed several APICS certification exams based primarily on this course. Some even teach modules for our local APICS chapter to help others prepare for the exams.

Anonymous (2004) "Survey: Gap between SC tech, business strategy," The Journal of Commerce Online, pp. 1-2. Bell, PC, and C Hachling von Lanzenauer (2000) "Teaching Objectives: The Value of Using Cases in Teaching Operational Research," Journal of the Operational Research Society, Vol. 51, No. 12, pp. 1367-1377. Draijer, C. and D. Schenk (2004) "Best Practices of Business Simulation with SAP R/3," Journal of Information Systems Education, Vol. 15, No. 3, pp. 261-265. Emmons, H., A.D. Flowers, C.M. Khot, and K. Mathur, (2001) STORM 4.0 for Windows: Quantitative Modeling for Decision Support Mini-Manual, Lakeshore Communications, 93 pages.

The course evaluations for this course are also very solid. My School uses a 5 point scale with 5 being the best rating on the student evaluation form. Research has shown that the overall course rating and the overall instructor rating tend to be the dominant factors from these types of evaluations. My most recent scores for this course involved two sections of the class, with the course ratings being 4.5 and 4.7, and the instructor ratings being 4.7 and 4.8 respectively. The ratings are not always this good, but they are consistently in the low to high 4's. Since sometimes high ratings just mean popularity, I would also add that the average workload ratings for this course were 4.4 and 4.5, where 3.0 was an average workload for a course, and anything above that meant a heavier workload. If students are working hard and still rating a course highly, it certainly could mean that they think they are learning something of value, so the effort is worth it.

Flowers, A.D. (1993) "The Modernization of Merit Brass," Interfaces, Special Issue for Edelman Award Papers, Vol. 23, No. 1, pp. 97-108. Peslak, A.R., (2005) "A Twelve-Step, Multiple Course Approach to Teaching Enterprise Resource Planning," Journal of Information Systems Education, Vol. 16, No. 2, pp. 147-155. Strong, D.M., S.A. Johnson, and J.J. Mistry, (2004) "Integrating Enterprise Decision-Making Modules into Undergraduate Management and Industrial Engineering Curricula," Journal of Information Systems Education, Vol. 15, No. 3, pp. 301313. Vollmann, T.E., W.L. Berry, D.C Whybark, and F.R. Jacobs, (2005) Manufacturing Planning and Control for Supply Chain Management, Fifth Edition, McGraw-Hill Irwin.

7. Acknowledgments

Watson, E. and H. Schneider, (1999) "Using ERP Systems in Education," Communications of the Association for Information Systems, Vol. 1, No. 9, pp. 1-47.

I would like to thank the anonymous referees and the Guest Editor for their suggestions that improved the final paper.

References Albritton, M.D., P.R. McMullen, and L.R. Gardiner, (2003) "OR/MS Content and Visibility in AACSB-Accredited US Business Programs," Interfaces, Vol. 33, No. 5, pp. 83-89. Anonymous (2003) "ERP Expenditures," The Controller's Report," p. 9. INFORMS Transactions on Education 7:1(3-17)

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Appendix Appendix A - Suggestions For Doing Cases The following are some thoughts that I hope students will find useful to guide their preparation of cases. They are based on experience with students in the past, especially with common mistakes students have made which resulted in frustration. The objective of sharing these thoughts is to try to get you started off on the right foot in this course, and then keep you there!

Careful Design, then Implement The most common mistake students make in analyzing cases with the assistance of computer software is to assume the software will do all the work. It won't. You must very carefully construct a design of experiments you want to do with the software to address the issues in the case; then and only then should you plunge into data analysis.

Data Analysis in Stages When you begin your data analysis with a careful design in mind, make the preliminary runs and then stop and analyze the results. See what they tell you and decide if the rest of your design is still appropriate, or if it should be modified. In this way, you will know exactly what you are doing at each stage, and where you are on your design road map.

Start with Company Statement of the Problem In this course (and in life), you should start with the problem as laid out by the company (your boss). Do not leave it until you have "nailed it," that is, until you feel that you have exhausted all realistic approaches to solving that exact problem. Some students want to solve some other problem first, and never bother to address the problem as stated in the case.

Relax Assumptions to try Other Scenarios: Leverage Points After exhausting the problem as stated by the company, change the problem to explore relationships between different parts of it. Try some things to facilitate your learning the subject, even if you think they would be impossible to achieve in reality. Find out where the leverage points are; that is, what changes to the problem scenario would yield the greatest benefits to the organization. Ask yourself, how would I try to make these changes in reality? To what degree could I reasonably expect to succeed? Scenarios that involve quadrupling sales in one year for a $2 billion company will be graded with the humor they deserve. Some improvement on leverage points may be realistically possible, however. State specific approaches you would take to try to make these improvements happen (automate, work with vendors, etc.).

Know your Software, and let it help your Design You should know the case thoroughly before you attempt to design your analysis, as well as the software you are going to use. The input data required by the software (any software, by the way) gives you ideas about what scenarios can be easily analyzed. Examine each input data item to decide what, if any, changes you might make to it to evaluate alternative scenarios. As mentioned above, use the software to satisfy your curiosity and simply to learn about relationships between problem variables as well. Some runs you make may not contribute greatly to your solution of the case, but may help you understand some of the material in the course better, and may apply to other cases you will solve later in life at your own organization. INFORMS Transactions on Education 7:1(3-17)

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Do a thorough Managerial Analysis, too While we admit that this course is fairly technical and that a thorough technical analysis is expected on every case, we also want to encourage strong managerial analysis. Sometimes all our technical analysis pales in comparison to taking one strategic action to relieve a critical constraint. Your managerial analysis may draw on concepts we have used in this course, concepts you have learned elsewhere in your academic experience, and concepts you have learned from your work experience. Managerial suggestions should be action oriented; they should not simply restate information provided in the case.

Leave Time for the Write-up Plan on finishing all your analysis and deciding what you want to say in your report a couple of days or more before it is due. Then spend some time discovering what you feel is the best way to communicate your results. Tables and charts are particularly effective at summarizing a lot of analysis in a simple, but powerful way. Construct these first and they will make your writing task much easier. Start your report with your conclusions and recommendations. Follow this with your analysis and discussion, including technical and managerial analysis sections. Conclude with any appendices such as detailed computer outputs, etc. Be as concise as possible in your report, consistent with clearly communicating your work. For example, if you have a series of things you think the company in the case should consider that are fairly self explanatory, put them in a simple bullet list. Don't drag on for many paragraphs about them when a simple bullet list will do. On the other hand, if you suggest a radical departure from the way the company is doing business, and it is not immediately clear how it would be implemented, provide enough explanation to convince the reader that your approach can be done.

Appendix B - An Example Case The case study below assumes that the student has completed the cases that precede it that introduce a lot of information about the company and the products for which the analysis is being done. Some of the "players" in the case are other faculty from my School that teach subjects that integrate with the case. I provide my graduate student assistant with a set of gradingnotes(1) in presentation format that I use to provide feedback to the students about their performance on the case. The feedback allows them to double check our grading and make sure it was done accurately. We fill in the numbers in the first slide with the summary performance for all the teams in the class. The "Knee Cap" award is for the team with the highest score on the case; it is named in jest since the other teams might bang the knee caps of the award winners. The graduate student uses the notes to make a first pass attempt at grading the cases and then meets with me to discuss specific aspects of any cases as necessary. MONARCH APPLIANCE CORPORATION V © A. Dale Flowers, 2006, All rights reserved. This case is a fictional case, although some of the data in it are real. Your consulting organization has successfully created a partnership with Monarch Appliance. The work that you have completed for them in the past has resulted in them viewing you as a strategic partner as they move forward. This means more work for your firm, and that translates into billable hours of consulting fees.

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For your next assignment, you have been asked to turn your attention to the production planning problem at the Monarch assembly plant in Mexico. The seasonal nature of the sales of the vacuum cleaners has created havoc in the production planning for the plant. In the past, Dale Flowers has pretty much just gone month-tomonth in deciding the staffing plan. Depending on the availability of workers in the area, sometimes he hires and lays off workers as he needs to in order to adjust to the demands of Monarch's customers. At other times, particularly when Stan Cort is complaining about low inventories, he has kept the work force at a more constant size, at least for a few months, and allowed inventories to accumulate. The new V.P. of Operations, Marc Vitantonio, has directed Flowers to start preparing a production plan for a year at a time, since Vitantonio believes that Monarch could save some money if they developed and implemented a better plan. Flowers knows that Vitantonio is probably right, and decides to see if he can produce a minimum cost plan. He figures that if he can impress Vitantonio, he can use that achievement to restore some of the reputation he has lost because of his poor inventory management performance and the resulting poor customer service. Those things are going much better now, due to the implementation of the ERP system that you recommended in your earlier work. Flowers has put together a lot of information and has begun to perform some analysis for his production plan. There is quite a lot to learn about how this plant is run in order to determine a plan that is consistent with that. The plant works an average of 4 weeks per month during each month of the year since there are scheduled shut downs for holidays and maintenance of the facility. Every assembler in the plant is guaranteed a 40 hour work week. If not all the production is needed to meet demand, the excess is simply carried over to the next month as finished goods inventory. This policy has helped Monarch recruit and keep good workers, since the employees get full fringe benefits this way. Part-time employees would not receive any benefits, so Monarch would have a hard time getting good employees to work part time. The plant is in a rural area in Mexico , so it does not have a physician on site to perform physical examinations when new employees are hired. Since it is against company policy to hire a worker without first giving the worker a physical, Monarch has contracted with a physician from the closest city to the plant to come out once a month and perform physical exams for new applicants the company wants to hire. This means that Monarch only hires people to begin a new month. Since occasionally the company has to lay people off, it uses this same policy and only lays people off at the end of the month. This way, a new hire knows that he or she will get at least one month of employment at 40 hours per week pay. This helps to reduce the disappointment for employees that are hired and then laid off fairly soon after they are hired. Flowers has determined that with the current mix of the three vacuum cleaners assembled at this plant, each additional assembler hired adds one vacuum per hour to the capacity of the plant. With the 40 hour work week and 4 weeks per month of operations, this means each employee contributes 160 units of production per month. The company pays an average of $5 per hour, and fringe benefits cost 10% of the base wage rate, so an employee costs $880 per month for regular time production. Overtime production is sometimes used to meet demand rather than hire workers only to have to lay them off very soon thereafter. Overtime rates are 1.5 times regular time rates, and overtime production is assumed to be just as efficient as regular time production, since the employees are motivated to earn this extra pay. So a month equivalent of overtime production would produce 160 units, and cost $1280. Due to the new importance placed on customer service, no production plan is acceptable except one that is expected to meet the demand forecast (the one you prepared in Monarch II). Flowers has taken the forecasts for the current calendar year that resulted from your earlier analysis and added them together to produce the following aggregate forecast for sales of all three vacuum cleaners.


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Because of the low prevailing interest rates and the modest cost of the rural facilities where the finished vacuums are stored, Monarch uses a 15% carrying charge rate per year for carrying inventory. Flowers computed a weighted average value of the product mix and learned that the average unit of inventory costs about $47.87. This means that the inventory carrying cost per unit per month is $0.60. The current total inventory of these three vacuums to start the calendar year is 2994.

The HR manager for Monarch, Mr. Paul Gerhart, has provided Flowers with some additional important information. Gerhart has determined that it costs Monarch $600 in total to hire one new employee and get them up to standard production speed. Due to the amount of paperwork that has to be done to lay off an employee, the layoff cost is a substantial $400 per employee. Gerhart is trying to maintain good relationships with the communities from which the workers are drawn, and so he has asked Flowers not to make frequent large changes in the work force size, since such hiring and layoff practices cause ill will in the community. There are currently 110 full time assemblers on the payroll to begin the planning period. As Flowers began to work on this problem, he considered various strategies he could try to implement. Due to Gerhart's request for a stable work force, this is the first strategy that Flowers tried. He produced the information shown in Exhibit1(2) as a part of this effort. To see how other strategies might perform, he computed two additional exhibits. Exhibit2(3) uses an overtime chase strategy; the work force is kept constant but overtime is used to absorb the fluctuations in demand from month to month. Exhibit3(4) contains the results of a chase strategy that involves changing the workforce size rather than chasing with overtime as in Exhibit2. Flowers sees that Exhibit3 has the lowest cost solution, and so would probably be best received by Vitantonio. However, Gerhart may oppose it because of the changes to the work force size that it employs. Flowers also wonders if there is an even lower cost solution that he hasn't found with his approach. Case Requirements Using the information above, compute the lowest cost production plan that you can that observes the company practices as explained above. Include this solution and a managerial critique of it in your final report. In addition, provide a solution that you recommend Monarch actually implement. It may be the same as your lowest cost solution, or one of Flowers' solutions in the Exhibits, or it may be another solution that you come

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up with that is different from any of these. You should explain clearly why you think your recommended solution should be the one that is implemented in the real world. Prepare your consulting report as a Word document (double-spaced, 12 point type, 1 inch margins all around, your report should probably be no longer than 8-10 pages, or less, excluding exhibits). In addition, submit any additional files that you create and use to solve this case.


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