Question

Use a personal example or a text example or a business problem from the real world to illustrate one or more of the Decision Analysis models covered.

Why was the particular model chosen? Which model(s) might provide a better decision for this problem?

Assign probabilities to the problem (if not already assigned) and determine the Expected Value solution.

Answer 1

In this section some examples of successful real-world applications of operations research are provided. These should give the reader an appreciation for the diverse kinds of problems that O.R. can address, as well as for the magnitude of the savings that are possible. Without any doubt, the best source for case studies and details of successful applications is the journal Interfaces, which is a publication of the Institute for Operations Research and the Management Sciences (INFORMS). This journal is oriented toward the practitioner and much of the exposition is in laypersons' terms; at some point, every practicing industrial engineer should refer to this journal to appreciate the contributions that O.R. can make. All of the applications that follow have been extracted from recent issues of Interfaces.

Before describing these applications, a few words are in order about the standing of operations research in the real world. An unfortunate reality is that O.R. has received more than its fair share of negative publicity. It has sometimes been looked upon as an esoteric science with little relevance to the real-world, and some critics have even referred to it as a collection of techniques in search of a problem to solve! Clearly, this criticism is untrue and there is plenty of documented evidence that when applied properly and with a problem-driven focus, O.R. can result in benefits that can be quite spectacular; the examples that follow in this section clearly attest to this fact.

On the other hand, there is also evidence to suggest that (unfortunately) the criticisms leveled against O.R. are not completely unfounded. This is because O.R. is often not applied as it should be - people have often taken the myopic view that O.R. is a specific method as opposed to a complete and systematic process. In particular, there has been an inordinate amount of emphasis on the modeling and solution steps, possibly because these clearly offer the most intellectual challenge. However, it is critical to maintain a problem-driven focus - the ultimate aim of an O.R. study is to implement a solution to the problem being analyzed. Building complex models that are ultimately intractable, or developing highly efficient solution procedures to models that have little relevance to the real world may be fine as intellectual exercises, but run contrary to the practical nature of operations research! Unfortunately, this fact has sometimes been forgotten. Another valid criticism is the fact that many analysts are notoriously poor at communicating the results of an O.R. project in terms that can be understood and appreciated by practitioners who may not necessarily have a great deal of mathematical sophistication or formal training in O.R. The bottom line is that an O.R. project can be successful only if sufficient attention is paid to each of the seven steps of the process and the results are communicated to the end-users in an understandable form.

Some examples of successful O.R. projects are now presented.

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Production Planning at Harris Corporation - Semiconductor Section: For our first application [1], we look at an area that is readily appreciated by every industrial engineer - production planning and due date quotation. The semiconductor section of Harris Corporation was for a number of years a fairly small business catering to a niche market in the aerospace and defense industries where the competition was minimal. However, in 1988 a strategic decision was made to acquire General Electric's semiconductor product lines and manufacturing facilities. This immediately increased the size of Harris Semiconductor's operations and product lines by roughly three times, and more importantly, catapulted Harris into commercial market areas such as automobiles and telecommunications where the competition was stiff. Given the new diversity of product lines and the tremendous increase in the complexity of production planning, Harris was having a hard time meeting delivery schedules and in staying competitive from a financial perspective; clearly, a better system was required.

In the orientation phase it was determined that the MRP type systems used by a number of its competitors would not be a satisfactory answer and a decision was made to develop a planning system that would meet Harris' unique needs - the final result was IMPReSS, an automated production planning and delivery quotation system for the entire production network. The system is an impressive combination of heuristics as well as optimization-based techniques. It works by breaking up the overall problem into smaller, more manageable problems by using a heuristic decomposition approach. Mathematical models within the problem are solved using linear programming along with concepts from material requirements planning. The entire system interfaces with sophisticated databases allowing for forecasting, quotation and order entry, materials and dynamic information on capacities. Harris estimates that this system has increased on-time deliveries from 75% to 95% with no increase in inventories, helped it move from $75 million in losses to $40 million in profits annually, and allowed it to plan its capital investments more efficiently.