Department of Management Science The Management School Lancaster University Lancaster LA1 4YX United Kingdom
Skill in modeling is one of the keys to success in OR/MS practice. This has been recognized for many years, but we often give it only lip service. Models are used in many ways in OR/MS practice. A few simple principles ofmodeling may be useful. The six principles discussed here cover simplicity versus complexity; model development as a gradual, almost piecemeal process; dividing larger models into smaller components; using analogies; proper uses of data; and ﬁnally the way in which the modeling process can seem chaotic. Others may wish to comment on these principles and add their own.
hen I am fortunate enough tovisit a new country, I usually try to buy one of the Rough Guides, since the prejudices of the writers seem fairly close to my own. The guides point out the good (and bad) in the place to be visited, and they attempt the impossible by trying to give a ﬂavor of the country in a few pages. I have been active in OR/MS both as an academic and as a practitioner since the early 1970s. In my experience,the real technical heart of OR/MS can be summaCopyright 1999, Institute for Operations Research and the Management Sciences 0092-2102/99/2902/0118/$5.00 This paper was refereed.
rized in the one word, modeling. In this paper, I will attempt to provide a rough guide to modeling, with principles that I and others have found useful and that seem to resonate with students and practitioners.Others have written at length on the useful principles of modeling. Morris  outlined some hypotheses about modeling that he had found useful and that illustrate the difference between modeling as an intuitive process and the forPROFESSIONAL—OR/MS EDUCATION PHILOSOPHY OF MODELING
INTERFACES 29: 2 March–April 1999 (pp. 118–132)
A ROUGH GUIDE
mal study of existing models. Little discussed how the then emerging technology of interactive computing could be employed to develop models that managers would be likely to use. Hugh Miser and Ed Quade had much to say on the subject in their magnum opus on craft issues in systems analysis [Miser and Quade 1988]. Hodges  argued that even bad models may be used in satisfactory ways, even if those models fall short of theircreator’s original intentions. Pat Rivett has written much on the subject of modeling, and Rivett  provided a number of examples to illustrate a general approach to model building. Powell  discussed how modeling skills may be taught to MBA students and suggested six key modeling heuristics for this purpose. I intend to complement the issues that these and others have raised. I also hope that Imay stimulate other people to consider their own key aspects of modeling in OR. In discussing these principles, I will rely on my own background in discrete simulation. However, I believe the principles I discuss are relevant for most forms of mathematical and computer modeling in OR/MS. Some of the material in this paper is based on chapter 4 of my book [Pidd 1996]. Models and Modeling I willfocus on modeling as a verb or as an activity and not models as nouns or subjects. Morris  wrote that “the teaching of modeling is not the same as the teaching of models.” By models he meant approaches and methodologies, such as those of linear programming or queuing theory, that present ready-made models by which situations may be analyzed. In contrast to teaching such readymade models, I,like Morris, am concerned with the processes of discovery and elaboration that are essential parts of modeling and of model development. I am interested in the ways people build and use models, rather than in the details of individual, ready-made models. Modeling activity is at the technical heart of OR/MS practice. Models in OR/MS have two main uses: (1) People use models to explore the possible...