Art Geoffrion
UCLA Anderson School of Management

One of the persistent challenges of OR/MS is explaining itself to people outside the field. There is often a great lack of understanding about OR/MS on the part of students, colleagues in neighboring fields, university administrators, prospective university donors, the business community, and the public at large.

This challenge can be addressed by developing crisp messages that can be used to frame discussions with outsiders.  By delivering these messages consistently over a long period of time, people may come to better appreciate what OR/MS has to offer.

Operations Research/Management Science is in many businesses. Among others, OR/MS is in the business of ...

  1. ... rationalizing decision-making, design, and other managerial activities with the help of analytic thinking based on the classical scientific method, models, and computers.
  2. [Other fields also attempt rationalization, but they take a different approach.]
  3. ... supporting all the functional specialties of business and other types of organizations. This includes, but is not limited to: bidding, design, finance, forecasting, human resources, information systems, logistics, marketing, manufacturing, and service operations. Contrary to some rumors, the service sector is just as amenable to OR/MS as the more traditional manufacturing sector.
  4. [Computers, mathematics, and the scientific approach are universally applicable.]
  5. ... helping managers to achieve a deeper understanding of their organization through the analysis and modeling of selected aspects of the organization and its environment.
  6. [Understanding enables control.]
  7. ... helping organizations to exploit the revolutionary developments in computers, communications, and related information technologies.
  8. [OR/MS's synergy with these technologies works both ways.]
  9. ... adding value to data. Through modeling and analytic thinking, OR/MS helps managers to make strategic, tactical, and operational sense out of the vast and rapidly increasing data resources available to most organizations; this includes coupling or embedding decision technologies into existing and new information systems.
  10. ["Adding value" is an enduring business priority. With their analytic skills, OR/MS professionals are able to add value beyond what typically can be added by IS groups and information technologists.]
  11. ... helping managers to deal with rapidly increasing organizational complexity.  OR/MS does this by solving organizational problems, enabling better planning, improving the efficiency of operations, etc.
  12. [Some managers erroneously believe that the rising complexity of managerial tasks tends to defeat the applicability of OR/MS.]
  13. ... embedding decision technology into important business processes, systems, and recurring tasks. The result is new functionality and improved performance.
  14. [This is the antithesis of the one-shot OR/MS project. Embedded applications can accumulate great impact over an extended period of time.]
  15. ... helping to improve productivity and competitiveness, in the context of economic globalization and the transition to a service and information-based economy.

  17. ... helping with the quest for quality in an organization's products and services, through process redesign and through quantitative measurement and models that lead to a deeper understanding and greater control.

  18. ... achieving the objectives of expert systems whether or not an expert is available, and in ways that (a) will not rapidly become obsolete (as will the static wisdom of yesterday's expert in the face of tomorrow's problems), and (b) do not overlook opportunities to achieve super-human performance.
  19. [OR/MS has some of the goods that ES and KBS promise, and is not limited to heuristics when superior methods exist.]
  20. ... finding the best way to cope with constraints, wherever they come from -- limited resources, government regulation, competition, the environment, or elsewhere.  OR/MS also can shed value on the marginal value of relaxing constraints.

  22. ... coping with uncertainty and doubt.  This includes ways tobalance risk against likely gain.

  24. ... experimenting with computerized replicas (often analytical or simulation models) of situations and systems, which can be a more revealing, quicker, cheaper, and safer first step than experimenting on the real world.

  26. ... handling trade-offs.
I used some of these points (p. 25ff) in "Prospects for Operations Research in the E-Business Era," with R. Krishnan, Interfaces, Vol. 31, No. 2 (March-April, 2001), 6-36.

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