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What is Operations Research?

Short Descriptions of OR · Typical Areas of Study within OR · Typical Application Areas of OR · A Career in OR

The name Operations Research (or Operational Research, as it is known in Europe and the United Kingdom) does not really describe the nature of the discipline. Neither do the synomyms Operational Analysis, Quantitative Management, Management Science or Decision Science, which are often used instead of the widely accepted term Operations Research. The name Operations Research stems from the collective war effort in the United Kingdom during World War II when a team of scientists were called upon "to study the strategic and tactical problems associated with air and land defense of the country" [2]. This team of scientists focussed on decisions regarding the effective utilisation of limited military resources, with applications including the use of the then newly invented technology of radar and the effectiveness of new types of bombing strategies. The term Operations Research was coined because the team did research on rendering (military) operations as effective as possible. Encouraged by the successes of the British team of scientists, various research teams in the United States followed suit, studying complex military logistical problems, the effectiveness of aircraft flight patterns, the planning of sea mining activities and the effective utilisation of electronic equipment of warfare.

After the war, the degree of success of the various military research teams attracted the attention of industrial engineers who were keen to apply similar optimisation and streamlining techniques to problems in business and industry [3]. The modern scope of Operations Research is indeed much wider than military operations. Today the discipline is still concerned with effective system utilisation and decision making, but now in business and industry, as well as in government and society at large. The decisions may be about large-scale undertakings, such as the building of a new mine, or about small ones, such as the re-routing of a local bus service. They may be concerned with long-term plans for the redevelopment of an entire inner-city area, or with the immediate problems of selecting a port to handle exports of cars, or how to balance predator-and-prey populations in the management of a game reserve.

The golden thread of commonality amongst the seemingly divergent examples of Operations Research application possibilities mentioned above is that the discipline seeks to employ the scientific method to improve the way in which decisions are made, usually with a view to optimise or steamline the effective use of limited resources (such as time, labour or money). The approach of an operations researcher during this optimisation process typically entails the following elements:

  • finding out what the problem at an application site really is,
  • assisting the role players at the application site to work out the objectives of the study,
  • observing the functioning and effectiveness of the application site,
  • collecting the relevant data at the application site,
  • determining the main factors influencing the problem at the application site,
  • proposing and testing various ways of solving the problem until one of them can be accepted as the best practical proposition (this often involves the use of a mathematical model), and finally
  • helping the role players at the application site to make the proposed solution work in practice.

Operations Research is not based on any single academic discipline. It draws from the physical sciences, logic, applied mathematics, industrial engineering, the social sciences, economics, statistics and computing, to name but a few, but is none of these on their own. It is typically concerned with decision problems which cut across several disciplines and attempts to tackle problems on their merits using appropriate tools from any of these sources.

Being about change, Operations Research is not just a "hard" (i.e. quantitative) subject; it also has to be concerned with people and how they react to change. Therefore, in addition to possessing good analytical skills, an operations researcher should also be prepared to search out and try to understand people’s attitudes, preferences and fears regarding change and improvement. In fact, today it is widely recognised that techniques and approaches within the discipline of Operations Research may be classified as encompassing both "hard" Operations Research and "soft" Operations Research.

Soft Operations Research, Problem Structuring Methods (PSM) or Soft Systems Methodology (SSM) is the result of research done by Peter Checkland and others [4]. It is a systemic approach for tackling problematic situations. It provides a framework for handling the kind of ill-defined or not easily quantified problems (in other words messy problems that lack a formal problem definition). In terms of systems thinking, traditional systems is not very appropriate for dealing with problems which cannot be defined clearly and that do not have a commonly agreed upon set of outcomes. Problem Structuring Methods attempt to understand complexity, promote learning, to identify weaknesses and to understand relationships.

In "hard" systems approaches, rigid techniques and procedures are used to provide unambiguous solutions to well-defined problems for which an abundance of clean data are available. Hard systems approaches assume that problems are well defined, the scientific approach to problem solving will work and that technical factors will dominate.

Characteristics of Problem Structuring Methods [4]:

  • Non-optimising; seeks alternative solutions that are acceptable on separate dimensions, without trade-offs,
  • Reduced data demands, achieved by greater integration of hard and soft data with social judgements,
  • Simplicity and transparency, aimed at clarifying the terms of conflict,
  • Conceptualises people as active subjects,
  • Facilitates planning from the bottom up,
  • Accepts uncertainty, and aims to keep options open for later resolution, and
  • Assist in giving appropriate elements of structure to a wide range of problem situations.

Problem structuring methods and “hard” OR are not in conflict. They are typically used in different stages of a problem solving process. Problem structuring methods are applied during the early stages where a problem is not well defined. "Hard" OR is applied during the later stages when problems are well-defined.

The description above of what Operations Research is, suffers from the serious drawback that, as a result of an attempt at giving a balanced and representative account of what the subject field entails, it is rather long-winded. This is typical of descriptions of what Operations Research is. Therefore, a number of shorter definitions of the discipline and what it entails are also available via the links at the top of this page, as are lists of typical specialisation areas within Operations Research and modern application areas of Operations Research. Finally, the Institute for Operations Research and Management Science (or INFORMS as the American Operations Research Society is known) has made a rather successful attempt at avoiding long-winded descriptions of what Operations Research is by introducing their catchy slogan that Operations Research is the Science of Better [1].


  1. INFORMS, 2011. Operations Research: The Science of Better, Available Online.
  2. Taha TA, 1971. Operations Research: An Introduction, Macmillan Company, New York (NY).
  3. Winston WL, 1994, Operations Research: Applications and Algorithms, Duxbury Press, Belmont (CA).
  4. Ittmann HW, 2009, Recent developments in operations research: A personal perspective, ORiON, 25(2), pp. 87-105.
Page last modified on June 18, 2014, at 11:21 AM