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- Employers generally prefer applicants with at least a master?s degree in operations research or management science, or a closely related field such as computer science, engineering, business, mathematics, or information systems.
- Employment growth is projected to be slower than average, reflecting slow growth in the number of jobs with the title ?operations research analyst.?
- Individuals with a master?s or Ph.D. degree in management science, operations research, or equivalent should have good job opportunities as operations research analysts or in closely related occupations, such as systems analysts, computer scientists, or management analysts.
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?Operations research? and ?management science? are terms that are used interchangeably to describe the discipline of applying advanced analytical techniques to help make better decisions and to solve problems. The procedures of operations research have been used effectively during wartime in areas such as deploying radar, searching for enemy submarines, and getting supplies to where they were needed most. New analytical methods have been developed, and numerous peacetime applications have emerged, leading to the use of operations research in many industries and occupations.
The prevalence of operations research in the Nation?s economy reflects the growing complexity of managing large organizations that require the effective use of money, materials, equipment, and people. Operations research analysts help determine better ways to coordinate these elements by applying analytical methods from mathematics, science, and engineering. Analysts often find multiple possible solutions for meeting the particular goals of a project. These potential solutions are then presented to managers, who choose the course of action that they perceive to be best for the organization.
Operations research analysts often have one area of specialization, such as working in the transportation or the financial services industry, but the issues and industries in which operations research can be used are many. In general, operations research analysts may be involved in top-level strategizing, planning, forecasting, allocating resources, measuring performance, scheduling, designing production facilities and systems, managing the supply chain, pricing, coordinating transportation and distribution, or analyzing large databases.
The duties of the operations research analyst vary according to the structure and management of the employer?s or client?s organization. Some firms centralize operations research in one department; others use operations research in each division. Operations research analysts also may work closely with senior managers to identify and solve a variety of problems. Some organizations contract with consulting firms to provide operations research services. Economists, computer systems analysts, mathematicians, industrial engineers, and others may apply operations research techniques to address problems in their respective fields. (These occupations are discussed elsewhere in the Handbook.)
Regardless of the type or structure of the client organization, operations research entails following a standard set of procedures and conducting analysis to help managers improve performance. Managers begin the process by describing the symptoms of a problem to the analyst, who then formally defines the problem. For example, an operations research analyst for an auto manufacturer may be asked to determine the best inventory level for each of the parts needed on a production line and to ascertain the optimal number of windshields to be kept in stock. Too many windshields would be wasteful and expensive, whereas too few could result in an unintended halt in production.
Operations research analysts study such problems, breaking them into their components. Analysts then gather information about each of the components from a variety of sources. To determine the optimal inventory, for example, operations research analysts might talk with engineers about production levels, discuss purchasing arrangements with buyers, and examine storage-cost data provided by the accounting department.
With the relevant information in hand, the analyst determines the most appropriate analytical technique. Techniques used may include Monte Carlo simulation, linear and nonlinear programming, dynamic programming, queuing and other stochastic-process models, Markov decision processes, econometric methods, data envelopment analysis, neural networks, expert systems, decision analysis, and the analytic hierarchy process. Nearly all of these techniques involve the construction of a mathematical model that attempts to describe the system being studied. The use of models enables the analyst to explicitly describe the different components and clarify the relationships among them. The descriptions can be altered to examine what may happen to the system under different circumstances. In most cases, a computer program is developed to numerically evaluate the model.
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