Management science

Management science is concerned with a number of areas of study:

• Developing and applying models and concepts that may prove useful in helping to illuminate management issues and solve managerial problems. The models used can often be represented mathematically, but sometimes computer-based, visual or verbal representations are used as well or instead.^[4]
• Designing and developing new and better models of organizational excellence.
• Helping to improve, stabilize or otherwise manage profit margins in enterprises.^{[citation needed]}

Management science research can be done on three levels:^[5]

• The fundamental level lies in three mathematical disciplines: probability, optimization, and dynamical systems theory.
• The modeling level is about building models, analyzing them mathematically, gathering and analyzing data, implementing models on computers, solving them, experimenting with them—all this is part of management science research on the modeling level. This level is mainly instrumental, and driven mainly by statistics and econometrics.
• The application level, just as in any other engineering and economics disciplines, strives to make a practical impact and be a driver for change in the real world.

The management scientist's mandate is to use rational, systematic and science-based techniques to inform and improve decisions of all kinds. The techniques of management science are not restricted to business applications but may be applied to military, medical, public administration, charitable groups, political groups or community groups. The norm for scholars in management science is to focus their work in a certain area or subfield of management like public administration, finance, calculus, information and so forth.^[6]

Although management science as it exists now covers a myriad of topics having to do with coming up with solutions that increase the efficiency of a business, it was not even a field of study in the not too distant past. There are a number of businessmen and management specialists who can receive credit for the creation of the idea of management science. Most commonly, however, the founder of the field is considered to be Frederick Winslow Taylor in the early 20th century. Likewise, administration expert Luther Gulick and management expert Peter Drucker both had an impact on the development of management science in the 1930s and 1940s. Drucker is quoted as having said that, "the purpose of the corporation is to be economically efficient." This thought process is foundational to management science. Even before the influence of these men, there was Louis Brandeis who became known as "the people's lawyer". In 1910, Brandeis was the creator of a new business approach which he coined as "scientific management", a term that is often falsely attributed to the aforementioned Frederick Winslow Taylor.^[7]

These men represent some of the earliest ideas of management science at its conception. After the idea was born, it was further explored around the time of World War II. It was at this time that management science became more than an idea and was put into practice. This sort of experimentation was essential to the development of the field as it is known today.^[8]

The origins of management science can be traced to operations research, which became influential during World War II when the Allied forces recruited scientists of various disciplines to assist with military operations. In these early applications, the scientists used simple mathematical models to make efficient use of limited technologies and resources. The application of these models to the corporate sector became known as management science.^[9]

In 1967 Stafford Beer characterized the field of management science as "the business use of operations research".^[10]

Some of the fields that management science involves include:

Management science's applications are diverse allowing the use of it in many fields.^[11] Below are examples of the applications of management science.

In finance, management science is instrumental in portfolio optimization, risk management, and investment strategies. By employing mathematical models, analysts can assess market trends, optimize asset allocation, and mitigate financial risks, contributing to more informed and strategic decision-making.

In healthcare, management science plays a crucial role in optimizing resource allocation, patient scheduling, and facility management. Mathematical models aid healthcare professionals in streamlining operations, reducing waiting times, and improving overall efficiency in the delivery of care.

Logistics and supply chain management benefit significantly from management science applications. Optimization algorithms assist in route planning, inventory management, and demand forecasting, enhancing the efficiency of the entire supply chain.

In manufacturing, management science supports process optimization, production planning, and quality control. Mathematical models help identify bottlenecks, reduce production costs, and enhance overall productivity.

Furthermore, management science contributes to strategic decision-making in project management, marketing, and human resources. By leveraging quantitative techniques, organizations can make data-driven decisions, allocate resources effectively, and enhance overall performance across diverse functional areas.

In summary, the applications of management science are far-reaching, providing valuable insights and solutions across a spectrum of industries, ultimately fostering more efficient and effective decision-making processes.

• Kenneth R. Baker, Dean H. Kropp (1985). Management Science: An Introduction to the Use of Decision Models
• David Charles Heinze (1982). Management Science: Introductory Concepts and Applications
• Lee J. Krajewski, Howard E. Thompson (1981). "Management Science: Quantitative Methods in Context"
• Thomas W. Knowles (1989). Management science: Building and Using Models
• Kamlesh Mathur, Daniel Solow (1994). Management Science: The Art of Decision Making
• Laurence J. Moore, Sang M. Lee, Bernard W. Taylor (1993). Management Science
• William Thomas Morris (1968). Management Science: A Bayesian Introduction.
• William E. Pinney, Donald B. McWilliams (1987). Management Science: An Introduction to Quantitative Analysis for Management
• Gerald E. Thompson (1982). Management Science: An Introduction to Modern Quantitative Analysis and Decision Making. New York : McGraw-Hill Publishing Co.