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Operations Research, Management Science, and Industrial Engineering

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[Stanford University]



- Operations Research

Operations Research (OR) is a discipline that deals with applying advanced analytical methods to help make better decisions. OR is generally considered a subfield of mathematical sciences. Disciplines similar to or overlapping with OR include statistical analysis, management science, game theory, optimization theory, artificial intelligence, and network analysis. The goal of all these techniques is to solve complex problems and improve quantitative decision-making. 

The OR field offers more powerful decision-making methods than ordinary software and data analysis tools. Hiring OR professionals can help companies obtain a more complete data set, consider all available options, predict all possible outcomes, and estimate risk. Additionally, OR can be tailored to a specific business process or use case to determine which technologies are best suited to solve the problem.


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[New York City, New York - Civil Engineering Discoveries]

- Management Science

In 1967, Stafford Beer described the field of management science as "the commercial use of operations research". Like operations research itself, management science (MS) is an interdisciplinary branch of applied mathematics dedicated to optimizing decision planning, with strong links to economics, business, engineering, and other sciences. It uses a variety of scientific research-based principles, strategies, and analytical methods, including mathematical modeling, statistical, and numerical algorithms, to improve organizational development by finding optimal or near-optimal solutions to complex decision-making problems. The ability to manage decision-making. Management scientists use the scientific method of operations research to help businesses achieve their goals. 

The task of management scientists is to use rational, systematic, science-based techniques to inform and improve decisions of all kinds. Of course, the techniques of management science are not limited to commercial applications, but can also be applied to military, medical, public administration, charitable, political, or community groups. 

Management science is concerned with developing and applying models and concepts that may help clarify and solve management problems, as well as design and develop new and better models of organizational excellence. 

The application of these models in the corporate sector is known as management science.


- Financial Engineering 

Financial engineering is the use of mathematical techniques to solve financial problems. Financial engineering uses tools and knowledge from the fields of computer science, statistics, economics, and applied mathematics to solve current financial problems and design new and innovative financial products. 

The most popular computer languages ​​used by financial engineers include: Python, Java, C++, Scala. However, it is important for aspiring financial engineers to be able to go beyond simple coding mastery. To complement their programming abilities, financial engineers should also be able to demonstrate higher-level computer science skills, including advanced modeling and mathematics. Additionally, artificial intelligence (AI) has become an increasingly important technology for financial engineers as they seek to understand, model and predict volatile financial markets.

Financial engineers work at the intersection of data science and the financial industry. For this reason, it is important for aspiring financial engineers to gain an in-depth understanding of market trends and current events about the world economy. Subscriptions to publications such as the Financial Times, The Economist, and The Wall Street Journal all provide a solid foundation for news reporting and analysis that can be incorporated into financial forecasting and modeling.


- Industrial and Systems Engineering

Industrial engineering is an engineering profession that optimizes complex processes, systems or organizations by developing, improving and implementing integrated systems of people, money, knowledge, information and equipment. Industrial engineering is at the heart of the manufacturing business. 

Industrial engineers use specialized knowledge and skills in mathematics, physics, and social sciences, as well as principles and methods of engineering analysis and design, to specify, predict​​, and evaluate outcomes from systems and processes. 

Systems engineering is an interdisciplinary and integrative approach that uses systems principles and concepts and scientific, technical and managerial approaches to enable the successful implementation, use and decommissioning of engineered systems. 

The goal of all systems engineering activities is to manage risk, including the risk of not being able to deliver what the customer wants and needs, the risk of late delivery, the risk of excess costs, and the risk of negative unintended consequences. One measure of the utility of systems engineering activities is the degree to which such risks are reduced. Conversely, the measure of acceptability that systems engineering activities are missing is the resulting level of excess risk.



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