Operations research (OR) is a discipline that uses analytical methods to improve decision-making in organizations. It involves breaking down problems into basic components and employing techniques from other mathematical sciences, such as modeling, statistics, and optimization, to arrive at optimal or near-optimal solutions to decision-making problems. OR is often concerned with determining the extreme values of some real-world objective.

The field of OR arose during World War II, when it was used to provide a quantitative basis for decisions regarding the operations under military control. After the war, the techniques used in OR were applied to addressing problems in business, government, and society.

Some characteristics of OR include:

• It is an analytical method of problem-solving and decision-making.
• It breaks down problems into basic components.
• It employs techniques from other mathematical sciences.
• It arrives at optimal or near-optimal solutions to decision-making problems.

OR is similar to or overlaps with other disciplines such as statistical analysis, management science, game theory, optimization theory, artificial intelligence, and network analysis.

The importance of OR lies in its ability to provide a more powerful approach to decision-making than ordinary software and data analytics tools. Employing OR professionals can help companies achieve more complete datasets, consider all available options, predict all possible outcomes, and estimate risk. OR can be tailored to specific business processes or use cases to determine which techniques are most appropriate to solve the problem.

OR can be applied to a variety of use cases, including scheduling and time management, resource allocation, logistics and supply chain management, and risk management.

In summary, OR is a problem-solving and decision-making discipline that uses analytical methods to help management run an effective organization. It employs techniques from other mathematical sciences to arrive at optimal or near-optimal solutions to decision-making problems. OR is important because it provides a more powerful approach to decision-making than ordinary software and data analytics tools.