Operations research (OR) is a discipline that uses analytical methods to improve decision-making in various fields, including business, government, and society. OR employs techniques from other mathematical sciences, such as modeling, statistics, and optimization, to arrive at optimal or near-optimal solutions to decision-making problems. The concept of OR arose during World War II by military planners, and after the war, the techniques used in their operations research were applied to addressing problems in business, government, and society.

The primary characteristics of all OR efforts include optimization, simulation, and probability and statistics. Optimization involves achieving the best performance under given circumstances, comparing and narrowing down potential options. Simulation involves building models or replications to try out and test solutions before applying them. Probability and statistics include using mathematical algorithms and data to uncover helpful insights and risks, make reliable predictions, and test possible solutions.

OR provides 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 practitioners have offices and work in the settings they are trying to improve, and they may observe staff working in a restaurant or watch workers assembling parts in a factory when collecting data.

OR is all about options, and companies look for new ways to reduce costs and raise productivity every day, turning to OR practitioners to develop solutions. OR is the application of similar ideas to larger, more complex decisions that concern the operations of systems, such as businesses and networks of machines. Making these decisions using OR entails employing mathematical methods to solve a numerical version of the problem at hand.