The Power of Operational Research in Business Decision-Making

By Bob Scott, Board Member, The OR Society

In today’s fast-paced business environment, where AI and big data dominate, a lesser known yet equally powerful tool is transforming decision-making: Operational Research (OR). Often described as “the art and science of decision-making,” OR combines advanced mathematics, data analytics, and human insights to tackle complex business challenges.

Originally developed during World War II to enhance military operations, OR offers a structured, evidence-based approach to decision making that goes way beyond data analysis, enabling organisations to optimise their processes, reduce risks, and improve efficiency.

How OR can drive business success

OR specialists collaborate with organisations to understand their challenges and goals and create mathematical models, algorithms, and customised tools to solve complex problems. For instance, an OR expert may work with a logistics company to optimise its delivery routes by considering traffic, fuel expenses, and deadlines, or help a retailer analyse sales data to determine optimal levels of stock to meet demand.

By modelling scenarios and evaluating potential outcomes, OR helps leaders make informed decisions. This approach allows businesses to anticipate challenges, streamline operations, and allocate resources more effectively.

While AI and big data excel at predicting trends and identifying patterns OR takes these insights further by offering actionable solutions. For example, AI might forecast a spike in product demand, but OR will determine the most efficient way to meet that demand, for example, whether production schedules should be adjusted, or resources reallocated.

Real-World Applications

OR in Practice: The Pilkington Example

One classic OR application outside a military setting is by British glass manufacturer Pilkington UK, part of the NSG Group. During the 1960s, they faced the “cutting stock problem” and needed to cut large glass sheets into smaller sizes to meet specific customer demands while minimising waste. By applying linear programming, Pilkington optimised its cutting patterns to match orders, reduced costs, and improved production efficiency. This allowed the company to respond more flexibly to customer orders, offer competitive pricing, and enhance delivery times. Pilkington’s use of linear programming set a precedent for solving real-world business problems with sophisticated analytical tools.

OR in business today

OR’s impact today can be seen across different industries. In healthcare, OR optimises patient flow, manages bed allocation, and reduces waiting times, directly improving patient care. It is also helping to save lives too and in NHS Wales OR interventions have led to significant improvements in cancer survival rates. Modelling led to the establishment of “rapid diagnostic hubs” and Wales became the first UK nation to introduce a single waiting time target for cancer patients, ensuring timely access to the right resources and the best outcomes for patients.

At airports OR is used to optimise airport operations, from reducing security queue times during peak travel periods to streamlining baggage handling systems. It has also enabled a smooth transition to electric buses in the Netherlands, where electrification of the network required significant operational changes and real time adjustments to handle delays and ensure buses had adequate electrical charge.

The Future: Simulation and Digital Twins

An exciting innovation in operational research is the deployment of digital twins and simulation technologies. A digital twin is a model or representation, often a simulation, of an actual business process, operation, or facility. It allows companies to experiment with different strategies in a virtual environment before implementation.

Using Digital twins, organisations can assess and optimise their designs—such as trialling new paint colours for cars or refining aircraft components, ahead of their physical production. This reduces development costs, minimises waste, and accelerates innovation.

From automotive and aerospace to construction and manufacturing, digital twins provide a dynamic, interactive environment for simulating, testing, and analysing real-world scenarios, leading to improved decision-making and product performance.

In the future, Digital twins are likely to be used more frequently in various sectors. In smart cities, they could optimise urban planning and infrastructure management, while in healthcare, digital twins of patients could personalise treatment and enhance medical outcomes.

Why businesses should embrace OR

Operational Research provides a clear, structured approach to decision-making that complements the predictive power of AI, and the insights offered by big data. In a world filled with data but lacking actionable insights, OR is a critical tool for smart, strategic decision-making. Furthermore, by integrating OR into their strategic toolkit, organisations can unlock new levels of efficiency, resilience, and innovation.