OPERATIONS RESEARCH

In today’s complex business world, operations research is gaining traction. Today, well-defined Operations Research tools provide support for every complex industry problem. Making decisions in today’s social and business environment is becoming increasingly difficult. Well-structured problems are routinely optimized at the operational level of organizations, and increased attention is now focused on broader tactical and strategic issues. To effectively address these issues and provide leadership in the advancing global age, decision-makers cannot afford to make decisions based solely on personal experiences, educated guesses, or intuitive feelings, because the consequences of poor decisions are serious and costly. As a result, understanding the applicability of quantitative methods to decision-making is critical for decision-makers. One such tool is operations research, which allows for the comparison of all possible alternatives (courses of action) to determine potential outcomes, as well as the examination of the solution’s sensitivity to changes or errors.

Meaning

OR is the application of scientific methods to complex problems in the direction and management of large systems of men, machines, materials, and money in industry, business, and defense government. The unique approach is to create a scientific model of the system that includes measurements of factors such as chance and risk in order to predict and compare the outcomes of various decision strategies and controls. The goal is to assist management in making scientific policy and action decisions.

— Journal of OR Society of UK

“OR is an experimental and applied science devoted to observing, understanding and predicting the behavior of purposeful man-machine systems; and OR workers are actively engaged in applying this knowledge to practical problems in business, government and society”

— OR Society of America

This definition is not widely accepted and is frequently criticized because it focuses on complex problems and large systems, implying that OR can be used in highly technical and sophisticated environments of large organizations.

Problems in operations research are broken down into basic components and then solved in defined steps using mathematical analysis. Mathematical logic, simulation, network analysis, queuing theory, and game theory are examples of OR analytical methods.

Uses of Operations Research

The fundamental question that arises is what the significance of OR is. We need to understand various OR techniques for the following reasons.

• The problem may be complex enough that a simple guess will not suffice. Techniques assist in arriving at a feasible solution to a problem, albeit after thorough analysis and research.
• The problem is critical, and no sluggishness on the part of the decision-maker is acceptable. OR can also help in this situation. OR methodologies are so detailed and meticulous that even a small margin for error is unaffordable. 
• The problem is novel, and there is no precedent to guide logical and intelligent decision-making. OR comes to the rescue of analysts in this situation because OR has a large pool of techniques that aid in solving even new and unanticipated problems.
• Because the problem is repetitive, a model could be developed to improve decision-making speed and accuracy. Again, OR is invaluable in assisting analysts in such a situation by providing either a readymade model or a readymade process for developing such a model and pacifying the decision-making process.

Scope of Operations Research

Transportation, inventory planning, production planning, communication operations, computer operations, financial assets, risk management, revenue management, and many other fields where increasing business productivity is critical are addressed by operations research.

Because OR has made significant contributions in almost all industries, almost all managerial and decision-making functions, and at almost all organizational levels over the years, the list of OR applications is extensive. Successful OR applications can be found in a variety of industries dealing with issues such as planning, routing, scheduling, forecasting, process analysis, and decision analysis.

OR aid decision-makers in nearly any management function. To illustrate, OR aids in key decision-making, allows for the resolution of urgent problems, can be used to design improved multi-step operations (processes), establish policies, aids in planning and forecasting, and measures actual results.

Manufacturing: OR’s success in modern business can be found in manufacturing and service operations, logistics, distribution, transportation, and telecommunication.

Operations research is used for a variety of activities such as scheduling, routing, workflow improvements, bottleneck elimination, inventory control, business process re-engineering, site selection or facility selection, and general operational planning.

OR, using pattern recognition and graph theory algorithms, assists in the development of software for material flow analysis and design for flexible manufacturing facilities. In addition, approaches for designing reconfigurable manufacturing systems and progressive automation of discrete manufacturing systems are being developed. Other OR projects concentrate on the industrial application of computer-based methods for assembly line balancing, business process reengineering, capacity planning, pull scheduling, and setup reduction.

Revenue Management: The use of OR in revenue management entails two steps: first, accurately forecasting demand, and second, adjusting the price structure over time to more profitably allocate fixed capacity.

Supply Chain Management: OR aids in Supply Chain Management decisions such as who, what, when, and where abstractions from purchasing and transporting raw materials and parts to manufacturing actual products and goods and finally distributing and delivering the items to customers.

The primary goal here is to lower overall costs while processing customer orders more efficiently than previously. The ability to use OR methods allows for a thorough examination of a rather complex and convoluted chain, as well as a search among a vast number of combinations for the resource optimization and allocation strategy that appears most effective, and thus beneficial to the operation.

Retailing: OR groups in supermarkets analyze data from store loyalty card schemes to advise on merchandising policies and profitability improvement. OR methods are also used to decide when and where to build new store developments.

Financial Services: OR practitioners in financial markets deal with issues such as portfolio and risk management, as well as customer service planning and analysis. They are widely used in Credit Risk Management, which is a critical area for lenders looking to find the best balance of risk and revenue. Cash flow analysis and capital budgeting both use OR techniques.

Marketing Management: OR assists marketing managers in making the best product mix selection. It assists them in making the best sales resource allocation and assignment decisions.

Human Resource Management: OR techniques are widely used in the functional area of Human Resource Management, assisting human resource managers with activities such as manpower planning, resource allocation, staffing, and training program scheduling.

General Management: OR assists in the design and management of Decision Support Systems and information systems, organizational design and control, software process management, and knowledge management.

Productions Systems: Production systems is a branch of operations research that focuses on real-world operational problems. Manufacturing, telecommunications, healthcare delivery, facility location and layout, and staffing are just a few of the industries where production system issues can arise.

For operations researchers, the field of production systems presents unique challenges. Because production problems are operations research problems, they must be solved with a solid foundation in operations research fundamentals.

Application of Operations Management

Managing consumer credit delinquency in the US economy: A multibillion-dollar management science application: GE Capital provides credit card services for a consumer credit business with total outstanding dollars exceeding $12 billion. Its goal is to optimize delinquency management by improving the allocation of limited collection resources to maximize net collections across multiple billing periods. To provide accurate data on collection resource performance, GE created a probabilistic account flow model and statistically designed programs. A linear programming formulation generates optimal resource allocations that have been implemented throughout the organization.

Control of the water distribution system under the Irrigation scheme in Malaysia: For a Malaysian irrigation scheme, a linear programming optimization model was developed and adapted for daily operating decisions that would provide proper control of the water distribution system in real-time. The optimization model uses water orders as input, and the water ordering program uses a simplified routing method to solve the unsteady state condition. Using the linear programming technique, the routed flow is then optimized by minimizing the deviation between gate releases and user water order demands. As constraints, the system’s physical limitations and water volume balance are used.

Formulating insurance policies by Life Insurance Company in India: LIC uses OR to determine the premium rate for its various policies, as well as how best to distribute profits in the case of profit policies.

Application of OR for optimum utilization of urban facilities: Citizens are increasingly demanding more urban services in terms of type, quantity, and quality. The resulting tension between demands for more and better services on the one hand and decreased revenue on the other has created a strong need for improved management decision-making in urban services.

As a result, OR is widely used for the effective and efficient allocation or deployment of urban service system resources, such as personnel, equipment, and various service-improving technologies.