Operations Research: How It Can Optimize Organizational Processes

By Dr. William Oliver Hedgepath  |  11/26/2024

Operations research (OR) is not a new concept. Its origins trace back to World War II, and it was born out of the desperation of military and civilian leaders who needed to find optimal solutions to complex problems.

However, precisely defining operations research is no easy feat. It employs a variety of mathematical tools and scientific methods to tackle a variety of real-world issues.

What Is Operations Research?

Operations research is about using scientific methods to make well-informed decisions. In the decades since World War II, the scope of operational research has evolved to reflect the growing complexity of systems and advances in computer technology.

These operations encompass elements such as people, machines, policies, regulations, and laws functioning in some organized, intentional capacity. These elements interact within dynamic and often complex systems, where each component plays a role in achieving specific objectives or outcomes.

Operations research has become an indispensable tool, aiding leaders in addressing pressing issues in supply chain management, transportation, and reverse logistics. Its processes involve experts from various disciplines, such as mathematicians and managers, who create applied mathematical models and data processing methods to analyze vast amounts of data.

Operational Research in Business, Government, and Society

During my tenure with the Department of Defense (DoD), we tackled questions about the most effective use of weapons for the Army and Air Force. Many companies adopted operations research, contracting major firms to solve their problems.

While working with the DoD, I had the pleasure of collaborating with the RAND Corporation for 10 years, a premier company that uses mathematical programming and management science to solve problems. RAND brought together experts from diverse fields, such as psychology, social sciences, and applied mathematics.

Other notable companies have also employed operational research techniques to better understand their complex networks, their supply chain management, and their supply chains so that they can optimize transportation routes. These organizations include Procter & Gamble and UPS.

While operations research is widely used in organizations today to save and make money, it also plays a vital role in government agencies, helping combat social issues like human trafficking by analyzing data patterns to disrupt criminal activities. Operations research is even relevant for data scientists, who apply its principles to develop effective strategies in sectors such as logistics, finance, and healthcare.

Military Use of Operations Research

The military has a rich history of forecasting and predicting how servicemembers will perform in combat. Some civilian and military analysts have used models on paper, and the military is also using computer simulations. 

Many of these simulations are linked to other simulations and live training exercises, as well as live combat operations. These tools use quantitative data and are closed systems, meaning they are not linked to another model.

For instance, a combat operations model focused on weapon usage would not be linked to a logistics or supply chain model. With the use of artificial intelligence (AI), these military models are now linked to a diverse array of models, including communication networks, to provide comprehensive, interconnected analyses.

Addressing Complex Problems through Operations Research

Although operational research might sound similar to the mathematical modeling of business operations, the questions being asked are often more complex than they initially appear. Operations research brings together information from a wide range of disciplines to tackle intricate issues.

Imagine that operation research is similar to a police officer who is taking testimony from 10 different witnesses about a traffic accident. Each person has a different view of the accident, depending upon the time frame, their age, and their education level. Blending all of this information is what an operations research analyst does.

Consider a company that wants to build a new manufacturing plant. There are many factors to consider: investment costs, regulatory constraints, supply chain logistics, and training workers. The result is an almost overwhelming set of alternatives that need to be considered before investing in the new plant, but operations research can be useful in aiding decision makers by providing useful information.

The Complexity of Problem Identification

Operations researchers and managers face an age-old conundrum: solving a problem within a group of complex systems. A core aspect of operations research is navigating the vast array of possible solutions to pinpoint the right problem to address, a process known as “problem identification” or “problem framing.”

Key Considerations in Problem Framing and Data Selection

As a cross-functional team of analysts and managers consider the correct problem to tackle, there are some factors to examine. They include complexity and data collection.

Complexity

Complexity in this context means how a problem is seen according to many interdependent variables. Some variables may be connected, while others may seem connected but are too weak to offer a clear path toward a solution.

When examining variables, you must be willing to discard some of them. Data is just another name for variables, and not all information that you collect needs to be used.

Data Collection

How up to date is the information you’re using to make decisions? Is it data that is currently being collected, or is historical data more important? How long has the data been collected for each variable?

In my Ph.D. thesis, for instance, my data spanned 400 years of combat data and consisted of 40 different variables. The goal was to use operations research to predict who would win the next battle.

Winning a battle is not by chance; it’s not a coin toss. Linear programming and neural network modeling using 28 computers over three years produced a model to predict combat outcomes. For a business problem, the same data overload could be challenging.

The Impact of Cognitive Bias and Stakeholder Bias in Operations Research

Since we are human, there is a constant problem of bias such as cognitive bias and stakeholder bias. These biases can adversely affect operations research and lead to less satisfactory outcomes.

Cognitive Bias

With cognitive bias, people may favor certain variables or data. They will approach a problem with preconceived solutions, which can influence their perception of the problem that needs solving.

When a police officer interrogates witnesses to an accident, for instance, cognitive bias can come into play. As a result, that police officer may make incorrect assumptions about the veracity of those witnesses.

Stakeholder Bias

A close relative to cognitive bias is stakeholder bias. I have been in many DoD meetings where an Army or Air Force general stated what the core problem was and directed the analysis toward a solution they had determined was accurate.

These generals would demand a report of the problem and a solution within a specified timeframe. However, such stakeholder demands can pose significant challenges to an operations research approach, because they often limit how broadly a problem can be analyzed. When high-ranking stakeholders define the problem and the solution from the start, it can push operations research teams into focus on confirming those views, rather than fully exploring other possibilities.

This pressure for a solution can lead to biased analysis. As a result, alternative solutions or key factors get overlooked, resulting in a solution that may not fully address the real issue.

Operations Research and Time

In operations research, it is crucial to consider the age of a problem. For example, the problem itself may change over time and experience rapid growth.

What is the correct answer today may change over the next few days, weeks, or months. Ideally, there should be a continuous assessment of the used and unused variables and data in operations research.

Measures of Effectiveness

A key tool in OR is the Measures of Effectiveness (MOE), which evaluates how well a solution or process meets its goals. Essentially, MOEs are metrics that help decision-makers understand whether they’re making real progress and achieving what they set out to do. While MOEs may seem to be simple, they are often very complex and necessitate careful planning to ensure they’re truly meaningful and focused on the right areas.

Over time, the scope of problems often continues to increase in complexity. Examples of MOEs in business include metrics like customer satisfaction, cost-benefit analysis, production times, and inventory turnover.

The Integration of Artificial Intelligence Technology into Operations Research

AI technology has strengthened the problem-solving abilities of business managers, military leaders, and scientists. Today’s AI tools can process large amounts of data in seconds or minutes, which is particularly useful in situations that require fast solutions.

For example, operations research professionals can leverage an AI tool to predict where enemy forces or weapons like enemy aircraft might be. Autonomous drones can conduct surveillance and combat missions, potentially saving the lives of human Air Force pilots. AI can also help operations research analysts detect and respond to real-time cyber threats more quickly.

Ethical Considerations in Operations Research

Due to the biased nature of human decision-making processes, marginalized individuals and communities and diverse cultures are important factors to consider when operations research professionals gather data and define a problem.  

OR professionals must consider the ethical implications of their decisions, especially when integrating AI into business strategies. This work means balancing technical skills with ethical considerations, such as privacy, fairness, and societal impact, to ensure responsible and effective decision-making for real-world problems.

There are several ethical areas of concern. One is data privacy: the collection of data could impact the individuals who are providing it.

Then there is data security – once collected, data must be protected to ensure no one tampers with it. The data and the mathematical models created from it need to be designed with fairness in mind to avoid any kind of bias and ensure efficiency.

Data collection must also be transparent. Both managers and employees collecting sensitive data must understand the methods that were used to gather data, how that data will be used, and what decisions were used exclude certain data.

From Data to Decisions: The OR Advantage

Operations research has evolved from its wartime origins into a multifaceted discipline that addresses complex problems across various sectors. It is a major part of our busy world.

Organizations like the Operational Research Society have also been instrumental in expanding the influence of operations research, enabling businesses to optimize their processes and reduce costs more effectively.

The integration of diverse fields such as mathematics, psychology, and social sciences have enriched operations research, making it a powerful tool for making data-driven decisions. As we continue to harness the potential of operations research, it is essential to approach it with a sense of ethical duty and a commitment to positive societal impact.

By blending scientific rigor with ethical awareness, OR can continue to be a force for good, helping us navigate the complexities of the modern world and create a better future for everyone.

Business Administration and Management Degrees at American Military University

For adult learners interested in topics such as business management, operations research, and strategic planning, American Military University (AMU) offers various degrees such as:

• An online associate degree in business administration
• An online associate degree in management
• An online bachelor’s degree in business
• An online bachelor’s degree in business administration
• An online bachelor’s degree in business analytics
• An online bachelor’s degree in management
• An online master’s degree in applied business analytics
• An online master’s degree in business administration
• An online master’s degree in management

Courses in these degree programs are taught by experienced faculty members with a deep knowledge of business and management. In addition, these programs have specialty accreditation through the Accreditation Council for Business Schools and Programs (ACBSP®) to ensure that they have met rigorous academic standards.

For more information about AMU’s programs, visit our business administration and management program page.