What is Operations Research and how Fintalent can help you hire the best Operations Research Consultants?
Operations research in finance is the application of operations research methods to financial problems. It covers both quantitative and qualitative modeling approaches, as well as machine learning techniques. The methods are used to provide suggestions for making optimal financial decisions, whether by an individual or a company, which are based on mathematical models. Operations research is also found in the field of marketing and production management.
Operations research in finance is a branch of applied mathematics that uses mathematical techniques to help solve problems in economics, management science, and other disciplines. In practice the subject has been divided into two main branches: time series analysis and linear programming.In addition to its use in finance, operations research is being integrated with other fields such as operations management and business administration. Expectedly, it has also found many applications in real-world problems; for example, epidemiological studies used it to demonstrate the importance of vaccination programs during the late 19th century.
Fintalent, the hiring and collaboration platform for M&A and Strategy Professionals is a one-stop shop for hiring the best and most experienced Operations Research Consultants. Hiring managers on the lookout for Operations Research Experts can avail themselves of the opportunity presented by the invite-only platform to engage some of the best Operations Research Consultants.
Operations research in business is a branch of applied mathematics. The field is concerned with optimal design and decision-making in management, marketing, finance, materials handling, military tactics and strategy. In other words, operations research seeks to optimize business processes by making logistical decisions based on the best available mathematical models.
There are many processes in a company that need improvement or optimization that can be addressed through operations research which can help to determine the most beneficial course of action for the process at hand. Typical approaches would include a systematic investigation of a company’s supply chain utilizing optimization techniques in order to find ways to reduce costs associated with transportation logistics while maintaining service levels in order to increase revenue and profits.
Background
The term “Operations Research” started as a synonym for “Management Science” during the 1950s and 1960s. The name of the journal Operations Research was first used in 1956, and its subtitle was considered to be “A Journal for Use in Operations Research and Management Science”. The connection of the journal with OR is still present; however, other factors affected this connection between management science and OR. One of the reasons why the journal “Operations Research” became one of the most important journals in operations research was because it had a very broad coverage, and published articles from all topics related to operations research (even those not related to management science).
During this time, the use of computer technology became more common. The link between management science and operations research faded even more due to the use of computers in operations research. Operations research is now considered to be an independent discipline instead of a sub-field of management science. As information systems became more common during the 1980s, business processes also started to become more complex, and the study of business process started becoming popular. As a result, management science was separated from operations research.
Management Science was used for modeling complex decision problems for which an algorithm could be found, while OR was used for decision making with no algorithm or equations available to solve mathematical problems. Thus Management Science became a subfield of Decision Science which involves modeling and solving decision problems using mathematical techniques, algorithms, and sometimes computer simulation programs. In the same time, the analysis of strategic planning and decision analysis also started to be more common. In particular, decision analysis is a subset of OR with a focus on representing and analyzing decisions with a focus on structured analysis instead of mathematical modeling.
Organizations such as ORSA and ORSE consider these differences as specific training for two different fields, not two branches of the same field. This view is supported by many researchers who studied operations research in universities but decided to separate their career from that of management science or decision analysis. It is often argued that operations research as a field has been declining since about 1990, while some other research has been growing during this period.
In addition to its use in finance, Operations Research is being integrated with other fields such as operations management and business administration. For example, a business process may concern the production of a product over an extended period of time, with variations in production. A company may have to produce a very large number of products in a very short time, so they would need an operations research approach to help them design the best possible production system for this situation. In economics, OR can be used to investigate how demand can change without affecting costs; for example, if the price of gas increases the demand for oil may decrease because more people will choose not to see their vehicles using gasoline.
A central question in OR is how to solve a business problem. In the field of operations research, a solution may be a mathematical model that provides an optimal solution to the business problem. The use of mathematics in this way is known as mathematical programming or linear programming; this type of problem is very common and has been studied since the 1940s. Economic problems such as maximizing returns to capital, minimizing operating costs, and maximizing profits are also inherently mathematical in nature and involve linear programming techniques. The study of mathematical operations research, the mathematical study of economics and management science, is often considered to be an area of operations research.
Operations Research Limitations
The goal of optimization is to find the global optimum, the best solution to the problem. However, there are many practical limitations. For example, an optimization model may not provide a very good description of reality; it may be more suitable for application in other fields besides business or economics (for example social sciences or engineering). The problem can also be more complicated than originally expected; this means more data is required to solve the problem (analogous with finding solutions in real life), making it even harder to find a solution.
Other limitations include the number of variables and constraints, the complexity of a solution, and a lack of a global optimal solution. In addition, a solution may need to be changed over time due to unforeseen changes in business or economic conditions. For example, a company that produces steel may experience an unexpected rise in demand for steel from new customers. In order to maximize profits the company should consider expanding its output capacity to be able to fulfill the increased demand. However, if it were possible for them to determine their future demand from historical data then expansion might not be beneficial. The best possible decision would require all these factors to be considered at one time and arrive at an optimal decision for their company.
Another limitation of the OR model is the inability to predict and incorporate all factors and details in a problem. A company’s sales and profit will be affected by many different factors, such as the health of its employees, its relationship with its suppliers or change in customer tastes. The objective of an OR model should be to create a framework that allows for other factors to be added when necessary. The best way to do this is to start with a basic model and add more elements when necessary; this process is known as developing an “extended model”.
Approaches to Operations Research
A key part of operations research is to understand which modelling approach would best suit the problem. There are many approaches to modelling, each with its own advantages and disadvantages. For example, a mathematical model is the most common approach to modelling used in OR. It allows for derivation of optimal solutions for problems by examining constraints and variables in an objective function or through dynamic programming methods. Many companies use mathematical programming techniques to choose the best possible product mix for their production facility, based on factors such as unit price, unit demand and standard operating costs.
The main advantage of mathematical approaches is the ability to provide optimal solutions with complete understanding of the problem. The disadvantage of mathematical models is that it is very difficult, if not impossible, to include every factor in the analysis (the “curse of dimensionality”), and they are often difficult to understand by non-operations researchers. If the decision-maker wants an optimal solution but does not care about the details of the model, then there must be some consideration given to whether or not a mathematical approach is appropriate.
Sub-fields in Operations Research
Linear Programming seeks an optimal solution by utilizing linear relationships to develop mathematical models for problems where profit is dependent upon the output of a production process. Principal areas covered include transportation logistics, inventory management, facility location and assigning students into classrooms.
This is an area of operations research that involves techniques for modeling and performing simulations of business processes in order to gain a better understanding of the system in question. In other words, simulation models can be used to determine the effects of a proposed solution by running a “virtual” model. Simulation is typically used in cases where it would be impractical, time consuming or unsafe to implement a real-world solution.
Marketing research gathers information about the suitability of a product in an attempt to determine whether or not it should be brought into production. Another function of marketing research is to gather information from consumers concerning their opinions about competitors’ products and their use or consumption patterns.
Planning is the process of determining how to allocate resources in order to meet goals. An example would be deciding when and how much inventory to bring in when expecting an increase in demand.
Decision analysis is the study of decisions made by one or more decision makers in order to determine the most beneficial course of action. Often, there are multiple courses of actions with varying consequences that all need to be considered in order determine which course of action would result in the best outcome for all concerned parties.
Neural networks is a relatively new area that uses information processing tools similar to that found in brains in order to perform decision making tasks.
Operations research is closely tied to many areas of economics, finance and operations management. For example, it has been used in the assessment of public utilities (i.e., water allocation systems), production control (e.g., manufacturing processes) and social welfare (e.g., welfare budgets). It has also been applied in fields such as sports (for selection of athletes), business intelligence (for more efficient operations like supply chain planning), game theory (for game theory modeling), etc.
Operations research has been used to schedule employees, schedule military tactics and strategies, and to determine the most efficient way of transporting materials. Operations research techniques have been successfully applied to a wide range of business problems.
Why you need Fintalent’s Freelance Operations Research Consultants
Operations research involves mathematical simulations that model economic processes such as firm performance, worker pay decisions, and trade patterns. The goal is to reduce the cost of finding solutions for problems such as generating forecasts or identifying causal relationships between events. This process directly impacts how well institutions function in terms of managing their risks and stakeholders’ welfare during periods of market uncertainty. The foregoing underlines the importance of Operations Research to the optimal operations of firms. Fintalent provides a platform for businesses and hiring managers to hire the best hands for those seeking to hire an Operations Research Expert. Fintalent’s Operations Research Consultants are pre-screened to ensure only the best and most experienced hands are available for hire on the platform, giving hiring managers an opportunity to take advantage of a global pool of expertise.
