Whether you are managing some kind of operational process, deciding on schedule or resource allocation, a marketing manager deciding on rules or priorities, or a senior decision maker setting a strategy – operations research can contribute by objectively and scientifically examining the problems you are facing.
Operations research is all about driving more value, by helping you choose the best course of action. We accomplish this by bringing you the set of tools you need to reach the optimal decision, while weighing the different options, considering your constraints, analyzing potential gaps, checking the sensitivity for different scenarios, and comparing the consequences of possible actions.
The tools of operations research are diverse, for example, we use simulations, data science, queueing theory, and many more mathematical methods.
What is operations research analysis and how is it preformed?
- We begin by setting the research questions? (what are the goals for optimization?). There is a variety of optimization goals, according to the needs: cutting on expanses, improving customer satisfaction, maximizing profit, shortening waiting times, maximizing other measures of performance.
- The second step is to identify the different parameters which might influence the process, and setting the assumptions about the values and relations between the parameters.
- The third step is to fit a model. In this step the assumptions are weighed and a scientific model is formulized to describe the dependencies between the parameters and measures of performance.
- The next step is to take the theoretical model and implement it. This can be done by analytical computation, by simulation, or other tools. These tools enable us to estimate the values of the measures of performance under different scenarios, and to reach the best course of action under the assumptions.
After the computation is completed, we write a complete report, including recommendations and a presentation in the relevant forum.
Here are some examples from past projects we conducted:
- IoT: Formulating an optimal algorithm which balances accuracy and battery usage.
- Healthcare: Queue management, driving more value by increasing the incoming patient rate, under SLA constraints.
- Environment: Optimal waste sampling rate at a recycling facility.
- Energy: Policies for energy management at a smart facility (with distributed generation, storage, and main grid market participation).
- Finance: Optimal portfolio management system.
Operations research can fit almost every organization in many situations. Take advantage of our expertise, fill-in the details below to get in touch.