The rise of data analytics, big data, and computing power has brought many opportunities for companies to start using different IT tools in their planning and operations. Among these tools, we always mention the power of optimization models, Cassotis' specialty, in which we use mathematical programming to represent complex situations and identify the best solution according to some specific objectives. Some examples are presented in the Cases section of our website, with different applications and industries.
Among the many benefits that an optimization tool can bring, some are related to the decisions taken and others to the decision-making process itself. Therefore, most can be obtained regardless of where they are being applied. These are benefits that we believe can improve any company's competitiveness and results:
There are decisions that involve so many variables and possibilities that it is just impossible for a human to observe all the possible solutions and identify the best one. Some examples are problems such as vehicle routing, production scheduling, and packing - their complexity increases exponentially as the size of the problem increases, and millions (or even billions and trillions) of solutions can exist.
Using optimization models and algorithms, and taking advantage of the computing power of new computers, it is possible to solve most problems in a reasonable time.
An optimization tool is usually designed to assist the decision-makers; not to replace them. In this process, they are consulted and the knowledge from the different parties involved is inserted into the model. This enables to gather the knowledge of many people into a single tool, which can evolve alongside its users. It also contributes to the perpetuity of knowledge in the company.
One advantage of using optimization tools is to reduce the time of the decision-making process and allow the users to focus their time on the analyses. In many cases, the companies are inserted in a constantly changing environment and the decisions must be taken fast to adapt to new situations. With an optimization model, all the user needs to do is to update some parameters and execute the model to find new solutions and start the analysis.
Sometimes the output of an optimization model can be counterintuitive. In these cases, it usually generates an opportunity for discussion between different specialists and planners, who will try to understand the solution and verify its feasibility.
There are some models where the solutions involve so many variables that they promote the integration of different departments and areas to find the best global solution. Our integrated models for the mining and metals industries are great examples!
When making decisions, humans are not always rational: besides the use of expertise and experience, we tend to use our intuition and many heuristics to simplify the process, as we have brought up in this insight. Even if in most cases this is helpful, sometimes these heuristics and our intuition may result in inappropriate decisions, due to the existence of some biases.
The use of an optimization model reduces the existence of such biases and noise in the decision-making process: the solver will always look for the best solution according to the defined objective function.
Each of these benefits contributes to the success of an organization. Whether it allows better decisions or improves the process, they are part of the reasons why optimization models can be a key factor and make your company stand out!
Author: Cassiano Lima - Senior Consultant at Cassotis Consulting
Co-author: Fabio Silva - Senior Manager at Cassotis Consulting
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