Alejandro Pursals, former professor of Accounting at the University of Barcelona, proposes a business management model based on fuzzy logic that surpasses conventional models in contexts of uncertainty or scarcity or unreliability of quantitative analysis data. Pursals presented his study “La toma de decisiones empresariales inciertas mediante el uso de técnicas cualitativas” (Making uncertain business decisions through the use of qualitative techniques) in the Third International Act of the Royal European Academy of Doctors-Barcelona 1914 (RAED).
For the researcher, the qualitative techniques help, through the fuzzy logic, to a better accuracy in the business decisions when they are under environments of indecision or uncertainty of data, to estimate the costs of both economic and technical factors. “Designing fuzzy logic models for production planning isn’t a substitute for deterministic models, but rather provides a strong and effective alternative for application in environments with uncertain conditions where the use of deterministic models does not is very realistic”, explains Pursals.
“The need to make business decisions based on estimates, when these technical or economic factors are limited, creates uncertainty in sales planning, costs and cash flows”, continues Pursals, who distinguishes between qualitative and quantitative techniques to quantify the value of these factors, while the former lead to a parametric estimation, the latter to an analytical estimate.The difference between them lies in the level of data integrity.
In order to fulfill its function of managing the company in the most efficient way, optimizing resources and reducing costs, the manager must know how to use all the tools at his disposal minimizing the quality of the data he has available and without surrendering to the rigidity of a analysis that limits their powers, argues the researcher.