Development of a quantification model for the cost of loss of image with customer complaints

Abstract

Despite the difficulty in measuring hidden quality costs, we must be aware not only of their existence, but also of their importance. Not surprisingly, they have been the causative factor in the closure of many companies because they are doubly dangerous. One the one hand, they represent very significant quantities of money and, on the other, they remain hidden, like the submerged portion of an iceberg [Campanella, J. (1999). Principles of Quality Costs: Principles, Implementation and Use. Milwaukee, WI: ASQ Quality Press]. Possibly one of the most harmful hidden quality costs, and most difficult to quantify, is the cost of loss of image (CLI) a company suffers because of faults detected by its customers. This paper develops an original tool that, with the use of fuzzy logic as an alternative to probabilistic theory, is capable of facilitating the quantification of the CLI in any company from the observation of its customer complaints. Once the theoretical model is presented, we proceed with its experimentation, making use of a case study as research methodology.