A framework of forecasting techniques as a checklist to minimize the likelihood of product design failures
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TRIZ is intended to support, among the others, the forecasting of future versions of technical systems. In this sense, the Laws of Evolution of Technical Systems range among the most powerful methods to predict possible product development patterns. The violation of these laws supposedly represents a trigger of product flops, due to an unnatural evolution of systems. It can be argued that such an infringement mainly regards the structural level of the product, also because TRIZ is mainly concerned with the description of physical components and their interactions. As it is well acknowledged from the design field, structures are essential ontological domains of products, but other dimensions are likewise relevant. First, other fundamental characterizations are represented by the product behaviour and function, whose definition might however differ with respect to its conceptualization in TRIZ domain. Second, the individuation of a more abstract goal is attracting increasing attention as a means to denote the designer’s intent and the purpose of the product in terms of human utility. By analysing lists of remarkable product failures, the author claims that reasons of fiascos cannot be fully explained by violation of TRIZ principles. Hence, other product ontological domains might be involved in unsuccessful product launches. To this aim, the paper proposes a framework comprising different forecasting and evolution models, which are sorted according to their reference to said ontological domains. For instance, dynamic Kano models are associated to the evolution of product requirements and functions. The claimed utility of the framework is the possibility of verifying whether any of the most reliable evolution patterns is infringed in new product development projects. Besides attempting to complement TRIZ body of knowledge with external models, the definition of the presented framework discloses the need for researching evolution of human needs more accurately.