To derive quality from quantity

The purpose of this master thesis is to present a model that illuminates the important factors when deriving technical information from market data within a company. For companies to be able to become and stay competitive in the market, product quality is an important factor. Whilst good product quality leads to customer satisfaction and loyalty, lack of quality brings costs in service and replacements. To improve product quality, the developers need information and knowledge about what quality issues affect existing products. Most companies gather data from market about known issues, but in order eliminate known quality issues in new products; this data has to be transformed into information and knowledge. Data, information and knowledge, as well as how to turn data into information and knowledge, is defined using existing theories on the area. Further, theories identifying factors that affect information creation are presented. Based on the theories, the model, ?Transformer? is created. Transformer constitutes a grasping framework for what factors affect derivation of technical information from market data. Transformer is built upon three main areas called; Organizational Factors, Human Factors and Tools. Further, harmonizing synergies have been identified as an equally important factor as each of the three areas. The practical use of Transformer is evaluated, and is demonstrated by its application to three cases found within a large technology based company. The conclusion is that information can not be created by focusing on only one, or two, of the three areas: Organizational factors, Human factors or Tools. All of the three pillars, as well as the synergies, are equally important in the process of turning market data into technical information. Even if information creation in many ways is a technical problem, it can not be solved by finding a technical solution.

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