Statistics in context: grounding quantitative decision-aid in business needs
Résumé
We propose to present some insights coming from our past research on a semiconductor wafer production plants. The general objective was to implement statistical methods, to improve business decisions. However, we rapidly discovered that introducing statistics in practice is not straightforward when people are not used to it. Consequently, we developed a comprehensive decision-aid process, based on an operation research framework proposed by A. Tsoukiàs. The process is divided in two main stages. Firstly, the context of the decision and the decision problem are formalized. We used a qualitative case-study methodology to build this formalization. The second stage aims at providing quantitative answers to the decision problem. In this perspective, we first built and validated a statistical model, before intergrating it in a specific user-oriented decision-aid analysis. As a result, the model finally provide a quantitative output that fits exactly to the business decision-maker's needs. This shows that the question of statistical modelling is not sufficient when developing statistical approaches in business contexts: it is necessary to formalize and analyze the application context, to refer to expertise for specific validation steps, and to integrate the models obtained within user-oriented decision-aid analyses or tools.