Abstract:
As a result of the limited availability of resources, companies need to establish a decision-making process which determines what products should be included in their offering. As a result, product portfolio management (PPM) should be conducted, aimed at the selection and positioning of an optimal product portfolio. Based on existing literature, this study argues that the use of a data-driven decision-making process leads to more effective PPM. This requires the use of data as the primary decision-making rationale for product portfolio decisions. A single case study research is conducted to explore the data-driven portfolio decision-making process and its related challenges and key success factors (KSF’s). The data used consists of a number of interviews and documents. This study has led to a characterization of the data-driven portfolio decision-making process. Further, this study has found seven related challenges that hinder the process via numerous ways. Moreover, this study has found six KSF’s that support the process via numerous ways and are able to address the challenges. With these results, this study extends the existing literature on PPM, data-driven decision-making and the evidence-based portfolio decision-making process.
