DQ Options: Evaluating Data Quality Projects Using Real Options

Abstract

Data plays a critical role in organizations up to the point of being considered a competitive advantage. However, the quality of the organizations’ data is often inadequate, affecting strategic and tactical decision making, and even weakening the organization’s image. Nevertheless it is still challenging to encourage management to invest in data quality improvement projects. Performing a traditional feasibility analysis based on Return on Investment, Net Present Value, etc., may not capture the advantages of data quality projects: their benefits are often difficult to quantify and uncertain; also, they are mostly valuable because of the new opportunities they bring about. Dealing with this problem through a real options approach, in order to model its intrinsic uncertainty, seems to be an interesting starting point. This paper presents a methodological framework to assess the benefits of a Data Quality project using a real options approach. Its adequacy is validated with a case study.