Conceptual Model for SMEs' Data Maturity Assessment

Abstract

Digital transformation has brought about a rapid shift towards a completely digital enterprise, generating a huge amount of data. Most small and medium-sized enterprises (SMEs) have data stored in different places, formats, and systems, or are unaware that it exists (Dark Data). While digital technologies are at the root of rapid data growth within and outside organizations, sharing and exchanging data between organizations presents an additional challenge. We argue that one of the barriers to the successful digital transformation of SMEs is data immaturity. The concept of data maturity has been addressed from different aspects (data quality, governance,...), in specific domains (supply chain management, manufacturing companies,...) and from the perspective of the Capability Maturity Model. However, there has been no study that has addressed a comprehensive assessment of data maturity for the SME sector as a multi-criteria problem. In this research, we propose to combine the ideas of maturity models and multicriteria decision modeling by using a design science research approach. The developed model will help SMEs assess their data maturity level and help them understand what aspects of data maturity they need to advance, what steps they need to take, and how to evaluate their progress