Data Transformation Success Model (DTSM): an A-to-Z Roadmap for Data Maturity Excellence

Enterprises are significantly investing in data and AI, yet many are struggling to achieve meaningful returns. The underlying issue in most cases is a weak or fragmented data foundation. Addressing this challenge requires first understanding what data foundation truly means within the enterprise’s context – starting with a clear assessment of data maturity. This Viewpoint introduces the Data Transformation Success Model (DTSM), a comprehensive framework that helps enterprises evaluate and elevate their data maturity across five interconnected pillars: vision and strategy, data technology and consumption, governance, people, and processes. By identifying capability gaps and benchmarking progress, DTSM enables organizations to build a strong, scalable foundation that supports long-term business goals. 

The report also highlights common pitfalls in data transformation and offers practical recommendations to overcome them. With DTSM, enterprises can align data strategies with organizational objectives, improve RoI, and drive meaningful transformation. The model’s maturity classification – laggard, typical, or advanced – helps organizations understand where they stand and develop targeted roadmaps to reach their desired state.