Our model
Data Product Maturity Model (DPMM)
RDI’s exclusive Data Product Maturity Model (DPMM) is a framework that helps organizations gradually enhance their data competencies, leading to improved data monetization and revenue capabilities.
Four domains
Data Foundations & Governance
The principles and policies for managing data, including quality, security, and compliance.
Data Engineering & Infrastructure
The technical infrastructure to collect, store, and process data so it is accessible and usable.
Analytics & Intelligent Insights
Analytics tools and techniques that turn data into actionable insight for informed decisions.
Security, Privacy & Ethics
Data practices that meet legal and ethical standards and protect customer trust.
Four maturity levels
Reactive Data Management
Teams respond to data issues as they arise. Practices are ad hoc, with little standardization or governance, which causes inefficiencies and missed opportunities.
Standardize Data Practices
Standard definitions and processes reduce errors and improve quality. The organization begins to recognize the importance of data governance.
Proactive Data Governance
Governance frameworks manage data strategically and align it with business objectives, with clear roles for data stewardship and cross-functional collaboration.
Integrated Data Strategy
Data is treated as a strategic asset. Advanced analytics and AI inform decisions and create new revenue streams.
How the model is used
Every RDI engagement starts from the DPMM. It gives you a shared reference point: where your data products sit today, what the next level requires, and which investments move you forward. Most organizations start from one of three points.
Starting from scratch
Use the DPMM to baseline your current level across the four domains. Then set governance standards that move you from ad hoc practice toward standardized definitions and processes.
Preparing for AI
Use the four DPMM domains to test readiness for AI across your data and technology. The gaps you find set the priorities for reaching the level where AI can reliably run in production.
Data into revenue
Map each maturity level to its monetization potential, then use the DPMM to prioritize which data products to monetize first, whether through direct sales or internal efficiency gains.
Running Program
Use the DPMM to measure operating maturity: track metadata freshness, platform health, and adoption each quarter, and raise the target level as your governance practices mature.
Take a deeper dive
Our two whitepapers go beyond the model overview. Read them to understand the thinking behind the DPMM and how it applies to your business.
Get AI Ready
A strategic framework for data product maturity. Read it to see why your data catalog is critical infrastructure for AI and how to build AI-ready data foundations.
From Data to Dollars
Drive revenue growth through data product maturity. Read it to learn how the DPMM supports data monetization and how each maturity level builds toward revenue.