Navigating your data maturity journey

Data maturity measures your organization’s level of sophistication at managing, governing and leveraging data as a strategic asset. This measurement considers data processes, skills, technologies and governance practices. Organizations with high data maturity typically have reliable data-driven decision-making processes, skilled expertise in data tools and methodologies, well-defined governance practices and optimized data technologies.

Optimized organizations, the most mature stage in the data maturity model, agilely deploy resources to advance their business initiatives. As your organization’s data maturity grows, so do innovation opportunities and your competitive edge.

	Ad hoc (initial)	Defined	Managed	Optimized
Data processes	Informal and inconsistent	Recognition of the importance of data quality and consistency	Integrated across multiple systems and teams	Continuous improvement processes to enhance data capabilities and innovation
Governance processes	Limited and minimal standardization	Basic frameworks and policies	Formal and actively enforced	Mature
Team collaboration	Data teams and business units work in silos with little collaboration	Initial cross-functional collaboration	Skilled employees with clear roles and responsibilities	Highly skilled, agile teams
Tools and technologies	Fragmented or manually operated	Select technology stack usage for data collection and processing	Use of modern tools and technologies for data management and analytics	Advanced usage of best-in-breed technologies
Decision-making approach	Often relies on intuition or incomplete data	Data management and analytics skill sets emerge that can inform decision-making	Data-driven decision-making is becoming a standard practice	Integrated ecosystem supports advanced analytics and real-time insights

Data maturity model stages

Significant data maturity milestones

How do you measure data maturity success during your journey along these four stages? Achieving the next maturity stage is one achievement measure, as is accomplishing three major priorities.

Unified data architecture: A mature data environment brings together people, processes and technology, resulting in cross-functional collaboration, agile methodologies, flexible deployment models and seamless integration with best-of-breed tools and technologies.
Role-based governance: Clearly defined governance rules assign specific responsibilities and roles for data management, driving accountability in supporting a modern data environment. Such roles foster collaboration between data teams and business units.
Predictive analytics adoption: Your data contains real power, but only if you can extract it and turn it into valuable insights. Data-mature organizations harness their data capabilities for decision-making that delivers intelligence on solutions/products, customers, innovation opportunities and market trends for a competitive advantage.

Assess your data maturity

The growth in AI makes data maturity an even greater business imperative. Understanding your organization’s data maturity is the first step in knowing the progress needed to reach the next maturity stage. How can you assess your current state? Complete our free data maturity and governance assessment to gauge your readiness.