Data Maturity

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The Open Institute

Data Maturity Model

This is a framework that helps organizations understand and improve their data management capabilities.
Each stage builds upon the previous one and represents a higher level of maturity in the organization's ability to effectively collect, store, and use data.

THE STAGES 

01

Seedling

This stage is the initial step that counties take towards building their data infrastructure. Data is collected as part of operations but without a specific use or objective, it is not processed for use or consumption.

Physical data collection
Data is collected infrequently, and not on a regular schedule
Data is stored in a format that cannot be easily accessed or used by most stakeholders
Data comes from a single source or only within the county govt

02

Growing

Data infrastructure is improving at this stage to accommodate regular collection and reporting. The use of data is integrated into departmental processes and regulations. The system has expanded to include data from other sources within the local and national government.

Physical/automated data collection
Data is collected infrequently, but on a regular schedule
Data is reported quarterly/yearly
Data is stored in a format that can be accessed within government, but with restrictions
Data comes from multiple internal sources, with no formal mechanism for collaboration
Data collection is required for administrative reporting

03

Flowering

Data-driven decision making is a priority at this stage of maturity. The use of technology is integrated into data management practices. The scope of data collection is widened to include partnerships outside the government. The data is reliable and available to all interested parties.

Physical/automated data collection

Data is collected infrequently, but on a regular schedule
Data is reported quarterly/yearly
Data is stored in a format that can be accessed within government, but with restrictions
Data comes from multiple internal sources, with no formal mechanism for collaboration
Data collection is required for administrative reporting

04

Fruitful

At the final stage of maturity, data is used for innovation and strategy. High quality data is freely available and up to date due to an intentional boost in resourcing and supportive legislation. Contextual data such as location and demographics is included for more robust analysis.

Data collection is legally mandated, with penalties for not reporting data
Database is updated in real time
Data is stored in a format that can be used by all stakeholders without restrictions
Collaborators can contribute to databases and use available data for new projects
Audit reports are also available to the public
Stakeholders have clear channels for feedback based on shared data
The county has a budget with an extensive funding stream for data functions
The county elected representatives and management prioritise data quality and availability in their operations
Marginalised groups are considered in data-driven decision making