Guide Home / 7. Information and Systems / 7.4 Data Governance and Management / 7.4.3 Assessing Data Management and Governance Maturity

There are several different assessment tools tailored to DOT data programs that can be used or adapted as needed. In addition, several DOTs have created their own tools. Most of these tools are based on a maturity model.

A typical maturity model could include the following levels:

  • Level 1-Initial
  • Level 2-Repeatable processes
  • Level 3-Defined and documented processes
  • Level 4-Measured and managed processes
  • Level 5-Optimizing processes (continuous improvement)

Use a maturity model to identify gaps, prioritize initiatives and track progress over time.

For TAM information and systems, maturity levels can be assigned to different aspects of data management and governance. Assessments can also be conducted at different levels of the organization – from the agency-wide level, to the level of individual information systems (or even data elements).

Figure 7.4 Example Maturity Model

Table 7.6 shows the data management and information system-related assessment elements from the TAM Gap Analysis Tool, developed under NCHRP Project 08-90. Figure 7.5 illustrates the data assessment guidance created under NCHRP 08-92. This process is suitable for application either at the agency-wide level, for an individual data program, or for a business process. It goes into greater depth than the TAM Gap Analysis Tool.

Figure 7.5 Folio Describing the Transportation Agency Data Self-Assessment Process

Table 7.6 - TAM Analysis Tool Assessment Elements

ElementSub-elementSample Assessment Criteria
Data ManagementAsset Inventory
  • Complete, accurate, current inventory data
  • Critical asset components identified
  • Asset tiers identified to facilitate prioritization
  • Location-based data collection practices (e.g. GPS)
  • Appropriate mix of data collection technology
  • Inventory level of detail considers maintenance costs, accuracy, and asset criticality
Asset Condition and Performance
  • Periodic/regular collection of condition and performance data
  • Adequate level of coverage to ensure objectivity, consistency and repeatability
  • Assessments by knowledgeable personnel
  • Ability to monitor operational status of assets
  • Monitoring of public perceptions
Data Governance
  • Oversight and approval authority for all data elements
  • Single authoritative sources for shared data entities
  • Data stewardship roles and responsibilities
  • Data standards
  • Central metadata repository
  • Business rules for add/update/delete
  • Efforts to reduce redundancy
  • Quality assessment and improvement
Information SystemsSystem Technology and Integration
  • Updated asset management systems
  • Integrated to provide consistent information across assets
  • Serving multiple users and uses
  • Established requirements and standards to guide future development
  • Common geographic referencing
  • Procedure to manage changes in referencing
  • Common map-based interface
Decision-Support Tools
  • Pavement management system
  • Bridge management system
  • Assessments by knowledgeable personnel
  • Maintenance management system
  • Capital-maintenance tradeoff capabilities
System Features
  • Life cycle analysis
  • Cost data
  • Performance data – impacts of maintenance and preservation
  • Cost and performance prediction
  • Future demand prediction
  • Regular review of treatment intervention strategies
  • Benefit/cost or optimization analysis