Establishing Enterprise-Wide Data Governance

Transcription

1 Establishing Enterprise-Wide Data Governance Dave Blackstone ODOT - Office of Technical Services Greg Yarbrough Data Transfer Solutions LLC.

2 ODOT s Definition of Data Governance (DG) What is it? Governance of data within ODOT Core foundation for how ODOT implements data management policy, standards, and procedures Continuous collaborative process requiring participation throughout agency Why? ODOT s planning and decisions impact Ohio s economy (multi-billion dollars) Citizen safety Data is highly valuable enterprise asset needing oversight

3 Data Governance Mission and Vision Mission Ensure ODOT creates and maintains reliable transportation data that is accurate, available, timely and usable for our People, Processes and Technology. Vision Data Governance (DG) will steward the standardization, coordination, and integration of existing and future applications, data sources, and reporting at ODOT.

4 Current State of Data Architecture

5 Why Is The Current State Problematic?

6 ODOT s Current State of Data Governance No DG process leading to: Inaccurate data Data redundancy Unavailable data Untimely data Absence of data standards Data integration difficulties Some aspects of DG are in place TAM Audit Group, GIS (TIMS) Standards, STP (Enterprise Architecture), DoIT Technical Requirements and BTRS ODOT needs coordinated, agency-wide DG process to improve effectiveness

7 Process Overview Define Maturity Measures Develop & Conduct General Survey Focus Group Meetings Follow-up Meetings With Data Owners Maturity Measure Scoring Consultant and Data Governance Steering Committee collaboratively developed 15 governance measures deemed to be critical for ODOT. NCHRP, URISA and other sources were used to develop the measures. Web-based survey delivered to a broad audience of data consumers, maintainers and data owners. Questions focused on maturity measures from a global perspective and not focused on specific data assets. On-site meetings held with data owners and consumers for each data asset. General survey results were presented for context and discussion was focused on maturity measures for each data asset. On-site meetings with Data Owners to discuss findings and fill in specific maturity measure gaps for each data asset. Additional meetings held with DoIT staff for feedback on backend systems and support. Three step process whereby Consultant provides initial scoring followed by editing by the Data Governance Committee and finalized with input from Data Owners. Gap Analysis and Recommendations Based on feedback from ODOT during all previous steps, gaps in data governance and opportunities to enhance data governance were identified. Recommendation developed as part of this report.

8 Data Governance What are the Data Governance measures? Data Quality Policy Organizational/Strategic Alignment Data Accessibility/Distribution Data Usability Systems Integration Privacy/Security Metadata/Documentation Performance (Risk) Management Service Delivery IT Collaboration Knowledge Management Data Awareness/Outreach Resource Allocation Tools & Analytics

9 Measure Considerations Data Quality Accuracy and integrity Timeliness Completeness Currency/Maintenance Confidentiality Metadata & Documentation Policy (Data Management) Data Standard Policies Standard Operating Procedures Organizational/Strategic Alignment Policy Alignment Roles & Responsibilities Stewardship & Accountability

10 Measure Considerations Data Accessibility/Distribution Data Distribution Ease of Access Data Usability Data Relevance Decision Support Ease of Use System Integration Integration with ODOT Systems LRS Integration

11 Measure Considerations Privacy/Security Data Backup & Recovery Data Protection Privacy & Personal Data Protection Metadata/Documentation Metadata Availability Relevance & Usability Metadata Updating Performance (Risk) Management Data Dependencies Internal Data Collaboration External Data Collaboration

12 Measure Considerations Service Delivery Responsiveness Resources Satisfaction DoIT Collaboration Responsiveness Business Alignment Processes Software/Hardware Knowledge Management Training/Cross-training Workflow Documentation Training Access

13 Measure Considerations Data Awareness/Outreach Data Awareness Outreach Efforts Resource Allocation Technology Funding Staffing Skillsets Tools and Analytics Data Collection Data Maintenance Reporting Analytics

14 General Survey Web-based Survey Captured General Data Management Perceptions Not focused on specific Data Assets Broad Audience (183 responses) Central Office All Districts Respondents from a variety of disciplines Executive Planning Engineering Administrative Technical (IT)

15 Focus Groups Face to Face Discussion Each Group Included Data Owners and Consumers from Related Multiple Business Units Planning & Engineering Construction DoIT Pre-Construction Local Programs District Representatives Executive Management Considered Primary and Secondary (Downstream) Users

16 Focus Groups - Things to Consider Do we have the right data to make good decisions and meet reporting requirements? What data do we need and why? Is our current data good enough? What level of accuracy, timeliness, completeness, and so forth is needed? Are we getting full value from the data we have? Can users locate, access, integrate and analyze it? Are we making the best use of our data collection and management resources? Are we being efficient about how we collect data?

17 Focus Groups - Things to Consider Are we managing the full life-cycle of the data? Is the data maintained, preserved, protected and archived in a useful way? Are we sharing data efficiently? Is data easily shared in useful formats? Is there sufficient communication among data producers and consumers? Are there systemic gaps? Consider documentation, skill sets, staff resources, technical resources, policies and processes. Are there specific areas where improvement is needed? Consider data availability, data quality, data quantity, usability, documentation, analytical tools, etc.

18 Data Owner Meetings Face-to-face meetings with designated owners of each data asset. Shared results of web survey and focus group meetings Captured information needed to fill gaps in Maturity Model Follow-up meetings to review and validate Maturity Model results.

19 Data Governance Maturity Model

20 How will ODOT create a Data Governance program? Taking Care Care of of What What We We Have. Have.

21 How Will We Accomplish? Multi-disciplinary business owners and stakeholders from ODOT Central Office and Districts

22 How Will We Accomplish?

23 New ODOT Data Governance Program Culture Change Impacting Nearly All

24 What We Hope to Achieve? Understand our Current State Identify where we would like to be in the next 3 years Establish DG oversight committee Establish a Chief Data Officer Develop and implement a true Data Warehouse/Data Lake, Central Repository Establish Policy Guided Framework for Governance

25 Data Governance Benefits Align to ODOT s Critical Success Factors People Provides timely, available data to improve employee efficiency, satisfaction and working environment System Conditions Delivers reliable, timely asset data (Tier 1 & ancillary) to better enable work plans (Cap & Maint) to improve asset condition and maintenance condition ratings Safety Integrates and standardizes data to improve analysis, reporting and decision making to reduce fatalities, serious injuries and crashes Capital & Maintenance Programs Facilitates data sharing and communication across jurisdictional boundaries for better decision making and collaboration to support capital & Maintenance investments

26 Next Steps 1. Finish the Maturity Assessment 2. Gain executive support 3. Contact other State DOTs to discuss best practices California, Colorado, Iowa, Louisiana, Minnesota, Nevada, New York, North Carolina, Virginia, Utah 4. Create DG framework for ODOT 5. Complete data discovery/analysis 6. Create recommendations 7. Plan initial tasks 8. Execute

27 Taking Care Care of of What What We We Have. Have. Questions?

28 Thank you! Dave Blackstone ODOT - Office of Technical Services Greg Yarbrough Data Transfer Solutions LLC.