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Effective Safety Data Governance

Learn about safety data governance practices, future viewpoints, NCHRP guidelines, steps to establish programs, roles, responsibilities, and stakeholder involvement. Understand how to develop data principles, governance models, and documentation for effective safety data management. Explore the benefits and challenges of data governance implementation in transportation agencies. Discover key assessment elements, dimensions, and maturity levels of data governance for sustainable business needs.

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Effective Safety Data Governance

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  1. Effective Safety Data Governance ATSIP Traffic Records Forum New Orleans, LA August 7, 2017

  2. Presentation Will Cover … What is Safety Data Governance Current Practices and Issues Future View

  3. Data Management The processes and activities in place to develop, implement and enforce policies and practices for protecting and enhancing the efficiency, value, and effectiveness of data and information NCHRP 814: Data to Support Transportation Agency Business Needs: A Self-Assessment Guide

  4. Data Governance The accountability for the management of an organization’s data assets to achieve its business purposes and compliance with any relevant legislation, regulation, and business practice. NCHRP 814: Data to Support Transportation Agency Business Needs: A Self-Assessment Guide

  5. Steps to Establish a Governance Program Develop Data Principles Develop a Governance Model Establish roles and responsibilities for governance Develop IT project governance Develop governance documentation Guide for State DOT Safety Data Business Planning: FHWA Safety Program (Preliminary, under development by Cambridge Systematics)

  6. AASHTO Data Principles Valuable (data is an asset) Available (open, accessible and shared) Reliable (quality sufficient for needs) Authorized (secure and meets standards) Clear (consistent and understandable) Efficient (not duplicated) Accountable (data utility for decisions)

  7. Governance Model Organizational framework Executive involvement Fit with existing processes / culture Fit with other ongoing data activities (asset management, program development, performance measurement) Fit with other IS and IT projects Guide for State DOT Safety Data Business Planning: FHWA Safety Program (Preliminary, under development by Cambridge Systematics)

  8. Roles and Responsibilities Data Governance Board/Council, Other Data stewards (data collection and distribution) Data business owners (e.g. safety decisions) Data custodians (Tech/IT staff) Working groups (business rules/processes) Guide for State DOT Safety Data Business Planning: FHWA Safety Program (Preliminary, under development by Cambridge Systematics)

  9. Safety Data Governance Stakeholders Data collectors/managers Traffic safety engineers Safety program managers pavement/bridge management engineers Law enforcement Local agencies/MPOs Guide for State DOT Safety Data Business Planning: FHWA Safety Program (Preliminary, under development by Cambridge Systematics)

  10. NCHRP Synthesis 508: Data Management and Governance Practices 43 State DOTs, 19 Local Agencies Data Governance Council (19% Yes, 44% No) Data Integration (Most - Roadway with Pavement, Bridge, Traffic, Crash) NCHRP Synthesis 508: Data Management and Governance Practices

  11. Existing State DOT Data Stewards (>85%) Pavement inventory and condition HPMS Roadway inventory Bridge inventory Crash Traffic monitoring NCHRP Synthesis 508: Data Management and Governance Practices

  12. Early Benefits of Implementing Data Governance Improved accountability for high-quality and reliable data Ensuring data integration/accessibility using common LRS Engaging business areas in their data vs. addressing as an Information Technology issue NCHRP Synthesis 508: Data Management and Governance Practices

  13. Synthesis 508 Data Governance Conclusions Bottom up approach more common by business process area (e.g. safety, asset management) Major factors limiting progress: - Lack of staffing - Other issues more pressing - Lack of resources High Benefit Data Integration Challenges – Roadway with Other Assets, Environment, Travel Modeling, Construction Projects, Traffic Monitoring Half of state DOTs have data user feedback mechanisms NCHRP Synthesis 508: Data Management and Governance Practices

  14. NCHRP 814: Data to Support Transportation Agency Business Needs: A Self-Assessment Guide Enterprise Level Business process area (e.g. Safety) NCHRP 814: Data to Support Transportation Agency Business Needs: A Self-Assessment Guide

  15. Key Elements of Assessment Data Availability Data Quality Data Usability NCHRP 814: Data to Support Transportation Agency Business Needs: A Self-Assessment Guide

  16. Dimensions of Assessment Data Strategy and Governance Data Architecture and Integration Life Cycle Data Management Data Collaboration Data Quality Management NCHRP 814: Data to Support Transportation Agency Business Needs: A Self-Assessment Guide

  17. Data Strategy and Governance Assessment Elements Strategy and Direction Roles and Accountability Policies and Processes (Agency-wide) Data Asset Inventory and Value Relationship with Customers (program specific) Data Management and Sustainability NCHRP 814: Data to Support Transportation Agency Business Needs: A Self-Assessment Guide

  18. Maturity Levels Initial: Ad hoc, event driven, led by individuals Developing: pilot initiatives Defined: documented processes, not stable/socialized Functioning: implemented processes, operating and adding value Sustained: evaluated and improved processes, sustained over time NCHRP 814: Data to Support Transportation Agency Business Needs: A Self-Assessment Guide

  19. DOT Business Process Areas Executive Annual/Multi Year Program Development Safety Asset Inventory Data Management Construction/Operations Internal/External Communications Intermodal Coordination Policy Analysis Project Design / Context Sensitive Solutions Cartography / Mapping Environmental Analysis

  20. NCHRP 829 Leadership Guide for Strategic Information Management for State DOTs Information is an Asset Maximize value Maximize efficiency of information management and use Improve organizational readiness for new information sources and new methods for analysis and visualization Need an organizational vision NCHRP 829: Leadership Guide for Strategic Information Management for State DOTs

  21. Major Challenges Fragmented Information Storage Ambiguous information management responsibilities Lack of information governance and process standardization Human factors – changing workforce Legacy systems NCHRP 829: Leadership Guide for Strategic Information Management for State DOTs

  22. Data Sources Business Processes (Silos) Enterprise Data External – Public and Private Data! Data! Data! I can’t make bricks without clay! - Sir Arthur Conan Doyle

  23. Lean Framework Strategy and Direction Roles and Accountability Policies and Processes (Agency-wide) Data Asset Inventory and Value Relationship with Customers (program specific) Data Management and Sustainability NCHRP 829: Leadership Guide for Strategic Information Management for State DOTs

  24. Data, Information, Knowledge Justified beliefs – basis for taking action Changing our standard will save money and won’t impact safety. Knowledge Relevant, processed, contextualized facts No correlation between rut depth and crashes for less than 1” rut depth Information Facts, observations Rut depth Data

  25. Knowledge is Complicated “…knowledge is not a result merely of filtering or algorithms…We get to knowledge — especially “actionable” knowledge — by having desires and curiosity, through plotting and play, by being wrong more often than right, by talking with others and forming social bonds, by applying methods and then backing away from them, by calculation and serendipity, by rationality and intuition, by institutional processes and social roles.” • David Weinberger, “The Problem with the Data-Information-Knowledge Hierarchy, Harvard Business Review (2010)

  26. Building Knowledge

  27. Managing Info and Knowledge

  28. Big Data vs. Business Intelligence Big data – volume, velocity, variety Big data – inductive statistics, reveal relationships, predict outcomes BI – descriptive statistics, measure things, reveal trends Safety Engineers and Data Scientists The alchemists in their search for gold discovered many other things of greater value. - Arthur Schopenhauer, German Philosopher

  29. Data Governance is Important DOT – Information Organization Expanding data sources Increasing access and use expectations Business intelligence and analytics – big data Institutionalize to fit the agency Need vision and leadership

  30. Selected Resources NCHRP Report 666 - Target Setting and Data Management NCHRP Report 754 – Management of Transportation Information NCHRP Report 813 – Guide to Agency-Wide KM NCHRP Report 800 – Successful Practices for GIS and TAM NCHRP Report 814 – Data Self-Assessment Guide NCHRP Report 829 – Executive Guide to Strategic Information Management NCHRP Project 08-90 - Asset Management Gap Analysis Tool NCHRP Synthesis 508 – Data Management and Governance Practices

  31. James P. Hall Hanson Professional Services Faculty Scholar Associate Professor Management Information Systems University of Illinois at Springfield One University Plaza Springfield, IL 62703 Phone: 217-206-7860 Email: jhall1@uis.edu

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