CDOT Performance Data Business Plan - Cambridge Systematics

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CDOT Performance Data Business Plan prepare HSIP projects for the traffic and safety engineers; and c) for the executive management, investment in an enterprise Geographic Information System (GIS) deployment may lead to the ROI for improved tradeoff analysis on project selection by visualizing the crash history, traffic, and pavement condition. A data governance framework, implemented on an enterprise level, supports ROI by providing a means of monitoring and tracking progress of various business programs for executives as well as data stewards, and stakeholders and users of the source data. Data governance provides methods, tools, and processes for: Traceability – aligning data programs with the agency’s business needs. Establishing data area communities of interest and working groups that examine needs in common areas and on a regular basis is essential. Performance Measures – should be reflective of the business needs identified in the traceability exercise. Risk Assessment – requires the agency to assess 1) how much data is needed; 2) how accurate should the data be; 3) what should the refresh rate of the data be, 4) who should have access to the data, and many other questions which help to assess the risks associated with a particular data program. Value of Data Programs – needs to be demonstrated to users and those who authorize investments in the data programs. This can be done effectively through the use of visualization tools, use of enterprise GIS systems, collecting data once and using it for many purposes, and demonstrated improvements in business operations through the use of quality, accurate, timely, easily accessible data, and information. Knowledge Management – must become part of the data governance framework in order to ensure that lessons learned and experiences pertaining to business operations within the organization are not lost. This will help to increase the ROI for time and resources committed to support of data programs. Institutional challenges may include: centralized policy-making, and decentralized execution of those policies; limited appreciation by decision-makers of the role of data systems in supporting business operations; and lack of formal policies and standards which guide the collection, processing, and use of data within the organization. It is particularly critical to have standardized policies and procedures for management of data and information when that information is the foundation of performance measurement and target setting programs for an agency. A data management program is used to coordinate the establishment and enforcement of data policies and standards for the organization. One of the ways to address these and other data-related needs is through the establishment of a structured data management program and data governance framework. Data management and data governance can help the agency to prioritize the most critical data needs and identify the resources available to address those needs in a timely manner.” Timeline Figure 4.3 provides a suggested timeline for the activities described above. 4-20 Cambridge Systematics, Inc.
CDOT Performance Data Business Plan Figure 4.3 Timeline Colorado DOT Data Governance Recommendations TIMELINE Month PRIORITY TASK & RESPONSIBLE GROUP 1 2 3 4 5 6 7 8 9 10 11 12 1 Create a Formal Data Governance Structure Data Governance Oversight Committee Data Governance Working Group 2 Develop a Data Governance Charter DG Committee DG Working Group 3 Complete a Data Inventory/Assessment Data Assessment Group 4 Develop and Adopt a Data Governance Procedure DG Working Group 5 Perform a Risk Assessment of Data Programs Risk Assessment Group 6 Implement Ongoing Data Management and Governance at CDOT Task Duration Data Governance Oversight Committee Meeting Cambridge Systematics, Inc. 4-21
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