CDOT Performance Data Business Plan - Cambridge Systematics

CDOT Performance Data Business Plan
Effective communication between the various communities of interest (COI)
regarding the data and associated application systems that are used to collect,
maintain, and report information;
Published definitions and standards for source data, metadata, and data used
in the data marts for creating reports from the various data systems; and
Use of a knowledge management system to document work process, data
dictionaries, data models, etc.
There also are many documented obstacles to implementing successful data
governance. They include:
Required culture change to adapt the organization;
Resistance to migration of data from silos to an enterprise management
system; and
Lack of funding or available resources.
State DOTs face many challenges to establishing formal data governance policy
and procedures. Data governance models for State DOTs are relatively new,
emerging in response to improved practices for collecting, analyzing, sharing
and disseminating data for the purposes of asset management, performance
reporting, resource allocation and decision-making.
The following definitions were developed previously by Cambridge Systematics
for inclusion in Target-Setting Methods and Data Management to Support
Performance-Based Resource Allocation by Transportation Agencies (NCHRP Report
666).
Data management is defined as the development, execution, and oversight of
architectures, policies, practices, and procedures to manage the information life
cycle needs of an enterprise in an effective manner as it pertains to data
collection, storage, security, data inventory, analysis, quality control, reporting,
and visualization.
Data governance is defined as the execution and enforcement of authority over
the management of data assets and the performance of data functions.
Organizations have different strategies for their approach for data governance.
Data governance defines how organizations coordinate the strategic
management of their data and information resources. This includes establishing
clear roles, responsibilities, and authorities through various committees and
works structures. These committees may range from an executive steering
group, operation unit information systems strategy groups, IT strategy groups,
application or technical management groups, and service management groups.
The data governance steers the organization and defines the role that top
management plays in information management planning, ensuring a fit between
the information management and the strategy of the organization, improving
communication between top management and middle management, and
influencing user attitudes about information management practices.
4-2 Cambridge Systematics, Inc.