CDOT Performance Data Business Plan - Cambridge Systematics

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.