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I-55 CHAPTER 4 Data Stewardship and Management Quality data are the foundation of performance manage- process to develop targets is, in many cases, based on historical ment. Effective decision-making in each element of the per- trends. It is often challenging to develop the most-effective formance management framework requires that data be targets for assessing how well a program is performing, and collected, cleaned, accessed, analyzed, and displayed. The orga- using past performance is a good basis as a starting point. nizational functions that produce these requirements are called More research is needed to investigate the analytical tools data management systems. There are two key dimensions to that are available for developing targets that most effectively creating and sustaining these systems. The two areas are equally measure program performance in a specific business area. important and must be synchronized within an organization to Establishing targets and developing data programs both rely ensure the generation and use of accurate, timely, and appro- on one basic component, data. priate data. The first area centers on the technical challenges Data must be collected, processed, and distributed through associated with data systems, including development and main- a means accessible to decision-makers at all levels of an organi- tenance of hardware and software, and the specifications for zation. Data are the basic pieces of information which when data collection, analysis, archiving, and reporting. The second processed through a system are available for analysis. The core area focuses on the institutional issues associated with data data pieces transform into information and decision-makers stewardship and data governance. Attention to both of these then use this information to manage business areas across the areas is required to assure solid data management systems. organization. In order for data to effectively meet the needs of Research for this project included an investigation of the the organization, it should be assessed in terms of accessibil- ways data management systems and organizational units within ity, accuracy, completeness, credibility, timeliness, and asso- a DOT are used to integrate data for purposes of ensuring the ciated risks. A data risk assessment and management plan is use of accurate, timely, high-quality data for decision-making often used to identify potential and known risks, assign purposes. The research focused on both technical and institu- persons and offices responsible for handling the risks, and for tional solutions and best practices. This section summarizes the developing risk mitigation plans. Using a risk management findings of the case studies in Volume III and includes many plan strengthens the overall data management program within specific and relevant examples to demonstrate how data pro- the organization. More information on the assessment process grams are supporting decision-making in many private and and data management is discussed in the following sections of public sector agencies. this report. Within any organization, data serves as the critical link between business areas of the organization. In a DOT, these 4.1 Introduction areas often include operations, planning, and production. The term data program in this report refers to specific data Typical office functions within Planning include long-range systems that support a business area of the organization. The planning, policy planning, and traffic data collection. Oper- "program" usually includes the functions of data collection, ations often include traffic engineering, safety, and mainte- analysis, and reporting. In the case of a DOT, some examples nance functions. Production refers to construction within a of these programs include traffic, roadway inventory, safety, DOT. There are some similarities and differences in the types and pavement data. of data which are used to support each of these areas. Oper- In many organizations, including some DOTs, targets ations, planning, and production functions often also rely on are used to measure how well programs are performing. The Human Resource type data, including available staffing for