Chapter 7 Summary
Information and Systems
This chapter of the guide describes how to determine TAMP data needs, the processes for ensuring it is accurate and current for asset decision-making, and systems for data management, analysis and reporting.
What’s Important
Deciding what data to collect and manage for asset management involves identifying information needs, estimating the full costs of obtaining and managing the data to meet those needs, and then determining whether the cost is justified. Once the desired data are identified, agencies must plan for the data collection process by coordinating with stakeholders, specifying exactly what data will be collected, and training staff to collect the data. As data are collected and checked through a quality assurance and control process, it becomes essential to have regular processes for updating the data. This can be accomplished through periodic data collection cycles, or through updating as part of asset project development and maintenance management processes.
How the Guide Can Help
Just as agencies do not have unlimited resources to repair and replace their assets, there are also limitations on resources for data collection and management. The guide presents the following questions to help identify asset management data needs:
- What decisions do we need to make?
- What questions do we need to answer that require asset data?
- What specific data items are required or desired?
- What value will each data item provide?
- What level of detail is required in the data?
- What level of accuracy is needed?
- How often should data be updated?
The Guide describes how integrating information across different systems can enable agencies to maintain an asset inventory in a single source system of record and share it with other systems. Integrating data for TAM should be approached systematically to ensure agencies achieve a solution that meets their needs and is ultimately sustainable. In the short term, agencies can integrate the information they already have. In the longer term, agencies can modify and consolidate their information systems.
Spotlight on
TAM Plans and Policies
Data governance and management practices are essential to achieve reliable, consistent, integrated and accessible data that is of value for decision-making. Data management includes activities such as data quality management, documentation, metadata management, security and access controls, data integration, and archiving. Data governance, is a policy making and oversight function for data management. Implementing data governance involves forming and chartering decision making bodies, defining roles and responsibilities, establishing policies that set expectations for behavior, and setting up standard processes for things like approving data standards, resolving data issues, and acquiring new types of data. Data stewardship refers to established responsibilities and accountabilities for managing data. Data stewardship can be viewed as the way to operationalize data governance policies, processes and standards.
Data governance is generally implemented in a hierarchical fashion, with an executive body at the top, a data council or board in the middle, and several more focused groups oriented around specific systems, business processes, organizational units or functions. It is best to take an incremental approach to start, beginning with a few high impact areas that are aligned with what the agency is trying to achieve.