1.1 Background

1.1 Guidebook Background

Purpose and Scope

The purpose of this guidebook is to assist DOTs in advancing use of data and information systems for transportation asset management (TAM). It is intended to be used in conjunction with a companion digital tool – the TAM Data Assistant – providing a comprehensive way to benchmark agency practices and identify and evaluate improvements.

Guidebook Purpose

TAM is by nature data and analysis-intensive. Data (and information derived from data) about asset inventory, condition, performance, and related work activities are used to inform agency strategies for maintenance, rehabilitation and improvement. Data also inform allocation of increasingly scarce resources.

Most transportation agencies have asset management systems in place and use a variety of systems to plan and track maintenance activities and capital projects. However, they face challenges with integrating data across systems and across the asset life cycle. They also seek to capitalize on opportunities to adopt new, emerging tools and technologies for data collection and analysis.

This guidebook provides a structured approach that agencies can use to assess current practices in use of data and information for TAM. This approach can be applied in a comprehensive fashion; it can be targeted for a particular asset; or it can focus on a particular topic area – such as data collection or data integration.

A companion digital tool – the TAM Data Assistant – is available for conducting the assessment, identifying improvements, and evaluating candidate improvements. This guidebook is intended to be used initially to help agencies plan and organize an assessment. It also provides supplemental resources that can help agencies with each step of the process – understanding the context for each of the assessment elements, learning about and evaluating possible improvements, and planning an implementation strategy.

Guidebook Scope

The guidebook is structured around a data life-cycle framework. This life-cycle (illustrated in Figure 1-1) consists of five essential steps for making efficient and effective use of data and information for TAM. The data life-cycle approach was selected to reinforce the importance of anticipating how data will be used prior to collecting it. The data life-cycle can be viewed as a supply chain in which the finished product is a data-informed decision. Getting a quality product depends on sound practices for specifying data, collecting it, storing and integrating it and providing access to potential users, and having suitable analysis tools and processes in place.

Figure 1-1. Guidance Framework

Each step of the data life-cycle represents an assessment Area in the guidebook. An overview of each Area is described below; further detail is provided in Chapters 2 and 3.

For each Area, the guidebook provides Benchmarks and Candidate Improvements. The Benchmarks describe different levels of practice – representing a trajectory for advancement from a non-existent or minimal practice to an advanced practice. The Candidate Improvements describe initiatives that agencies can pursue to move from one benchmark level to the next.

The guidebook provides two types of supplemental resources to help agencies select and plan improvements.

Case Studies provide examples of implementation experience. Organizational Practice descriptions highlight approaches that can be taken to overcome the very real challenges of implementing data and information improvements.

Anticipated Uses

The guidebook is intended to be used to carry out a formal assessment and improvement planning effort. However, it can also be used as a resource for DOT’s that are not ready to pursue an assessment process but are interested in what they can do to improve their practices.

Formal Uses: Formal application of the guidance involves selecting a focus area, forming a team, using the companion tool to carry out the assessment, and then producing a plan of improvements.

Informal or Individual Uses: The guidebook can be used as a reference for individual agency managers or TAM practitioners to understand possible future directions for advancement, review case studies, and provide ideas for evaluating improvement strategies.

Intended Outcomes

Completing the full assessment process will result in:

  • A shared understanding of current agency practice – and a shared vision for how the agency wants to advance.
  • A list of candidate data and information system improvements that could be used to close the gap between current and target practice levels.
  • A prioritized list of improvements – created based on a systematic process of evaluating likely impact versus effort required; and implementation challenges.
Intended Audience

This guidebook is targeted at state DOT asset managers, business leads, system owners, and stewards interested in evaluating and improving how data and information systems are used within their TAM programs. While state DOTs are the primary intended audience for the guidance, it is also applicable to other transportation asset owners (such as transit agencies).

To fully realize the benefits of the assessment, other business, technical, and supporting functions should be involved in the process, including:

  • Field asset management staff,
  • Information technology managers,
  • Workforce, human resource, and organizational change management leads.
The TAM Data Assistant

A companion digital tool is available for agencies to use to conduct the assessment. This tool supports benchmarking of the agency current and desired state, improvement identification and evaluation, and results summary and communication.

While this guidebook contains all of the materials needed to carry out the assessment process, use of the TAM Data Assistant is strongly recommended as it will streamline workflow and provide summary materials useful in communicating and engaging with agency executive management or other decision-makers. A brief overview of the TAM Data Assistant functions is provided in Chapter 2.

Chapter 4 details TAM Data Assistant uses supporting improvement evaluation, results summary, and executive communication.

Appendix H provides uses of the TAM Data Assistant to facilitate the complete assessment process.

The Appendix I contains a quick reference guide that explains the functionality and use of the TAM Data Assistant in detail.

Relationship to Other Guidance

This guidebook provides a comprehensive perspective on data and information system use in TAM. However, there are other related assessment and guidance products available. These include:

This guidebook and companion tool complement these existing tools by providing an in-depth look specifically at how data and information systems are applied to TAM practice.

Technical Framework
Data Life-Cycle Area Overview
Specify and Standardize Data

Supports the understanding of the needs and full costs of asset inventory, condition and performance, treatment, and work history data. Also addresses the documentation of data meaning, derivation, and quality, and the establishment of governance structures and processes and stewardship roles and responsibilities.

Collect Data

Explores TAM related data collection processes, tools and technologies, and quality as delivered with respect to existing data standards.

Store, Integrate, and Access Data

Addresses data availability across the enterprise and the elimination of redundant and duplicative data. Specific asset life-cycle process areas are identified for data standardization and integration, as well as other data and process areas important to TAM decision-making.

Analyze Data

Examines decision-support tools, techniques, and practices that facilitate development of actionable information and insights supporting decision-making. Data exploration, reporting, visualization, and asset modeling are a focus within this Area.

Act Informed by Data

Covers data-informed TAM practices, exploring asset life-cycle management through resource allocation and prioritization, project planning, scoping, and design, and maintenance decision-making.

Guidebook Organization

This guidebook is organized to help agencies step through the process of preparing for an assessment, conducting an assessment, evaluating improvements, and planning for implementation.

The self-assessment and improvement identification materials are organized in a three-level hierarchy:

  • Areas – representing each phase of the data life cycle (e.g. data collection)
  • Sections – representing topics relevant to a data life cycle phase (e.g. asset inventory, condition and performance data collection)
  • Elements – representing items for benchmarking and improvement (e.g. asset inventory, condition an performance data quality)
Guidance Process Overview and Organization

The guidebook is organized into five chapters and several technical appendices.

Chapter 1 – Introduction: This chapter describes the purpose, scope and target audience for the guidebook and provides an overview of the assessment process.

Chapter 2 – Pre-Assessment Preparation: This chapter helps prepare an agency for conducting an assessment. It covers selecting a focus area, assigning a facilitator, and engaging the right participants. It also reviews the steps for conducting the assessment and selecting and evaluating improvements.

Chapter 3 – Self-Assessment and Improvement Identification: This chapter provides guidance and links to resources that can be used as participants step through the process of assessing current practice and selecting improvements. This content is organized around the five Areas representing data life cycle phases.

Chapter 4 – Evaluation and Summary: This chapter provides guidance that can be used as participants evaluate candidate improvements, set priorities, and develop materials for gaining executive support for improvements.

Chapter 5 – Implementation Support: This chapter describes additional resources that can be used to support implementation of data and information system improvements. These include case studies of DOT practice and general organizational practices (such as change management).