Office of Operations
21st Century Operations Using 21st Century Technologies
Table of Contents

Operation Performance Management Primer: From Performance Measures to Performance Management

Chapter 4. Operations Performance Measures and Management in Decisionmaking

How Operations Performance Measures and Management Enhances Transportation Systems Management and Operations Planning and Programming Decisions

Performance management provides a means to efficient investment of Federal transportation funds by increasing accountability and transparency, and improving project decisionmaking through performance-based planning and programming. States have been developing performance measures and implementing performance management for several years, often prior to Federal TPM requirements. Consequently, consistency at the national level is essential as a subsequent step.

The intent of TSMO is effective and cost-efficient solutions in lieu of major capital investments. TSMO strategies aim to better leverage capacity limitations due to congestion, incidents, construction, weather, poor signalization, and other factors. TSMO improvements are based on measuring performance on a regular basis, tracking performance changes over time, and managing the transportation system to achieve desired results.

OPMM can enhance TSMO though improving communications between decisionmakers, stakeholders and the traveling public. Following steps can be used as a part of OPMM to advance TSMO:32

  • Using a performance-based approach to provide users with a high quality and reliable highway system.
  • Helping to extend the performance life of new facilities and support the agency’s overall mission to manage and operate the transportation system.
  • Implementing a comprehensive system level performance measurement program to monitor progress toward mobility and reliability targets.
  • Developing a data supported system for resources in need of performance reporting.

FHWA and the Federal Transit Administration promote planning for TSMO among MPOs, State and local State DOTs, transit agencies, and other stakeholder organizations through guidebooks, case studies, workshops, courses, and webinars. A few of their previous works are listed below:

  • Planning for TSMO within Corridors—A Desk Reference.33
  • Advancing TSMO through Scenario Planning.34
  • TSMO in Action.35
  • Maryland TSMO Strategic Implementation Plan.36
  • Developing and Sustaining a TSMO Mission for Your Organization—A Primer For Program Planning.37

TSMO program planning is a living process which should reflect all undertaking agencies plans. TSMO primer for program planning articulated that there is no single method for agencies to advance TSMO, and recommended several key elements and principles that should be undertaken by agencies in order to develop a comprehensive plan.38 TSMO program planning three key elements are:

  1. Strategic elements: The main focus of this step is to develop the business case for TSMO vision and program mission. Identify performance measures that link to TSMO goals.
  2. Programmatic elements: This step addresses issues such as leadership support, organizational structure, career development plans for TSMO staff, and strategies to promote TSMO culture within the agency and among partners.
  3. Tactical elements: Identifying prioritized services, activities, and projects.39

Integrating Operations Performance Measures and Management Into Agency Processes

Agencywide Performance Reporting

Performance measures can be defined at several different levels for TSMO program management. These include:

  • Inputs: resources put into an activity (e.g., staff-hours associated with incident management, number of ramp meters).
  • Activities or Outputs (e.g., number of signal controllers upgraded).
  • Outcomes (e.g., travel time, congestion level). Outcome measures are used to monitor progress toward goals and objectives.
  • Efficiencies (e.g., money spent per reduction in incident duration). Efficiency measures are used to evaluate the effectiveness of overall transportation programs.

Performance measures for OPMM should be developed for the input, output, and outcome levels. Further, they should be vertically integrated. That is, a fully integrated set of performance measures should be constructed, where higher-level performance measures (outcomes) are directly influenced by changes in lower-level measures. In the general literature on performance measurement, this is described as a program logic model.40

Program logic models visually map the cause-effect relationships that exist between the inputs, activities, outputs, and outcomes produced by their programs or projects, for specific stakeholders. Program logic models also provide a framework for assessing the impact achieved by the organization’s application of resources to its programs. These models are intended for organizations whose impact is social change, such as reducing health problems from smoking, reducing water consumption in times of drought, increasing use of sunscreen to minimize skin cancer incidence, or reducing homelessness.

Figure 11 shows how this model can be adapted for traffic incident management. The distinction between “outputs” and “outcomes” is that outcomes are experienced directly by the user of the highway, while outputs are related to how incident management activities perform (which in turn influence outcomes). Note that measures related to daily operations activities feed into a broader context, and are indicated by broader planning vision, goals, and objectives. In addition, as one goes higher in the structure, the influence of other factors outside of incident management affect congestion and travel time reliability.

A program logic model as applied to traffic incident management.

Figure 11. Diagram. Program logic model applied to traffic incident management.
(Source: Federal Highway Administration.)

Performance-Based Planning and Programming

PBPD refers to the application of performance management principles within the planning and programming processes of transportation agencies to achieve desired performance outcomes. PBPD is based on establishing performance goals and continuously measuring progress toward those goals with performance measures. PBPD is data-driven and uses data to support long-range and short-range investment decisionmaking.

OPMM uses a variety of performance measures for many purposes. While some measures may be dictated by legislative or regulatory mandates, it is useful to also select measures that provide internal or detailed operational and planning data beyond that normally needed for reporting purposes. Understanding the range of needs and uses is important in the process of identifying the measures. For example, already deployed TSMO strategies can be “tweaked” in the short term to address measured changes in performance. In the long term, different TSMO strategies can be applied in response to changing performance levels.

PBPD is meant to affect a range of activities and products related to planning and programming, among them are:

  • LRTPs.
  • Federally required plans and processes such as Strategic Highway Safety Plans, Congestion Management Plans (CMP), and Transportation Asset Management Plans.
  • Transportation Improvement Programs.
  • STIPs.

OPMM has important roles to play in the production of most of these planning and programming products. OPMM performance measures on mobility inform the development of a broad range of strategies that go into these products. Additionally, the identification of TSMO strategies and their potential impact need to be included in these broader scope documents to ensure that TSMO is viewed on equal footing with other forms of improvements.

For example, CMPs are “…systematic and regionally accepted approach for managing congestion that provides accurate, up-to-date information on transportation system performance and assesses alternative strategies for congestion management that meet State and local needs.”41 OPMM performance measures are primarily related to congestion and are thus the starting point for CMP development. Moreover, the CMP is an ideal place to plan for TSMO deployment along with other congestion mitigation strategies.

Performance-Based Practical Design

Performance-Based Practical Design (PBPD) is based on modifying a traditional design approach to tailor the design of an improvement so that its performance meets both project and system objectives. PBPD uses data to understand current performance and deficiencies and performance analysis tools to predict the impact of proposed improvements. It considers both short- and long-term project and system goals.

Whereas Planning for Operations is performed at the beginning of the project development process, PBPD is done as part of the design process. Just as with Planning for Operations, OPMM can supply both the data and performance analysis tools to assess the impacts of operations strategies during the design process. Ideally, operations strategies have been previously identified during planning steps, but even if they are not, they can still be considered at the design stage.

For example, the data used to develop OPMM performance measures—especially travel time, weather, and incident data—can be used to document current performance and to influence design decisions. These data may indicate problems that would otherwise go undetected using only the demand and geometric data that are typically used for design. A further example of how the operations strategy of Active Traffic Management can be considered during the PBPD process has been prepared by the FHWA.42 More detail on the OPMM data sources and performance analysis tools appear later in this Primer.

Operations Performance Measures and Management Support of Freight Performance Management and Planning

Just as OPMM is the enabling mechanism for TSMO Planning and plays a role in the larger planning environment, it also supports freight performance management and planning. One of the key areas of support is in the required reporting of freight bottlenecks. As part of the Federally mandated reporting, State DOTs must identify and describe the ways in which they are addressing congestion at freight bottlenecks.43 The FHWA Truck Freight Bottleneck Reporting Guidebook recommends the following process for identifying bottlenecks, which is the starting point for addressing freight issues in TPM:44

  • Gather data for bottleneck identification and analysis, including travel times, truck volumes, traffic management center operational data, and truck restriction information from roadway inventories.
  • Screen for truck freight bottlenecks using a data-driven process for more detailed site-specific analysis and verification.
  • Validate truck freight bottleneck list using of comparable data, expert validation, stakeholder input, or additional research.
  • Evaluate the causes of bottlenecks based upon analysis of roadway characteristics, field assessment, and discussions with affected road users.
  • Prioritize the list of freight truck bottlenecks to focus freight planning efforts on the highest and best use of limited resources.

Bottleneck identification is part of the OPMM process of monitoring current mobility conditions. In urban areas, the worst bottlenecks are typically related to geometric and capacity deficiencies apparent during peak periods. However, while trucks must also navigate these types of bottlenecks, trucks also are subject to bottlenecks created by policy restrictions, such as time of day and routing restrictions. Freight bottlenecks are generally categorized as follows:

  • Congestion Bottlenecks—Bottlenecks characterized by significant reductions in average truck speeds can be either recurrent or nonrecurrent.
    • Recurrent congestion bottlenecks—Recurrent congestion occurs when traffic over-demand at peak periods routinely exceeds a road’s capacity, defined primarily by the number of lanes and the travel speed for which they were designed.
    • Nonrecurrent congestion bottlenecks—These bottlenecks occur sporadically when out-of-the-ordinary incidents impede road capacity, add travel demand or, in extreme cases, force re-routing or a complete halt to all travel, such as, crashes, special events, work zones, or severe weather.
  • Truck Restriction Bottlenecks—Truck-specific bottlenecks attributed to infrastructure restrictions that uniquely impact trucks and may require trucks to take longer routes, carry smaller loads or move at different times of day, such as substandard vertical or horizontal bridge clearance, weight restrictions, steep grades, hazardous materials restrictions, or delays at port gates, intermodal rail yards, border crossings, and weight stations.

OPMM has a direct effect on freight bottleneck planning and management. The same data that is used to monitor congestion-based performance for general traffic can be used for truck-specific bottleneck performance, with the inclusion of truck volumes. Moreover, solutions to freight bottlenecks can be integrated into TSMO solutions. Such a framework will lead to a coordinated and comprehensive State freight plan.

32 Maryland Department of Transportation (2016). TSMO Strategic Transportation Plan. Annapolis, MD. Last accessed April 7, 2022. [Return to note 32]

33 Bauer, J., Platman, D., Grant, M., and Smith, M., Bauer, J. Planning for Transportation Systems Management and Operations within Corridors—A Desk Reference. Report No. FHWA‑HOP‑16‑037, Federal Highway Administration, Washington, D.C. Last accessed December 8, 2022. [Return to note 33]

34 Bauer, J., Ange, K., Twaddell, H. (2015). Advancing Transportation Systems Management and Operations through Scenario Planning. Report No. FHWA‑HOP‑16‑016, Federal Highway Administration, Washington, D.C. Last accessed April 7, 2022. [Return to note 34]

35 Clark, J., et al. (2017). Transportation Systems Management and Operations in Action. Report No. FHWA‑HOP‑17‑025, Federal Highway Administration, Washington, D.C. Last accessed April 7, 2022. [Return to note 35]

36 Maryland Department of Transportation. (2016). Strategic Implementation Plan. Annapolis, MD. Last accessed April 7, 2022. [Return to note 36]

37 Grant, M. Noyes, P., Oluyede, Bauer, J., and Edelman, M. (2017). Developing and Sustaining a Transportation Systems Management and Operations Mission for Your Organization—A Primer for Program Planning. Report No. FHWA‑HOP‑17‑017, Federal Highway Administration, Washington, D.C. Last accessed April 7, 2022. [Return to note 37]

38 Grant, M. Noyes, P., Oluyede, Bauer, J., and Edelman, M. (2017). Developing and Sustaining a Transportation Systems Management and Operations Mission for Your Organization—A Primer for Program Planning. Report No. FHWA‑HOP‑17‑017, Federal Highway Administration, Washington, D.C. Last accessed April 7, 2022. [Return to note 38]

39 Grant, M. Noyes, P., Oluyede, Bauer, J., and Edelman, M. (2017). Developing and Sustaining a Transportation Systems Management and Operations Mission for Your Organization—A Primer for Program Planning. Report No. FHWA‑HOP‑17‑017, Federal Highway Administration, Washington, D.C. Last accessed April 7, 2022. [Return to note 39]

40 Besharov, Douglas J., Baehler, Karen J., and Klerman, Jacob Alex. (2017). Improving Public Services: International Experiences in Using Evaluation Tools to Measure Program Performance. ISBN-13: 9780190646059. [Return to note 40]

41 Federal Highway Administration. (no date). “Organizing and Planning for Operations.” Washington, D.C. Last accessed April 7, 2022. [Return to note 41]

42 Federal Highway Administration. (2022). “Demonstrating Performance-Based Practical Design through Analysis of Active Traffic Management.” Washington, D.C. Last accessed April 7, 2022. [Return to note 42]

43 23 CFR 490.609. [Return to note 43]

44 Federal Highway Administration. (2018). Truck Freight Bottleneck Reporting Guidebook. Washington, D.C. Last accessed April 7, 2022. [Return to note 44]