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Performance Measures for Freight Transportation (2011)

Chapter: Chapter 4 - Freight Performance Measures

« Previous: Chapter 3 - Performance Measurement Experience in the Public Sector
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Suggested Citation:"Chapter 4 - Freight Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2011. Performance Measures for Freight Transportation. Washington, DC: The National Academies Press. doi: 10.17226/14520.
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Suggested Citation:"Chapter 4 - Freight Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2011. Performance Measures for Freight Transportation. Washington, DC: The National Academies Press. doi: 10.17226/14520.
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Page 39
Suggested Citation:"Chapter 4 - Freight Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2011. Performance Measures for Freight Transportation. Washington, DC: The National Academies Press. doi: 10.17226/14520.
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Page 39
Page 40
Suggested Citation:"Chapter 4 - Freight Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2011. Performance Measures for Freight Transportation. Washington, DC: The National Academies Press. doi: 10.17226/14520.
×
Page 40
Page 41
Suggested Citation:"Chapter 4 - Freight Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2011. Performance Measures for Freight Transportation. Washington, DC: The National Academies Press. doi: 10.17226/14520.
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35 c h a p t e r 4 Freight Performance Measures Whereas Chapter 3 found relatively little use of freight per- formance measures by state DOTs, this chapter documents that a significant amount of freight system performance information is available from other sources. Much of this information exists as data within federal databases, as reports to federal regulatory agencies, and as published reports by private-sector companies such as railroads. A primary finding is that freight performance measure- ment is challenged both by an abundance of data and by a lack of complete data for many important freight system per- formance functions. Sorting and selecting from the volumi- nous available data sources is one daunting challenge. Clos- ing data gaps is another. The following section summarizes the performance infor- mation that is available. More detail is provided in Appendi- ces C and D. Trucking Data For the trucking mode, data from which performance measures could be derived are extensive. The Freight Analy- sis Framework synthesizes several databases to produce truck volume data nationally and by state.1 The Fatality Analysis Reporting System includes statistics and a data base query tool for highway crashes, including those involving trucks.2 Further drilling into performance of truck safety is possible through the Federal Motor Carrier Safety Administration (FMCSA) query tools that allow analysis of the safety records and inspection histories of individual motor carriers.3 FHWA is partnering with ATRI to use global positioning system (GPS) data from hundreds of thousands of trucks to mea- sure the speed and reliability of truck movements on the Interstate Highway System (IHS).4 USDOT’s Pipeline and Hazardous Materials Safety Administration maintains data- bases of hazardous materials releases5 for highway, air, water, and rail modes. The American Trucking Associations’ (ATA) Motor Carrier Annual Report lists the key elements of a cost- per-mile calculation for trucking. The ATA’s U.S. Freight Transportation Forecast tracks trends and forecasts in manu- facturing, construction, agricultural commodities, mining, and non-oil merchandise imports that affect truck freight volumes. ATA’s Trucking Trends report provides information regarding trucking company commodity flows, the number of company failures, tonnage and revenue growth, revenue per mile, and trucking producer price indices.6 From the available data, performance measures can be produced annually for categories such as the number and severity of truck crashes, volumes of freight shipped, general trends of trucking costs, and periodic measures of travel time and travel reliability on the IHS. Real-time operation perfor- mance information is much less available across the network. Also, because trucking occurs disproportionately upon the higher functional classes of roadways, the condition data regarding pavement and bridge conditions can be used to measure the relative condition of the functional classes that carry the majority of freight. Rail Data Although largely deregulated, the U.S. railroads still pro- duce significant volumes of performance information to the FRA, to the Surface Transportation Board (STB), and to indi- vidual state regulatory commissions. More than 1,500 catego- ries of statistics are reported for each of the Class I railroads in the Statistics of Class I Freight Railroads report required by the STB.7 These data include uniform reporting of income, expenses, investments in track, equipment investments, and depreciation by various categories. The Federal Railroad Administration Office of Safety Analysis provides search and query tools to conduct analyses of railroad crashes.8 The query tools link to federal crash databases that allow for analysis of crashes by railroads, state, crash types, and

36 localities. Links to individual crash reports are provided. The Association of American Railroads (AAR) produces its own extensive website of performance data, background papers, and policy analyses.9 These performance data address rail- road cost indices that track the inputs to railroad pricing, the speed of trains and dwell time in yards, volumes of freight shipped, and various other statistics of railroad employment, safety, efficiency, and performance. The Class I railroads are all publicly traded companies. As a result, their annual filings with the Securities and Exchange Commission include volu- minous financial performance information. From this significant volume of data, it is possible to report important aspects of rail freight system condition and perfor- mance, including average railroad operating speeds, general rail freight prices, and the magnitude of reinvestment by the railroads into system capital, and to measure the safety trends of U.S. railroads. Ports and Waterways Data Data regarding port volumes and the quantity and type of cargo imports and exports are available to generate some performance trends for U.S. ports. However, the Maritime Administration (MARAD) reported to Congress that it was unable to measure the performance of ports because of a lack of common metrics, a lack of a performance reporting process, and a lack of definitions as to how ports should be measured in terms of performance, preparedness of national emergencies, or for efficiency.10 Condition statistics are produced by the U.S. Army Corps of Engineers (USACE) for the maritime transportation sys- tem of inland waterways, locks, and dams and for the tonnage they accommodate each year. Highway Condition Data Highway condition data are mature and abundant, but highway performance data regarding travel speeds and reli- ability are less available. The FHWA’s National Bridge Inven- tory records current and past conditions of bridges for all states, Washington, D.C., and Puerto Rico. The FHWA’s High- way Performance and Monitoring System (HPMS) tracks pavement conditions and estimated congestion levels on the highway network. It also makes planning-level estimates of levels of service. Freight Externality Data One of the more robust areas for freight system measure- ment is in the area of externalities. The data regarding exter- nalities appear to be among the most comprehensive, well- defined, and granular of the freight data. Data systems exist for highway emissions, hazardous material releases, and accidents involving trucks, railroads, and air freight carriers. The Clean Air Act Amendments of 1990 created the current air quality “conformity” process. Under that process, transportation emission budgets, which are like targets, are established through a cooperative process involving the U.S. Environmental Protection Agency (EPA), state environmental agencies, state transportation agencies, and metropolitan planning organizations (MPOs). Public involvement is included. The emission budgets serve as a ceiling, above which transportation emissions cannot rise. The regional long-range transportation plans and short- range transportation programs are modeled, and the emis- sions estimate produced is compared to the emission bud- gets. Emissions for the current year, the short-term program, and the long-range plan all must meet the emission budgets. Included in the models are the trips generated by trucks using the highway system. The analysis of vehicle emission factors has led to a number of truck-related emission-control strate- gies to reduce oxides of nitrogen (NO x ), particulates (PM .10 and .25), and volatile organic compounds (VOCs). The con- formity process was not designed as a performance measure- ment system, but it includes the elements of one. It has goals, targets, an accepted architecture and technical protocols, and a reporting and quality-assurance process. The outputs of the conformity process indicate whether highway freight move- ments are contributing adequately to air quality goals. Similarly, the data from the hazardous materials releases and for crashes allow for high-level trend analysis as well as for granular drilling down into performance at the local, regional, or state level. Although the data for both crashes and hazardous releases have some well-documented report- ing flaws, they are available for continuous reporting of performance. The types of performance measures that could be pro- duced from the externality data sources include freight emis- sions by truck and rail, broken down by major category of pollutant; crashes by both highway and rail modes; and haz- ardous material release incidents. Emerging but Incomplete National Measures Considerable federal efforts have been undertaken to mea- sure many aspects of freight system performance, although an official set of federal freight performance measures does not exist. The Freight Analysis Framework and the Trans- portation Services Index provide considerable information about short-term freight volumes and long-term estimates of freight volumes, origins, and destinations. U.S. Depart- ment of Commerce data regarding economic output by sec- tor also can contribute significantly to approximating freight

37 volume trends. The USACE tracks waterborne freight volume on the U.S. Maritime Transportation System (MTS), as well as monitoring the age and condition of locks and dams. Rail volumes are reported by the FRA, as are aviation freight vol- umes by the FAA. Overall information about freight volumes, the modes they travel on, their value, and their origins and destinations are available. Disjointed Data Separate from the challenge of data volume is the challenge of inconsistency and integration of freight data to construct a performance measurement framework. Most of the freight data sets were developed independently by different organi- zations for different purposes. One study concluded that the data sets were a “disjointed patchwork” that frustrate users.11 The disjointed array of data sources is cumbersome and dif- ficult to use, lacking in geographic detail, and notably deficient in covering increasingly important motor carrier flows. Several users also expressed concern about the unnecessary burden on data providers, who may be asked to provide similar data to different organizations—sometimes in different formats. This heavy respondent burden is likely to hinder efforts to gather quality data. AASHTO’s Standing Committee on Performance Manage- ment has sponsored research projects that illustrate that dif- ferences exist in how two basic sets of transportation perfor- mance data are gathered. The research projects12, 13 examined how state transportation agencies collected and reported data for pavement conditions and project completion. Although pavement roughness data are collected by profilometer vehi- cles, the study noted that variations in how the equipment was calibrated, whether states measured one or two wheel paths, and how consistently the vehicles stayed in the wheel path all affect results. The issue of differences in how states collect pavement roughness data prompted the FHWA to include a separate table in its Highway Statistics report that notes the variations in the data collection methods.14 In its Report to Congress on the Performance of Ports and the Intermodal System,15 MARAD noted that a lack of common performance measures and the lack of a reporting process has stymied its attempts to measure the efficiency of major U.S. ports. It informed Congress that it was unable to assess congestion levels at ports or to assess the performance of the nation’s intermodal system overall. MARAD was unable to provide the requested comparison of the most congested ports in terms of operational efficiency due to a lack of consistent national port efficiency data. Given the diverse characteristics of U.S. ports, comparing port efficiency would require the creation of new methodologies and the collec- tion of data that were not available for this report. The GAO reported to Congress repeatedly on efforts by FMCSA to improve the quality of truck-crash reports: Overall, commercial motor vehicle crash data does not yet meet general data quality standards of completeness, timeliness, accuracy, and consistency. For example, according to FMCSA, as of fiscal year 2004 nearly one-third of commercial motor vehicle crashes that states are required to report to the federal govern- ment were not reported, and those that were reported were not always accurate, timely, or consistent.16 Lack of Performance Data Another finding of the research is that data about infra- structure condition are more available than are data for freight system performance. For instance, data for the condition of bridges and pavements have long been available through the National Bridge Inventory and through HPMS. However, information on overall performance as measured by truck speeds is only recently being developed through research by the FHWA and ATRI. Although USACE measures the infra- structure condition of the maritime transport system and the volumes on it, the Corps does not report on the travel time or reliability of water shipments. Likewise, despite the volu- minous information available on railroads, information on the speed and reliability of shipments is not being produced. Data on the relative speed of individual modes are available in some forms. The FHWA/ATRI data, HPMS speed esti- mates, and the AAR train-speed data provide general insight into the travel times on major highways and railroads. How- ever, the overall speed and travel reliability of supply chains that rely upon handoffs between modes is not available in the public domain. Package firms such as UPS and FedEx, major truck carriers, and the Class I railroads generally use GPS to track packages and freight. However, the data are available to their customers only for individual shipments. It is not aggregated for publication. Lack of Well-Defined Goals As has been mentioned, most performance measurement systems evaluate the success of policies, programs, or entities to achieve their goals. As there is no national freight policy, few explicit freight programs, and no single national freight agency, freight performance measurement lacks a clarifying set of priorities upon which measures would focus. In the Framework for a National Freight Policy,17 USDOT has taken the first steps toward outlining the components of a national freight policy. USDOT emphasizes that a true freight policy would come as the result of extensive consultation with the many public and private stakehold- ers and would probably involve considerable political dis-

38 course. Such consultation and discourse have only partially occurred. Therefore, USDOT emphasizes that it has pro- duced a framework for a national freight policy, and not a national policy itself. USDOT has adopted a vision statement for the framework, from which the subsequent objectives derive: “The United States freight transportation system will ensure the efficient, reliable, safe and secure movement of goods and support the nation’s economic growth while improving environmental quality.” The “overarching themes” for this national freight policy framework include four elements. First, the framework relies upon not only USDOT but also upon a large number of public and private stakeholders. Second, the national trans- portation system requires extensive investment, both public and private. Third, public and private collaboration is essen- tial not only for investment but also for the operation of the freight system. Fourth, the framework and its objectives must evolve as conditions and strategies change. The national framework is organized around a tradi- tional structure of objectives, strategies, and tactics. The objectives are: • Objective 1. Improve the operations of the existing freight transportation system. • Objective 2. Add physical capacity to the freight transpor- tation system in places where investment makes economic sense. • Objective 3. Better align all costs and benefits among par- ties affected by the freight system to improve productivity. • Objective 4. Reduce or remove statutory, regulatory, and institutional barriers to improve freight transportation performance. • Objective 5. Proactively identify and address emerging transportation needs. • Objective 6. Maximize the safety and security of the freight transportation system. • Objective 7. Mitigate and better manage the environmen- tal, health, energy, and community impacts of freight transportation. Specific program targets and a well-defined methodol- ogy for measuring progress toward those targets exist for the air-quality program. Such targets exist less explicitly for the hazardous materials and safety programs, but targets in those programs are implicit: both programs seek continuous reductions in crashes and in hazardous material releases. The presence of targets and performance-measurement architecture in those programs partially explains the com- prehensiveness of performance data for them. As a corollary, the lack of national freight system programs, performance goals, or targets partially explains the lack of freight system performance data. In “Strategy-Focused Performance Measures,” Frigo says “strategy first, then performance measures.”18 This conclu- sion is shared by many performance measurement authors. They first recommend clarity regarding strategy and desired outcomes, then the development of metrics to gauge the strategy’s effectiveness. The GAO has made similar recom- mendations regarding the national interest in freight: Compounding these challenges facing state and local trans- portation planners is that the federal government is not well po- sitioned to enhance freight mobility due to the absence of a clear federal strategy and role for freight transportation, an outmoded federal approach to transportation planning and funding, and the unsustainability of planned federal transportation funding. When combined, these challenges and factors hinder the ability of public sector agencies to effectively address freight mobility and highlight the need to reassess the appropriate federal role and strategy in developing, selecting, and funding transportation investments, including those for freight transportation.19 Endnotes 1 USDOT, FHWA Office of Freight Management and Operations, http://www. ops.fhwa.dot.gov/freight/freight_analysis/faf/index.htm (accessed May 13, 2010). 2 The National Highway Traffic Safety Administration, http://www-fars.nhtsa. dot.gov/Vehicles/VehiclesAllVehicles.aspx (accessed May 13, 2010). 3 USDOT, FMCSA, http://www.fmcsa.dot.gov/safety-security/sites/ company- safety.htm (accessed May 13, 2010). 4 USDOT, FHWA, http://ops.fhwa.dot.gov/freight/freight_analysis/perform_ meas/index.htm (accessed May 13, 2010). 5 USDOT, Pipeline and Hazardous Materials Safety Administration, http:// ops.fhwa.dot.gov/freight/freight_analysis/perform_meas/index.htm (ac- cessed May 13, 2010). 6 ATA, http://www.atabusinesssolutions.com/p-199-ata-american-trucking- trends-2008-2009.aspx (accessed May 13, 2010). 7 STB, Statistics of the Class I Freight Railroads in the United States, 2004, http://www.stb.dot.gov/econdata.nsf/66a333195e0491c885256e82005ad319 /2e8067542777b14c8525702e004144fc/$FILE/ts%20web%20version.pdf ( accessed May 13, 2010). 8 FRA, http://safetydata.fra.dot.gov/officeofsafety (accessed May 13, 2010). 9 AAR, http://www.aar.org/Resources/Resources%20Landing.aspx (accessed May 13, 2010). 10 MARAD, Report to Congress on the Performance of Ports and the Intermodal System, USDOT, June 2005, p. 43. 11 Donnelly, Rick (PB Consult, Inc.), “A Concept for a National Freight Data Program,” for the TRB Committee on Freight Transportation Data: A Frame work for Development, 2003, p. 6. 12 Harrison, Frances, and Hyun-A Park, NCHRP 20-24(37B), Comparative Per- formance Measurement: Pavement Smoothness, 2008.

39 13 Crossett, Joe, and Lauren Hines (TransTech Management, Inc.), AASHTO Standing Committee on Quality. Comparing State DOTs’ Construction Project Cost and Schedule Performance—28 Best Practices from 9 States. AASHTO, Washington, D.C., May 2007. 14 Table HM-66, Measured Pavement Roughness—2008 HMPS Data Repor- ting Details, FHWA Highway Statistics 2008, October 2009. 15 MARAD, Report to Congress on the Performance of Ports and the Intermodal System, USDOT, June 2005. p. 43. 16 GAO, Further Opportunities Exist to Improve Data on Crashes Involving Com- mercial Motor Vehicles, Nov. 2005 Highlights page. 17 USDOT, Framework for a National Freight Policy, http://www.freight.dot. gov/freight_framework/index.cfm. 18 See Frigo, M. L., Strategy-Focused Performance Measures, Strategic Finance, September 2002. 19 GAO, National Policy and Strategies Can Help Improve Freight Mobility, January 2008.

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TRB’s National Cooperative Freight Research Program (NCFRP) Report 10: Performance Measures for Freight Transportation explores a set of measures to gauge the performance of the freight transportation system.

The measures are presented in the form of a freight system report card, which reports information in three formats, each increasingly detailed, to serve the needs of a wide variety of users from decision makers at all levels to anyone interested in assessing the performance of the nation’s freight transportation system.

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