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38 Guidebook for Understanding Urban Goods Movement three underlying movement pairs (foreign to domestic, domestic to domestic, and domestic to foreign) and each type of O/D pair is further described by seven types of modal movement or combination of modes. In addition, the database provides forecast matrices out over 2 decades. Even with the greater detail in geographic zones, the database must be further disaggregated and supplemented with local data for use in many urban planning applications. However, given the robust promise of the FAF-3 for planning applications, research into techniques for disaggrega- tion continues, and some additional tools and techniques are readily available for planners to begin commodity analysis for their area. NCFRP Project 20, "A Guidebook for Developing Sub- National Commodity Flow Data," a project in progress at the time of this report, will provide additional resources and methods for local planners seeking to use freight flow data. Additional information about FAF-3 can be found at TRANSEARCH is a proprietary database produced by IHS Global Insight. TRANSEARCH is a nationwide commodity O/D database produced on an annual basis for freight flows between U.S. geographies at the county, Bureau of Economic Analysis (BEA) area, or state level. TRANSEARCH employs the CFS but also various primary and secondary data sources covering commodity volume, value, and modal flow, including a long-term, proprietary motor carrier traf- fic sample, railroad waybill samples, and numerous commercial and federal government surveys. The comprehensive geographic, commodity, and modal coverage of this database has made it a popular source of freight flow information for state and metropolitan transportation planners. TRANSEARCH data is not free, and the price varies with the level of customization and cover- age. One benefit of TRANSEARCH over FAF-3 is that if errors or inaccuracies in the O/D matrix are discovered, they are corrected in a timely manner. Nonetheless, as many governments strug- gle with budgetary issues, many find data purchases for freight flows difficult to justify. Whether public or private, secondary sources of freight flow information can be enhanced by primary data collection activities, such as truck intercept surveys or shipper interviews. Because the prominent freight flow data sources are based on periodic national survey samples and data modeling techniques, localized surveys can serve to validate flows at a more localized level. Techniques such as truck intercept surveys can be used to examine the validity of O/D data, length of haul, and other attributes of third-party datasets. These data sources and meth- ods for disaggregation to smaller geographic areas will be discussed further in the next section. See Exhibit 4-9. Freight Data Protocols As discussed at the beginning of this chapter, freight data has become a topic of intense inter- est. Many planners, analysts, and academics hold strong opinions about freight data sources, techniques for applying freight data to planning issues, and the usefulness of products resulting from freight data and analysis. Freight data is a complex subject requiring information about both public and private facilities. Unlike passenger travel, a freight trip is far more likely to cross multiple modes and journey through multiple geographic jurisdictions. Although methods for collecting passenger information have become highly standardized, freight data sources are often fragmented and incompatible. For instance, the primary sources of commodity flow data use dif- ferent industry classification schemes: FAF-3 and CFS use the Standard Classification of Trans- ported Goods (SCTG), and TRANSEARCH and the Rail Waybill Sample use the Standard Transportation Commodity Classification (STCC) system. Both FAF-3 and TRANSEARCH produce statistics for seven transportation modes or movement types; however, FAF movement types include modal combinations representing intermodal movements, while TRANSEARCH movement types disaggregate specific modes like trucking into truckload, less-than-truckload, and private fleets.

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Using Freight Data for Planning 39 Exhibit 4-9. Example of integrated data sources for customizing freight flow data. Source: Wilbur Smith Associates. Given the complexity of freight data and its applications, the following protocols are offered for selecting and using freight data in planning applications: Clearly define the issue(s) to be addressed: While planners always start with a plan, it cannot be overstated that in the case of freight data, clearly defining specific data needs to support the planning effort will save considerable time and resources. A good first step in identifying the data needed to support a larger planning effort is the creation of a data synthesis and collec- tion plan. Putting together the issues to be addressed, and the specific data needed to support those efforts, allows for greater interaction (and potentially buy-in) from the planning team and colleagues. The data plan should be a flexible document that is modified as conditions change or new information is identified. Collect only the information you need (and can support): Although "only collect the data you need" is a common rule, there is often a tendency to extract "nice to know" as opposed to "need to know" information from private-sector freight stakeholders. It is also a good idea to assess internal capabilities for data analysis and maintenance, so that efforts made to collect freight data don't go unused or become outdated if the planning effort requires periodic updates to the supporting information. Seek out partners who can open doors for your data collection efforts: Many successful freight data efforts result from public agencies partnering with business groups, trade associations, or economic development agencies. Chambers of commerce and industry associations like state trucking or rail associations can be crucial partners for data collection. Getting the sup- port of industry groups can provide access to their membership and often these groups will

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40 Guidebook for Understanding Urban Goods Movement assist in disseminating surveys and add legitimacy to your efforts. In addition, they can be a source of expert advice and rules of thumb, which may substitute when data is inaccessible. Public or quasi-public economic development agencies also can be of great help identifying appropriate stakeholders for primary data collection efforts with various industry groups. Remember the 80/20 rule: Pareto's principle suggests that for many things a few (20 percent) are vital and many (80 percent) are trivial. Because freight is often consolidated at significant nodes, getting good information for the most vital facilities (i.e., largest 20 percent) can provide information about a majority of volume. There is no "one size fits all" data solution for most freight planning efforts: Once your data needs are identified there are likely to be local-, regional-, and state-level data that can help support your efforts. There are also a growing number of national-level secondary freight data sources avail- able online, as well as documentation and research through FHWA and TRB that can identify and explain secondary freight data sources. With a comprehensive list of secondary data that can support your project, conduct a gap analysis to identify where primary data collection may be needed to address your specific issues. Design a data program that fits your needs, and be creative: There are many opinions about what constitutes good freight data. Often opinions have been formed by using inappropriate data sources for the problem being addressed, misguided expectations, or personal biases. Before using secondary freight data sources do the research required to understand potential shortcomings and be realistic about what data gaps may need to be filled. Be prepared to think outside the box in seeking ways to collect primary data.