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TCRP Report 134: Transit, Call Centers, and 511: A Guide for Decision Makers (2009)
Transit Cooperative Research Program (TCRP)

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Transportation Research Board. "3.2.2 Implications for Transit Agencies." TCRP Report 134: Transit, Call Centers, and 511: A Guide for Decision Makers. Washington, DC: The National Academies Press, 2009.

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28
Front Matter (R1-R11)
Summary (1-7)
1.1 Background (8-8)
1.3 Research Tasks (9-9)
2.2 National Inventory of Operational 511 Systems (10-10)
2.3 Transit Agency Case Studies (11-12)
2.4 Non-Transit Call Center Interviews (13-13)
2.6 Transit Rider Focus Group (14-16)
3.1.1.1 Customer Information Needs and Preferences (17-17)
3.1.1.2 Information Provided by Transit Agencies (18-18)
3.1.1.3 Dissemination Methods/Technologies Utilized (19-19)
3.1.1.4 Matching Dissemination Methods/Technologies with Customer Needs and Preferences (20-21)
3.1.2.3 Technologies (22-24)
3.1.2.4 Metrics (25-25)
3.1.3 Implications of Agency Size and Type (26-27)
3.2.2 Implications for Transit Agencies (28-28)
3.3.2.1 Operational 511 Systems (29-29)
3.3.2.2 Transit Agency Participation in 511 Systems (30-31)
3.3.3.1 Customer Information and Call Center Approaches (32-32)
3.3.3.2 Participation in Non-511 Traveler Information Systems (33-33)
3.3.4 Transit-Related 511 Operating Statistics (34-34)
3.4 Transit Agency Case Studies (35-35)
3.4.1.1 Arizona 511 (36-37)
3.4.1.2 El Dorado Transit (Sacramento California, Area) (38-38)
3.4.1.4 Central Florida Regional Transportation Authority (39-39)
3.4.1.5 Island Explorer (Bar Harbor, Maine) (40-40)
3.4.1.7 Charlotte Area Transit (North Carolina) (41-41)
3.4.1.8 San Diego 511 (42-44)
3.4.1.10 Washington Metropolitan Area Transportation Authority (45-45)
3.4.1.12 Southeast Florida 511 (46-51)
3.4.1.13 San Francisco Bay Area 511 (52-61)
3.4.2.1 Manchester Transit Authority (New Hampshire) (62-62)
3.4.2.3 King County Metro Transit (Seattle) (63-63)
3.4.3.2 Regional Transit District (Denver) (64-64)
3.4.3.4 Tri-Met (Portland) (65-65)
3.5.1 Rationale for Transit Content Decisions (66-66)
3.6 Transit Rider Focus Group (67-67)
3.6.2 Transit Information on 511 (68-69)
4.1.1.1 National Overview of 511 Systems and Transit Participation (70-70)
4.1.1.3 Transit Rationale for Participation/Non-Participation in 511 (71-71)
4.1.1.4 Impacts of 511 Participation on Transit Agencies (72-73)
4.1.2.1 Buy-In on 511 as a Multimodal Resource (74-74)
4.1.3.2 Transit Information on 511 (75-75)
4.1.4.1 The Role of the Telephone in Transit Customer Information (76-76)
4.2.1.1 General Recommendations on the Applicability of Basic and Additional Transit Information on 511 (77-77)
4.2.1.2 Basic Transit Information (78-78)
4.2.2.1 Consider Greater Utilization of Proven, Advanced Technologies and Techniques (79-80)
4.3 Plan for Implementing the Research Findings (81-82)
References (83-84)
Appendix A - Transit Agency Interview Questionnaire (85-87)
Appendix B - Transit Rider Focus Group Discussion Guide (88-89)
Abbreviations used without definitions in TRB publications (90-90)

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28 level of agency size represents the tipping point where more · The quality monitoring technologies used and the perfor- complex and rigorous call center methods become common. mance metrics tracked by non-transit call centers are sim- The somewhat counterintuitive findings for real-time infor- ilar to those employed by transit agencies. The size of the mation (i.e., small agencies are as likely to provide real-time organization and number of calls seems to be the key driver information as are large agencies) is a function of the small both within and outside the transit industry. There does sample size and the fact that the small agency sample included seem to be a slightly greater use of the most sophisticated the Acadia National Park Island Explorer service, a rare exam- techniques in non-transit organizations. ple of a small agency that provides "next bus" type information. 3.2.2 Implications for Transit Agencies 3.2 Telephone Information Overall, it was found that transit and non-transit agencies Strategies of Other use many of the same call center methods. Those methods Organizations vary primarily in relation to call volumes. Organizations han- This section compares and contrasts the call center opera- dling the highest call volumes use more of the most sophisti- tions of transit and non-transit organizations whose call cen- cated methods. However, it was also found that although ter operations are considered state of the art. Information on many of the same methods were used, non-transit call centers non-transit call centers was collected from call center literature tend to use more of the advanced methods than do transit (26-29) and supplemented with telephone interviews. Three call centers with comparable call volumes. Based on our tele- organizations were interviewed including a state motor vehi- phone interviews, in those cases where transit agencies use cle department; a local bank branch office; and a very large, less technology than non-transit agencies, it is either because national consumer durables manufacturer. These organiza- they lack the resources, or because they do not feel that the tions provided insight on call center organizations of various more advanced, costly methods are necessary given their call sizes responsible for different types of products and services. volumes. These findings have the following implications for transit agencies: 3.2.1 Similarities and Differences between · Consider employing advanced call center technologies. Transit and Non-Transit Call Centers Although the smallest agencies with the lowest call volumes The study team identified the following similarities and do not warrant major call center technology investments, differences between transit and non-transit call centers: somewhat greater use of technology by agencies of varying sizes would provide benefits for many organizations. Some · Call center approaches vary widely depending mostly on general benefits of using call center technology include the size of the organization; larger organizations employ ­ Decreasing the amount of manual, paper-based processes more sophisticated approaches. at larger call centers (those with more than 10 call takers · Non-transit organizations typically utilize more advanced that are typically found at medium/large urban or rural call center technologies than even the larger transit agencies. transit agencies) by using workforce management tech- For example, the consumer durables manufacturer inter- nologies that can track daily work logs and automate viewed uses all of the technologies asked about on the most tasks; survey, whereas many of even the largest transit agencies ­ Reducing the amount of time spent on repetitive infor- interviewed use only some of those technologies. mation requests by implementing IVR systems and post- · Non-transit organizations, particularly the larger and more ing such information on the agency website; sophisticated ones, use IVR technologies more than the ­ Ensuring customer service quality for agencies with large average transit agency to limit the number of live opera- call volumes (e.g., more than 1,000 calls per day) by using tor interactions. Non-transit organizations, especially those quality monitoring technologies; and with high call volumes, often employ more sophisticated ­ Improving customer management, particularly at those IVR menu structures/ACD schemes and make a greater agencies that wish to provide personalized information effort to route specific types of customer questions to spe- such as service alerts, through the use of CRM and CIM cific operators. software. · Transit and non-transit organizations utilize similar ap- · Provide more personalized information. Many non- proaches to staffing call centers and setting call-taker skill transit call centers provide highly personalized informa- requirements. The study team's judgment is that non-transit tion to callers. One way they accomplish this service is organizations tend to use more sophisticated human re- by creating individual customer accounts based upon the source strategies than do even the largest transit agencies. products purchased. This captured information enables