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42 in the number of pavement segments identified as requiring chapter, the distinction between quality control and accep- treatment and a large reduction in the estimated budgetary tance activities depends on how the activities are incorpo- requirements (51). Although this is only a single case, it indi- rated into the management plan, rather than the activities cates that third-party verification of data may be a cost-effective themselves. quality management tool. The techniques and approaches used for the verification are typically very similar to those applied The purpose of the quality control plan is to quantify the for the quality acceptance. A sample (e.g., 5% to 10%) of the variability in the process, maintain it within acceptable limits, data is typically subjected to the independent verification. identify the source of variability that can be controlled, and take the necessary production adjustments to minimize the "controllable" variability. A large percentage of the respon- DATA REJECTION dents (64%) have a formal data collection quality control In general, the amount of data that has to be corrected because plan or require the service provider to develop such a plan. A of errors detected during the quality assurance process is rela- comprehensive quality control plan typically includes clear tively small. More than half of the agencies (52%) reported that delineation of the responsibilities, documented manuals and less than 2% of the data need to be corrected or resubmitted procedures, personnel training, equipment and/or process cal- by the service provider, and 39% reported having to correct ibration, certification and inspection, verification procedures 2% to 5% and only 8% (two agencies) reported having to before starting and during production testing (e.g., using con- reevaluate or correct 6% or more. This result is consistent trol sites), and checks for data reasonableness, consistency, with the responses indicated that, in general, outsourcing of the and completeness. data collection with appropriate quality acceptance procedures has been beneficial for pavement management practices. Quality acceptance activities include all procedures used for acceptance testing of both the pavement condition data Although there does not appear to be a clear connection that are collected by the agency and those that are collected between network size and amount of rejected data, states with by a service provider. These tests validate that the data meet larger networks generally reported a data rejection rate of the established requirements before they are used to sup- less than 2%, whereas agencies with smaller networks showed port pavement management decisions. Approximately half more variation. Nearly all agencies reported a data rejection of the agencies that responded to this question have a formal rate of less than 5%. Agencies with a formalized quality man- pavement condition data quality acceptance plan. Quality agement plan appear to reject less data. This is expected management techniques commonly used for this purpose because a formalized quality management plan would clarify include testing of control and verification sites, sampling data acceptance procedures to all parties and data collec- and re-rating, complete database checks, GIS-based quality tion teams would most likely follow the quality control pro- acceptance checks, and time-history comparisons. Impor- cedures and would not submit data that would not meet the tant aspects for the testing of control and verification sites known standards. include establishing the acceptance criteria and the size of the sample required. SUMMARY In some cases, agencies also use an independent verifica- This chapter covered the main quality control, quality accep- tion by a third party to resurvey or reevaluate a sample of the tance, and independent assurance principles and techniques data. The techniques and approaches used for the independent currently being followed by transportation agencies for pave- verification are typically similar to those applied for the quality ment condition data collection. As discussed in the previous acceptance.