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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.