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Statistical process control has been compared with two other approaches (confidence intervals and acceptance testing) to determine the potential for this technology in developing realistic sampling plans that offer equal protection for both consumer and producer. These theories were first assessed from a practical standpoint and then were subjected to experimental manipulation using a computer simulation program. Results showed that the optimal solution is to use a combination of process control (the p-chart method) and acceptance testing (Military Standard 105D) to evaluate service quality. This approach offers realistic output that protects the consumer and producer at a similar level; in addition, process control allows historical data to be used so that a contractor who has performed well in the past can be sampled less stringently. Finally, a major advantage is that overall quality of contract services should improve by implementing this approach because the contractor will receive feedback that identifies inconsistencies in services performed; the faults can then be corrected and, over time, the contractor will learn what needs to be done to provide acceptable performance. A step-by-step implementation plan has been proposed. It is recommended that the Army field- test this approach and develop an automated system for rapid evaluation.