Using Earned Value Data to Detect Potential Problems in Acquisition Contracts

Government contractors report earned value information to government agencies in monthly contract performance reports. Though major differences may exist in the data between subsequent contract performance reports, we know of no government effort to detect these occurrences. The identification of major changes may locate and isolate problems and, thus, prevent million and billion dollar cost and schedule overruns. In this study, we illustrate a proof of concept approach to identify changes in the cost performance index and the schedule performance index that may indicate problems with contract performance. We find the intuitive detection algorithm identifies changes in the cost performance index and the schedule performance index that correspond to large changes in the Estimate at Complete from 1 to 12 months out. The ability to detect unusual changes provides decision-makers with warnings of potential problems for acquisition contracts.