A statistical project control tool for engineering managers

Engineering managers make decisions daily to ensure their project is meeting customer requirements. The project environment is highly dynamic and decisions must be made quickly based on experience and data readily available from internal and external sources. This research evolved from a fundamental belief that proven engineering quality control methods applied to hardware processes can also be applied to project management processes. This research was limited to process, power, heavy equipment, general building, and environmental projects in the construction industry.; The research problem statement is supported by historic accounts of a large number of project failures. These failures occur as delays, budget overruns, cancellations, and customer requirement shortfalls. This dissertation advocates a practical easy-to-use quantitative benchmarking tool to help managers guide the project successfully and reduce the large losses of capital investment in the US.; The research procedure and methodology utilized a modified Shewhart control chart used in manufacturing processes since the 1920s and applied it to project management processes. This new chart is called the Statistical Project Control Tool (SPCT). Quantitative variables that are indicators of project success were plotted versus time-periods. These actual real-time data were plotted in control chart form with statistical limit zones. Pattern analysis rules were used to determine real-time “health” of the process.; The research results were four valid control charts for each variable derived from twenty similar successful projects. There is a different control chart for each of four variables—actual owner expenditure, actual % design complete, actual % construction complete and actual cost of change orders—used as a function of time periods during the project life cycle. Three successful and three failed projects were plotted on each of the four control charts. Validation was accomplished by comparing the project owners' judgment with the control chart results. The results indicated that projects judged successful by their owners followed an “in control” pattern and projects judged unsuccessful by their owners followed an “out of control” pattern. The “out of control” patterns were described by six rules. A new dynamic decision-making tool for project management benchmarking is now available.