Data mining model for identifying project profitability variables

Many engineering design companies collect data such as profits to manage projects. But the relationships between operational variables and performance are usually not thoroughly analyzed and interpreted. This paper proposes a data mining model and procedure to relate influence variables to project profitability. Data categories and variables are defined at the project input, process and output stages. The model proposed herein was tested by analyzing 548 projects of an engineering consulting company. The relationships between profitability and various input and process variables were identified and interpreted. For example, the effect of QA/QC on profitability is positive. Based on documented data and derived information, this model can help companies gain operational knowledge and thus further improve performance.