Construction projects can be complex and managers are faced with the challenge of managing multiple trades working on a large number of interdependent tasks. When one trade or task experiences variation, defined as the time difference between what was planned and what happened for this research, additional trades or tasks can be impacted, the project schedule can be disrupted, and/or productivity can suffer. A case study involving a general contractor (GC) building a 150,000 square foot data collection center was conducted. Both starting time and task duration variation data was collected on approximately 1200 tasks performed by over 40 trades. A risk assessment matrix was used to determine which causes of variation posed the greatest risk to project performance. Pajek, a social network analysis software, was used to illustrate the organizational structure of the key trades throughout the project. The research is unique as it couples the quantitative variation analysis with the associated social network of trades to create a decision support system that can be used to target variation for reduction. The results of this research are repeatable and can be useful for managers in improving project performance.