After reviewing SEM measurement and verification (M&V) protocols from different programs, the NW SEM Collaborative's Energy Tracking and Savings Protocols (ETSP) team identified multicollinearity as a common statistical issue in industrial data sets in October 2013. Understanding that multicollinearity has the potential to affect the specification of regression-based energy models used to determine adjusted baselines, more consistent treatment of this issue may help improve confidence in SEM-based savings, and thereby address a potential market barrier. Therefore, the team compiled this paper for the purposes of outlining the implications of multicollinearity in the context of SEM measurement and verification, and providing examples of how program implementers have successfully identified and treated the presence of multicollinearity among a set of predictor variables.