Accurate measurement of energy savings from industrial energy efficiency projects can reduce uncertainty about the efficacy of the projects, guide the selection of future projects, improve future estimates of expected savings, promote financing of energy efficiency projects through shared-savings agreements, and improve utilization of capital resources. Many efforts to measure industrial energy savings, or simply track progress toward efficiency goals, have had difficulty incorporating changing weather and production, which are frequently major drivers of plant energy use. This paper presents a general method for measuring plant-wide industrial energy savings that takes into account changing weather and production between the pre and post-retrofit periods. In addition, the method can disaggregate savings into components, which provides additional resolution for understanding the effectiveness of individual projects when several projects are implemented together. The method uses multivariable piece-wise regression models to characterize baseline energy use, and disaggregates savings by taking the total derivative of the energy use equation. Although the method incorporates search techniques, multi-variable least-squares regression and calculus, it is easily implemented using data analysis software, and can use readily available temperature, production and utility billing data. This is important, since more complicated methods may be too complex for widespread use. The method is demonstrated using case studies of actual energy assessments. The case studies demonstrate the importance of adjusting for weather and production between the pre- and post-retrofit periods, how plant-wide savings can be disaggregated to evaluate the effectiveness of individual retrofits, how the method can identify the time-dependence of savings, and limitations of engineering models when used to estimate future savings. (C) 2007 Elsevier Ltd. All rights reserved.