Recognizing the broad scope of the problem, GM responded with a three-pronged analytics-based effort focusing on production line data collection, throughput modeling and algorithms, and throughput improvement processes. In tackling the production data collection component, GM recognized the importance of limiting data inputs from the massive universe of production data available, to avoid bogging down the analytical processes. The goal was to develop models and algorithms with modest data requirements that still produce meaningful results. Repeated trial and validation efforts established the appropriate data inputs in the areas of workstation speed changes, scrap counts and