- March 21, 2016
- Your Price: $50.00
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Most process benchmarking or process analysis projects focus on descriptive statistics such as median costs or average ratings for satisfaction and cycle time. Though useful as an indicator of current performance, descriptive benchmarking does not provide information on “why” performance is what it is and how to improve it. Statistical analysis and predictive models, on the other hand, help organizations understand the relationships and drivers for key business process outcome and outline why and how the organization needs to improve its processes.
In 2015, APQC conducted a benchmarking effort that focused on automotive warranty performance measures. This case study explores that how the project developed a model to predict which factors improve key performance measures related to the business objectives: cycle time, customer retention, and costs.