In Organizational Process Performance (OPP), why are process performance baselines and process performance models important?
Process performance baselines and models (OPP specific practice1.4, “Establish and maintain the organization’s process-performance baselines.” and specific practice 1.5, “Establish and maintain the process-performance models for the organization’s set of standard processes.”) summarize the historical performance of selected processes (or subprocesses). Process performance baselines are often represented as statistical summaries (e.g., mean and variation) of how a process or subprocess has performed across the organization (appropriately normalized, e.g., for work product or task size). Process performance models are often represented as predictive models (e.g. Regression, Correlation, Analysis of Variance, Chi-Square Analysis, Logistic Regression, Discrete Event, and Monte Carlo simulation modeling) that indicate the statistical relationship among measures of selected process or work product attributes from different lifecycle phases. Both process performance models and baselines are u
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