What do Level 4 practices use to predict the achievement of quality and process performance objectives?

Level 4 practices in CMMI (Capability Maturity Model Integration) are focused on quantitatively managing processes. The hallmark of Level 4 is the use of statistical and quantitative techniques to understand and control processes quantitatively. By applying these methods, organizations can predict the achievement of quality and process performance objectives with a higher degree of accuracy.

Statistical methods allow organizations to analyze variations in processes, measure performance against objectives, and make informed predictions about future performance. Techniques such as statistical process control (SPC), control charts, and regression analysis help managers make decisions based on empirical data rather than assumptions or anecdotal evidence.

In contrast, methods like best practices, expert opinions, and historical data may provide valuable insights but do not offer the predictive rigor and reliability that statistical techniques provide. Best practices may vary from organization to organization and may not be based on specific quantitative analyses. Expert opinions can be subjective and uncertain, relying on individual experience rather than data. Historical data can be informative but without the analytical frameworks provided by statistical techniques, it may not accurately predict future performance on its own. Thus, statistical and quantitative techniques are fundamental for achieving the predictive capabilities emphasized in Level 4 practices.