Evaluating a process by examining its operational method and the outcome it produces provides a comprehensive understanding of its effectiveness. For example, analyzing a sorting algorithm involves scrutinizing the specific steps it takes to arrange data and the final order of that data. This dual assessment helps pinpoint inefficiencies and potential errors.
This approach to evaluation is essential for ensuring quality, reliability, and continuous improvement. By examining both the process and the outcome, one can identify discrepancies between expected and actual results, leading to more effective problem-solving and informed decision-making. Historically, focusing solely on results has often masked underlying process flaws. This combined analysis offers a deeper understanding, facilitating refinement and optimization across various disciplines, from software development to manufacturing and scientific research.