What is the purpose of stratification in quality management?

Stratification in quality management serves to uncover patterns in different data sources by dividing data into subgroups or layers, allowing for a deeper analysis of variations and trends. This method enhances understanding by revealing insights that might be hidden when looking at data as a whole. By examining different strata, such as customer demographics, product types, or time periods, organizations can identify specific issues or opportunities for improvement, which may not be visible when the data is aggregated. This targeted analysis enables decision-makers to implement more focused and effective strategies.

Data collection methods, mapping process sequences, and control limits play important roles in quality management but do not specifically relate to the strategic purpose of stratification. Collecting qualitative data focuses on subjective inputs rather than patterns, and mapping sequences is about understanding workflow rather than data analysis. Analyzing control limits pertains to monitoring process variability and performance over time, which doesn't directly target the uncovering of patterns in diverse data sources. Thus, the correct purpose of stratification aligns with the need for uncovering meaningful patterns that can drive quality improvements.