Which technique distinguishes between assignable cause and chance cause variation?

Control charts are a statistical tool used to monitor processes over time and to distinguish between assignable causes of variation (which are due to specific, identifiable factors) and chance causes of variation (which are inherent and natural to the process). By plotting data points of a given process on a control chart, one can visualize if the process is stable and within control limits or if there are variations that indicate an issue requiring investigation.

When data points fall within the control limits, it suggests that the variation is due to common cause (chance cause). However, if points fall outside the control limits, it signals that an assignable cause may be affecting the process. This insight enables organizations to take corrective action and improve process stability and quality.

Other techniques, such as process mapping, root cause analysis, and benchmarking, serve different purposes. Process mapping focuses on visualizing the steps in a process for clarity; root cause analysis seeks to identify the fundamental reasons behind specific problems; and benchmarking involves comparing performance metrics against industry standards or competitors. None directly address the differentiation between assignable and chance causes like control charts do.