Build a Pareto From Complaint Data
Calculate and interpret a Pareto priority from complaint-category data.
A support export has 312 complaints: wrong item 118, missing item 72, late delivery 48, damaged packaging 28, unclear invoice 24, other 22. Pareto analysis: sort categories by count, compute percent of total, compute cumulative percent, choose the focused slice for cause analysis. The common trap is to prioritize the category with the most recent escalation or the stakeholder with the loudest story. That can send Analyze toward a visible irritation while the largest defect population keeps growing. Step 1 Sort the categories from largest to smallest: wrong item 118, missing item 72, late delivery 48, damaged packaging 28, unclear…
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