The best way to understand Pareto analysis is to see it in action. Below are 6 real-world Pareto chart examples across manufacturing, healthcare, software, customer service, logistics, and HR. Each shows the raw data, the vital few categories, and the corrective action taken.
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Manufacturing: PCB Assembly Defects
| Category | Count | % | Cumulative % |
|---|---|---|---|
| Solder bridging | 142 | 43.8% | 43.8% |
| Missing component | 78 | 24.1% | 67.9% |
| Cold solder joint | 52 | 16.0% | 83.9% |
| Misalignment | 31 | 9.6% | 93.5% |
| Wrong orientation | 21 | 6.5% | 100.0% |
Healthcare: Medication Administration Errors
| Category | Count | % | Cumulative % |
|---|---|---|---|
| Wrong dose | 74 | 39.6% | 39.6% |
| Omitted dose | 48 | 25.7% | 65.2% |
| Wrong time | 32 | 17.1% | 82.4% |
| Wrong patient | 19 | 10.2% | 92.5% |
| Wrong route | 14 | 7.5% | 100.0% |
Software: Customer Bug Reports
| Category | Count | % | Cumulative % |
|---|---|---|---|
| Login/auth failures | 128 | 31.1% | 31.1% |
| Slow page load | 94 | 22.9% | 54.0% |
| Data sync errors | 71 | 17.3% | 71.3% |
| UI rendering | 58 | 14.1% | 85.4% |
| Notifications | 60 | 14.6% | 100.0% |
Customer Service: Support Escalations
| Category | Count | % | Cumulative % |
|---|---|---|---|
| Late delivery | 112 | 43.8% | 43.8% |
| Wrong item | 68 | 26.6% | 70.3% |
| Damaged item | 41 | 16.0% | 86.3% |
| Missing item | 23 | 9.0% | 95.3% |
| Billing error | 12 | 4.7% | 100.0% |
Logistics: Warehouse Pick Errors
| Category | Count | % | Cumulative % |
|---|---|---|---|
| Wrong quantity | 81 | 42.0% | 42.0% |
| Wrong SKU | 55 | 28.5% | 70.5% |
| Damaged on pick | 29 | 15.0% | 85.5% |
| Wrong location | 18 | 9.3% | 94.8% |
| Missing label | 10 | 5.2% | 100.0% |
HR: Voluntary Employee Resignations
| Category | Count | % | Cumulative % |
|---|---|---|---|
| Better compensation | 34 | 36.2% | 36.2% |
| No growth path | 26 | 27.7% | 63.8% |
| Poor manager | 19 | 20.2% | 84.0% |
| Work-life balance | 11 | 11.7% | 95.7% |
| Relocation | 4 | 4.3% | 100.0% |
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The blue-highlighted rows in each table are the vital few — the categories that fall below the 80% cumulative threshold. These are the priority. Fixing the vital few first is almost always more efficient than spreading effort across every category equally.
Notice that the action in every example targets the vital few directly. The 80/20 split is also approximate: some charts land at 70/30 (like the healthcare and logistics examples above), others at 85/15 (HR). What matters is identifying the clear break between high-impact and lower-impact categories, then focusing resources there before addressing the rest.
Related
- Pareto Analysis: Complete Guide
- 5 Whys vs. Pareto: When to Use Each
- Free Pareto Chart Template
- Free Pareto Chart Maker (tool)
Frequently asked questions
What is a Pareto chart example?
A Pareto chart example shows categories of a problem (e.g., defect types, complaint categories) sorted from most to least frequent as descending bars, with a red cumulative percentage line overlaid. The 80% threshold line separates the “vital few” categories — the small number responsible for most of the problem — from the “useful many.” A typical manufacturing example might show that solder bridging and missing components cause 68% of all PCB defects.
How many examples should a Pareto chart have?
Most effective Pareto charts contain 4–8 categories. Fewer than 4 rarely shows a meaningful distribution. More than 10 often means categories need consolidation. An “Other” category is acceptable if it falls below 5–10% of the total, but should never be the largest bar — if it is, your categories are too granular.
Can a Pareto chart be used in healthcare?
Yes. Pareto charts are standard tools in healthcare quality improvement. Common examples include analyzing types of medication errors (wrong dose, omitted dose, wrong time), categorizing adverse event causes, or prioritizing readmission diagnoses. The Joint Commission and IHI both include Pareto charts in their recommended quality tools.
What data do I need to make a Pareto chart?
You need a list of problem categories and a count of how many times each occurred in a defined period. For example: defect type + number of defects per type over 3 months. You do not need equal time periods per category, but all counts should reflect the same overall period. Percentages and cumulative percentages are calculated from the raw counts.