What Is a Pareto Chart?
A Pareto chart is a combination chart that visualizes concentration: it shows which contributors drive the majority of a result, and how quickly the cumulative total is reached as you move down the list.
It's named after the Italian economist Vilfredo Pareto, who observed in the late 1800s that roughly 80% of Italy's land was owned by 20% of the population. That same 80/20 pattern turned out to appear everywhere in business and nature:
- 80% of revenue comes from 20% of customers
- 80% of inventory movement is driven by 20% of SKUs
- 80% of defects originate from 20% of root causes
- 80% of support tickets come from 20% of product issues
The Pareto chart makes this concentration visible at a glance.
How it's built
A Pareto chart has three components:
- Sorted bars — the entities you're analyzing (customers, products, defect types...) sorted from the highest contributor on the left to the lowest on the right. Each bar shows that entity's share of the total.
- Cumulative line — a line overlaid on the bars that shows the running total as a percentage of the whole. It starts low on the left and climbs toward 100% as you move right.
- Reference line — a horizontal marker (usually at 80%) that intersects the cumulative line. The vertical crosshair shows you exactly which group of entities accounts for that 80%.
Everything to the left of that crosshair is your critical group — the few contributors that explain most of the result.
What Is a Pareto Chart Used For?
Pareto charts are standard tools in quality management, operations, sales strategy, and supply chain. Some of the most common applications:
Sales & revenue analysis
Which customers generate the most revenue? A Pareto chart instantly surfaces whether your revenue is concentrated in a handful of accounts or spread broadly — critical information for key account strategy and resource allocation.
ABC inventory classification
In supply chain, the ABC method groups products by their contribution to total volume or value: A items (top ~70%) get tight stock control; B items (70–90%) get standard replenishment; C items (90–100%) are reviewed for potential discontinuation. A Pareto chart is the standard visualization for this analysis.
Defect prioritization (Lean / Six Sigma)
Which root causes should your quality team tackle first? The Pareto principle says that fixing the top two or three defect categories will eliminate the majority of your quality issues. The chart shows which ones they are.
Supplier & procurement analysis
How concentrated is your supplier base? If 80% of your purchasing spend goes through two suppliers, that's a supply chain risk — and a Pareto chart surfaces it immediately.
Product portfolio review
Which SKUs should stay in the catalog? Which ones occupy warehouse space for negligible volume? Pareto analysis separates the vital few products from the long tail.
General Features of a Pareto Chart
Before getting into a specific tool, here's what any well-built Pareto chart should do:
- Automatic ranking — entities must always be sorted from highest to lowest contributor. The whole point of the chart is the ranked order; if the sorting is wrong, the analysis is meaningless.
- Dual-axis display — the left Y-axis shows each bar's individual contribution (usually as a percentage of total); the right Y-axis shows the cumulative percentage tracked by the line.
- Configurable reference lines — the 80% line is the classic default, but good implementations let you set the threshold to any value. ABC analysis requires two lines (at 70% and 90%); some use cases need three.
- Binning — when you have hundreds or thousands of entities (e.g. 5,000 SKUs), showing one bar per entity makes the chart unreadable. Binning groups entities into percentage-based buckets — the top 10%, the next 10%, and so on — turning a 5,000-bar chart into a clean 10-bar summary.
- Outlier handling — a single extreme entity (one mega-account worth 5× the next largest customer) distorts the entire cumulative shape. Good tools let you exclude top/bottom outliers so you can analyze the distribution of the "normal" part of your data.
- Cross-filtering — in a BI tool context, clicking a bar should filter the rest of the report. The Pareto chart is most powerful when it acts as an entry point that drives a table, a map, or other charts on the same page.
- Drilldown — for hierarchical data (Category → Subcategory → SKU), being able to drill into a Pareto level and have it automatically recalculate is far better than building a separate chart for each level.
Pareto Chart Pro for Power BI
Power BI doesn't include a native Pareto chart. You can approximate one by combining a sorted column chart with custom DAX measures for rank and cumulative percentage — but it's a multi-step setup that takes 15–30 minutes, breaks when the data model changes, and doesn't support binning without additional calculated columns.
Pareto Chart Pro is a Microsoft-certified custom visual available free on AppSource that handles all of this automatically.
How it works
You add two fields and the chart renders:
- Entity — the category you're ranking (Customer, Product, SKU, Supplier, Defect Category — anything)
- Value — the numeric measure (Revenue, Units, Defect Count, Purchase Amount)
The visual sorts automatically, groups into bins, draws the cumulative line, and places a reference line at 80% by default. No DAX, no calculated columns, no combo chart configuration.
Features
Automatic binning
By default each bar represents 10% of your entities — so 10 bars total regardless of how many entities you have. In the Pro tier you can set bin size from 1% to 20%, from a granular 100-bar view down to a 5-bar executive summary.
Up to 3 reference lines
Line 1 is on at 80% by default. Change it to any threshold, add a second line (both tiers), and a third (Pro) for ABC-style three-zone analysis. Each line has its own color, position, and label.
Drilldown on hierarchies
Add a hierarchy to the Entity field — Category → Subcategory → SKU — and the standard Power BI drill buttons appear. Drill down and the Pareto recalculates automatically at each level. No separate charts needed.
Outlier exclusion (Pro)
Exclude the top or bottom N% of entities before binning. Useful when a single dominant account distorts the shape of the rest of the distribution.
Value labels (Pro)
Show the percentage contribution above each bar. Essential for executive dashboards and exported screenshots where the audience won't hover over the chart.
Cross-filtering
Click a bin to filter all other visuals on the page. Multi-select with Ctrl to compare groups. Pareto Chart Pro participates fully in Power BI's standard cross-filter and cross-highlight model.
High contrast & accessibility
Automatically switches to system high-contrast colors when Windows or Power BI high contrast mode is active.
Conditional formatting on bars
In the Format Pane → Bar color, click the fx button to apply standard Power BI conditional formatting rules — color by value range, percentage tier, or gradient scale.
Step-by-Step: Your First Pareto Chart in Power BI
- Install from AppSource In Power BI Desktop → Visualizations pane → three dots → Get more visuals → search Pareto Chart Pro → Add.
- Add the visual to your canvas Click or drag the new icon from the Visualizations pane.
- Bind your data Drag a category field into Entity and a numeric measure into Value.
- Read the result Left Y-axis: each bin's % of total. Right Y-axis: cumulative %. Orange line: cumulative curve. Red dashed line: 80% threshold. The bin where the cumulative line crosses 80% is your breakpoint. Everything to the left is your critical group.
- Add a second reference line for ABC analysis (optional) Format Pane → Reference Lines → Show line 2 → set to 90%. You now have three zones: A (0–80%), B (80–90%), C (90–100%).
- Enable drilldown (optional) Replace the single category field in Entity with a hierarchy. Use the drill arrows in the visual header to navigate levels.
Example Configurations
Classic 80/20 customer analysis: Entity: Customer Name · Value: Revenue · Line 1 at 80% → Shows which customers to treat as key accounts
ABC inventory: Entity: SKU Code · Value: Sales Volume · Line 1 at 70% · Line 2 at 90% · Line 3 at 100% (Pro) → Segments the catalog into A, B, and C items automatically
Defect prioritization: Entity: Defect Category · Value: Defect Count · Bins at 5% (Pro) · Outlier filter: top 2% → Surfaces the two or three root causes responsible for most defects
Supplier concentration: Entity: Supplier Name · Value: Purchase Amount · Line 1 at 80% · Value labels on (Pro) → Quantifies supply chain risk at a glance