Pareto analysis to identify the vital few segments

business analytics

slug: recipe-business-analytics-pareto-analysis-to-identify-the-vital-few-segments

Recipe: Pareto analysis to identify the vital few segments

category: business analytics

Problem

You need to identify the segments that drive the majority of value:

• Find top-performing product categories, customers, or regions
• Allocate resources to the highest-impact areas
• Understand concentration risks and distribution of contributions
• Support executive decision-making with clear prioritization

Solution

Follow these steps to perform Pareto analysis:

• build a cube using cube step to aggregate metrics across dimensions
• apply pareto step specifying the measure and metric
• optionally filter or rank to focus on top contributors
• visualize results to communicate insights effectively

Step Sequence

cube step -> pareto step -> chart step

Input Datasets

• sales_cube — aggregated dataset from cube step
• Notes: must contain the measure column in measure.metric format and optionally a 'level' column for hierarchical analysis

Output Dataset

• pareto_analysis — dataset with segments ranked by contribution
• Key columns: rank, segmentPct, cumulativePct, abcCategory, paretoFlag
• Extras: statistical summary stored in extras.stats.pareto including Gini coefficient, concentration ratios, and category counts

Step-By-Step Explanation

Step	Purpose	Notes
cube step	Aggregate metrics across dimensions	Example: total revenue by product × region × quarter
pareto step	Identify top segments driving most of the value	Example: top 80% of revenue contributors (A category)
chart step	Visualize Pareto distribution	Optional bar chart, cumulative curve, or ABC chart

Variations & Extensions

• Adjust paretoThresholds to analyze 70/80/90/95% thresholds
• Customize abcBreakpoints to redefine categories based on business rules
• Combine with filter step to focus on specific dimensions (e.g., region or product line)
• Integrate with dashboards or executive reports

Concepts Demonstrated

• Pareto principle and ABC analysis
• Concentration metrics and Gini coefficient
• Ranking and prioritization of segments
• Sequencing analytics from cube aggregation to insight

Related Recipes

• Multi-dimensional analysis using cubes
• Contribution analysis using contribution step
• Index analysis using index step

Notes & Best Practices

• Input data should be pre-aggregated (cube step) for accurate analysis
• Verify measure and metric formatting (measure.metric)
• Document thresholds and ABC breakpoints for reproducibility
• Visualize both absolute and cumulative contribution for clarity

Metadata

title: "Pareto analysis to identify the vital few segments"
category: "business analytics"
difficulty: "Intermediate"
tags: [pareto, cube, ABC, prioritization, analytics]
inputs: [sales_cube]
outputs: [pareto_analysis]
steps: [step-cube, step-pareto, step-chart]
author: "Tom Argiro"
last_updated: "2025-10-25"
doc_type: "recipe"