Pereto Analysis

business analytics

slug: topic-map-business-analytics-pereto-analysis

Vocabulary:

• pareto_principle: The 80/20 rule - often 80% of effects come from 20% of causes
• concentration: How much of the total is accounted for by the top segments
• cumulative_percentage: Running total of percentages as you move through ranked segments
• lorenz_curve: Graphical representation of cumulative distribution
• gini_coefficient: Statistical measure of inequality/concentration (0=perfect equality, 1=perfect inequality)
• top_decile: The top 10% of segments
• long_tail: The many small segments that individually contribute little but collectively matter
• abc_analysis: Categorizing segments into A (vital few), B (useful many), C (trivial many)
• herfindahl_index: Sum of squared market shares - measures market concentration
• tail_percentage: What portion of total comes from the bottom X%

Concepts:

• vital_few_vs_trivial_many: Small number of items drive most of the value
• inequality_measurement: Quantifying how unevenly distributed value is across segments
• rank_order_analysis: Sorting segments by contribution to identify top performers
• cumulative_thinking: Understanding progressive accumulation of value
• threshold_identification: Finding natural breakpoints for segment classification
• opportunity_sizing: Quantifying the value concentration in top segments
• long_tail_strategy: Whether to focus on head or tail of distribution
• portfolio_balance: Understanding if concentration is healthy or risky

Concepts_advanced:

• dynamic_concentration: How concentration changes over time (increasing/decreasing inequality)
• cross_dimensional_concentration: Is concentration higher in geography vs product category?
• pareto_efficiency: Optimal allocation where you can't improve one without hurting another
• concentration_risk: High concentration means vulnerability to loss of top segments

Procedures:

• rank_segments: Sort by measure value descending
• calculate_percentiles: Determine segment's position in distribution
• calculate_cumulative_values: Running sum of measure as you progress through ranks
• calculate_cumulative_percentages: Running sum of % of total
• identify_pareto_point: Find where cumulative % crosses key thresholds (80%, 90%)
• calculate_gini: Area between lorenz curve and diagonal / total area under diagonal
• classify_abc: Assign A/B/C categories based on cumulative contribution
• plot_lorenz_curve: Cumulative % of segments vs cumulative % of value
• calculate_concentration_ratios: Top 10%, top 25%, top 50% share of total

Procedures_detailed:

• gini_calculation: 1 - (Σ[(cumPct[i] + cumPct[i-1]) × (1/n)])
• pareto_percentage: Find n such that cumulative % >= 80% (or other threshold)
• herfindahl_calculation: Σ(share[i]²) where share is % of total for each segment
• abc_classification:
  • A: segments contributing to first 80% of cumulative value
  • B: segments contributing to next 15% (80-95%)
  • C: segments contributing to last 5% (95-100%)

Topics:

• customer_value_concentration
• product_portfolio_optimization
• inventory_management_prioritization
• sales_territory_analysis
• supplier_risk_assessment
• revenue_diversification
• resource_allocation_optimization
• quality_problem_prioritization
• market_share_distribution
• wealth_inequality_measurement

Categories:

• distribution_analysis
• inequality_metrics
• prioritization_frameworks
• risk_assessment
• strategic_focus

Themes:

• focus_on_vital_few: Concentrate resources where they matter most
• understand_distribution: Are results normally distributed or power-law?
• risk_vs_efficiency: High concentration is efficient but risky
• actionable_segmentation: ABC analysis drives different strategies for each tier

Trends:

• real_time_pareto: Live dashboards showing current concentration vs historical
• predictive_concentration: Forecasting how concentration will evolve
• multi_measure_pareto: Analyzing concentration across multiple measures simultaneously
• dynamic_abc: ABC classifications that automatically adjust based on contribution shifts
• concentration_alerts: Notifications when concentration crosses thresholds

Use_cases:

• retail: "Top 20% of products generate 85% of revenue (Gini=0.72) - focus inventory on A items"
• saas: "Top 15% of customers represent 90% of MRR - high concentration risk, need diversification"
• manufacturing: "Top 5 defect types cause 92% of quality issues - prioritize those fixes"
• banking: "Top 10% of accounts hold 95% of deposits - concentration exceeds risk tolerance"
• ecommerce: "Long tail (bottom 60% of products) contributes only 8% of sales - consider delisting"
• healthcare: "Top 20% of diagnoses account for 75% of costs - focus preventive care there"
• marketing: "Top 3 channels drive 88% of conversions - reallocate budget from underperformers"
• supply_chain: "Top 10 suppliers represent 70% of spend - develop backup suppliers for risk mitigation"