abc-xyz-classifier

name	abc-xyz-classifier
description	Multi-dimensional inventory classification skill combining value (ABC) and demand variability (XYZ) analysis for differentiated policies
allowed-tools	["Read","Write","Glob","Grep","Bash","WebFetch"]
metadata	{"specialization":"logistics","domain":"business","category":"inventory","priority":"high"}
graph	{"domains":["domain:logistics"],"skillAreas":["skill-area:procurement-management","skill-area:data-analytics","skill-area:statistical-analysis"],"roles":["role:supply-chain-analyst","role:operations-analyst","role:procurement-manager"]}

ABC-XYZ Classifier

Overview

The ABC-XYZ Classifier is a multi-dimensional inventory classification skill that combines value-based (ABC) and demand variability (XYZ) analysis to enable differentiated inventory policies. It automates Pareto analysis and demand pattern classification to recommend optimal stocking strategies, service levels, and review frequencies.

Capabilities

• Pareto Analysis Automation: Automatically classify inventory into A, B, C categories based on value contribution using Pareto principles
• Demand Pattern Classification: Analyze demand variability to classify items as X (stable), Y (variable), or Z (erratic)
• Inventory Policy Recommendation: Recommend appropriate inventory policies based on combined ABC-XYZ classification
• Service Level Differentiation: Suggest differentiated service level targets based on item classification and business importance
• Review Frequency Optimization: Determine optimal inventory review frequencies for each classification
• Stocking Strategy Suggestions: Recommend make-to-stock, make-to-order, or hybrid strategies based on classification
• Cross-Docking Candidacy Identification: Identify items suitable for cross-docking based on velocity and predictability

Tools and Libraries

• Statistical Analysis Libraries (pandas, numpy)
• Inventory Optimization Models
• Data Visualization Libraries
• Classification Algorithms

Used By Processes

• ABC-XYZ Analysis
• Reorder Point Calculation
• Dead Stock and Excess Inventory Management

Usage

skill: abc-xyz-classifier
inputs:
  inventory_data:
    - sku: "SKU001"
      annual_value: 150000
      monthly_demand: [100, 98, 102, 99, 101, 100, 98, 103, 99, 100, 101, 99]
      unit_cost: 125
    - sku: "SKU002"
      annual_value: 45000
      monthly_demand: [50, 75, 30, 60, 45, 80, 35, 55, 70, 40, 65, 50]
      unit_cost: 75
  classification_parameters:
    abc_thresholds:
      A: 80  # Top 80% of value
      B: 95  # Next 15% of value
    xyz_thresholds:
      X: 20  # CV < 20%
      Y:   

  
      
       
       
       
       
       
       
      
         
         
         
         
      
       
       
       
       
       
       
      
         
         
         
         
  
     
     
     
     
     
     

Integration Points

• Enterprise Resource Planning (ERP) Systems
• Inventory Management Systems
• Demand Planning Systems
• Warehouse Management Systems (WMS)
• Financial Systems

Performance Metrics

• Classification accuracy
• Policy compliance rate
• Service level achievement by class
• Inventory investment by class
• Turn rate by class