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logistics-kpi-tracker

Habilidade abrangente de medição de desempenho logístico com rastreamento de KPIs, benchmarking e recomendações de melhoria.

1.4kestrelas
Atualizado há 4 meses

Ver no GitHub ↗ Licença: MIT

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Logistics KPI Tracker

Overview

The Logistics KPI Tracker provides comprehensive logistics performance measurement with KPI tracking, benchmarking, and improvement recommendations. It monitors key metrics across all logistics functions and identifies opportunities for operational improvement.

Capabilities

  • OTIF (On-Time In-Full) Tracking: Track on-time and in-full delivery performance against commitments
  • Perfect Order Rate Calculation: Calculate perfect order rates considering all order fulfillment dimensions
  • Fill Rate Analysis: Monitor fill rates at order, line, and unit levels
  • Order Cycle Time Measurement: Track order cycle times from order placement to delivery
  • Cost Per Order/Unit Tracking: Calculate and monitor logistics costs at various levels
  • Benchmark Comparison: Compare performance against industry benchmarks and best practices
  • Improvement Opportunity Identification: Identify areas for operational improvement based on KPI analysis

Tools and Libraries

  • BI Platforms (Tableau, Power BI)
  • Data Warehousing
  • Logistics Dashboards
  • Statistical Analysis Libraries

Used By Processes

  • All logistics processes (cross-cutting)

Usage

skill: logistics-kpi-tracker
inputs:
  reporting_period:
    start: "2026-01-01"
    end: "2026-01-24"
  data_sources:
    orders: true
    shipments: true
    inventory: true
    costs: true
  benchmarks:
    otif: 95.0
    perfect_order_rate: 90.0
    fill_rate: 98.0
    order_cycle_time_days: 3.0
    cost_per_order: 12.50
  comparison:
    prior_period: true
    prior_year: true
outputs:
  kpi_summary:
    otif:
      actual: 93.5
      target: 95.0
      variance: -1.5
      trend: "improving"
      prior_period: 92.8
      prior_year: 91.2
    perfect_order_rate:
      actual: 88.2
      target: 90.0
      variance: -1.8
      trend: "stable"
      components:
        on_time: 93.5
        in_full: 96.2
        damage_free: 99.1
        accurate_documentation: 98.5
    fill_rate:
      actual: 97.5
      target: 98.0
      variance: -0.5
      trend: "stable"
    order_cycle_time:
      actual_days: 2.8
      target_days: 3.0
      variance: 0.2
      trend: "improving"
    cost_per_order:
      actual: 11.85
      target: 12.50
      variance: 0.65
      trend: "improving"
  performance_breakdown:
    by_channel:
      ecommerce: { otif: 91.2, fill_rate: 96.8 }
      wholesale: { otif: 95.8, fill_rate: 98.2 }
      retail: { otif: 94.1, fill_rate: 97.8 }
    by_region:
      northeast: { otif: 94.5, fill_rate: 98.1 }
      southeast: { otif: 92.8, fill_rate: 97.0 }
      midwest: { otif: 93.9, fill_rate: 97.5 }
  improvement_opportunities:
    - area: "On-Time Delivery"
      current: 93.5
      target: 95.0
      gap: 1.5
      root_causes:
        - "Carrier performance in Southeast region"
        - "Dock congestion at DC002"
      recommendations:
        - "Carrier performance review with underperformers"
        - "Implement dock scheduling system at DC002"
      potential_improvement: 2.0
    - area: "Fill Rate"
      current: 97.5
      target: 98.0
      gap: 0.5
      root_causes:
        - "Safety stock levels insufficient for high-velocity items"
      recommendations:
        - "Review and adjust safety stock for A-class items"
      potential_improvement: 0.8

Integration Points

  • Enterprise Resource Planning (ERP)
  • Warehouse Management Systems (WMS)
  • Transportation Management Systems (TMS)
  • Order Management Systems
  • Business Intelligence Platforms

Performance Metrics

  • OTIF percentage
  • Perfect order rate
  • Fill rate
  • Order cycle time
  • Cost per order
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