Babysitter supplier-scorecard-engine

Automated supplier performance scorecard generation with KPI tracking and trend analysis

install

source · Clone the upstream repo

git clone https://github.com/a5c-ai/babysitter

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/domains/business/supply-chain/skills/supplier-scorecard-engine" ~/.claude/skills/a5c-ai-babysitter-supplier-scorecard-engine && rm -rf "$T"

manifest: library/specializations/domains/business/supply-chain/skills/supplier-scorecard-engine/SKILL.md

Supplier Scorecard Engine

Overview

The Supplier Scorecard Engine automates the generation and maintenance of supplier performance scorecards. It aggregates performance data across multiple KPI categories, calculates weighted scores, tracks trends, and generates actionable insights for supplier management.

Capabilities

OTIF Calculation: On-Time In-Full delivery performance
Quality Metrics Aggregation: PPM, defect rate, inspection results
Cost Performance Tracking: Price variance, savings achievement
Responsiveness Scoring: Issue resolution, communication metrics
Sustainability/ESG Metrics: Environmental and social performance
Weighted Composite Scoring: Configurable weighting by category
Trend and Benchmark Analysis: Performance trending and peer comparison
Action Plan Tracking: Improvement initiative monitoring

Input Schema

scorecard_request:
  supplier_id: string
  evaluation_period:
    start_date: date
    end_date: date
  performance_data:
    delivery:
      orders_received: integer
      on_time: integer
      in_full: integer
    quality:
      units_received: integer
      defects: integer
      returns: integer
    cost:
      contracted_spend: float
      actual_spend: float
      savings_target: float
    responsiveness:
      issues_raised: integer
      issues_resolved: integer
      avg_resolution_time: float
    sustainability:
      certifications: array
      esg_score: float
  weighting_profile: object
  benchmark_data: object

Output Schema

scorecard_output:
  supplier_id: string
  period: object
  category_scores:
    delivery:
      otif_percent: float
      score: float
      trend: string
    quality:
      ppm: float
      score: float
      trend: string
    cost:
      variance_percent: float
      score: float
      trend: string
    responsiveness:
      resolution_rate: float
      score: float
      trend: string
    sustainability:
      score: float
      trend: string
  composite_score: float
  rating: string                    # A, B, C, D, F
  benchmark_comparison: object
  action_items: array
  trend_analysis: object

Usage

Monthly Scorecard Generation

Input: Previous month's delivery, quality, cost data
Process: Calculate KPIs, apply weights, generate score
Output: Comprehensive supplier scorecard with rating

Trend Analysis

Input: 12 months of scorecard history
Process: Analyze performance trajectory by category
Output: Trend report with improvement/decline identification

Benchmark Comparison

Input: Supplier scorecard, peer group data
Process: Compare against category averages and best-in-class
Output: Relative performance positioning

Integration Points

ERP Systems: Purchase orders, receipts, quality data
Quality Systems: Inspection results, NCRs
BI Platforms: Scorecard visualization and distribution
Tools/Libraries: Scorecard templates, analytics frameworks

Process Dependencies

Supplier Performance Scorecard
Quarterly Business Review (QBR) Facilitation
Supplier Development Program

Best Practices

Define clear KPI definitions and measurement methods
Establish data collection automation where possible
Calibrate weights based on category importance
Share scorecards with suppliers transparently
Link scorecard results to business allocation
Review weighting profiles annually