home / skills / a5c-ai / babysitter / supplier-scorecard-engine
This skill automates supplier performance scorecard generation, tracking KPIs, trends, and actionable insights to improve management of supplier performance.
npx playbooks add skill a5c-ai/babysitter --skill supplier-scorecard-engineReview the files below or copy the command above to add this skill to your agents.
---
name: supplier-scorecard-engine
description: Automated supplier performance scorecard generation with KPI tracking and trend analysis
allowed-tools:
- Read
- Write
- Glob
- Grep
- Bash
metadata:
specialization: supply-chain
domain: business
category: supplier-management
priority: high
---
# 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
```yaml
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
```yaml
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
1. Define clear KPI definitions and measurement methods
2. Establish data collection automation where possible
3. Calibrate weights based on category importance
4. Share scorecards with suppliers transparently
5. Link scorecard results to business allocation
6. Review weighting profiles annually
This skill automates supplier performance scorecard generation, consolidating KPIs into a weighted composite rating and actionable action items. It produces category-level scores (delivery, quality, cost, responsiveness, sustainability), trend insights, and benchmark comparisons to support supplier management and development.
The engine ingests period-specific performance data and a weighting profile, computes KPI metrics (e.g., OTIF, PPM, cost variance, resolution rate, ESG score), then normalizes and combines them into category scores and a composite score. It performs trend analysis across historical scorecards and benchmarks the supplier against peer data to surface strengths, declines, and priority action items.
What inputs are required to generate a scorecard?
Supply a supplier_id, evaluation period, structured performance data for delivery/quality/cost/responsiveness/sustainability, and an optional weighting profile and benchmark data.
How is the composite rating determined?
Category KPIs are normalized, weighted per the weighting profile, and summed into a composite score. The composite is mapped to a letter rating (A–F) using configurable thresholds.
Can trends and benchmarks be customized?
Yes. Trend windows (e.g., 3/6/12 months) and peer groups for benchmarking are configurable to fit your review cadence and comparator set.