supply-chain-optimizer

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Supply chain analysis, inventory optimization, logistics planning, vendor evaluation, and demand forecasting frameworks. Use when analyzing supply chains, optimizing inventory, or evaluating suppliers.

travisjneuman By travisjneuman schedule Updated 2/10/2026

name: supply-chain-optimizer description: Supply chain analysis, inventory optimization, logistics planning, vendor evaluation, and demand forecasting frameworks. Use when analyzing supply chains, optimizing inventory, or evaluating suppliers.

Supply Chain Optimizer

Comprehensive frameworks for supply chain analysis, inventory management, logistics optimization, and vendor evaluation.

Supply Chain Mapping Template

End-to-End Supply Chain Map

RAW MATERIALS → SUPPLIERS → MANUFACTURING → DISTRIBUTION → CUSTOMER

MAPPING STEPS:
1. Identify all nodes (suppliers, plants, warehouses, customers)
2. Map material flows between nodes
3. Map information flows (orders, forecasts, POs)
4. Map financial flows (payments, invoicing)
5. Record lead times at each stage
6. Identify bottlenecks and single points of failure

NODE DETAIL TEMPLATE:
| Node           | Type       | Location  | Lead Time | Capacity | Utilization |
| -------------- | ---------- | --------- | --------- | -------- | ----------- |
|                | Supplier   |           |           |          |             |
|                | Plant      |           |           |          |             |
|                | Warehouse  |           |           |          |             |
|                | DC         |           |           |          |             |

Inventory Optimization

Economic Order Quantity (EOQ)

EOQ = sqrt(2DS / H)

Where: D = Annual demand, S = Ordering cost/order, H = Holding cost/unit/year
Total Cost = (D/Q)S + (Q/2)H + DC

Example: D=10,000, S=$50, H=$5 → EOQ = 447 units, 22.4 orders/year

Safety Stock & Reorder Point

SAFETY STOCK: SS = z x sigma_dLT
REORDER POINT: ROP = (Avg Daily Demand x Lead Time) + Safety Stock

SERVICE LEVEL FACTORS:
| Service Level | z-Score | Use Case          |
| ------------- | ------- | ----------------- |
| 90.0%         | 1.28    | Basic coverage    |
| 95.0%         | 1.65    | Standard          |
| 99.0%         | 2.33    | High service      |
| 99.9%         | 3.09    | Critical items    |

Inventory KPI Dashboard

Metric Formula Target
Inventory Turns COGS / Average Inventory Industry-specific
Days of Supply Average Inventory / (COGS / 365) Minimize
Fill Rate Orders Filled Complete / Total Orders 97%+
Stockout Rate Stockout Events / Total Demand Events < 2%
Carrying Cost % Holding Costs / Average Inventory Value 15-30%
Dead Stock % No-movement Items / Total SKUs < 5%
Inventory Accuracy Correct Counts / Total Counts 99%+
GMROI Gross Margin / Average Inventory Cost > 2.0

ABC-XYZ Analysis Framework

ABC CLASSIFICATION (Value):
A Items: Top 20% of SKUs = ~80% of annual consumption value
  → Tight control, frequent review, accurate forecasts
B Items: Next 30% of SKUs = ~15% of value
  → Moderate control, periodic review
C Items: Bottom 50% of SKUs = ~5% of value
  → Minimal control, simple replenishment rules

XYZ CLASSIFICATION (Demand Variability):
X: Coefficient of Variation < 0.5 → Stable, predictable demand
Y: CV between 0.5 and 1.0 → Some variation, trend/seasonal
Z: CV > 1.0 → Highly irregular, sporadic demand

COMBINED MATRIX:
| Class | AX         | AY           | AZ            |
| ----- | ---------- | ------------ | ------------- |
| Strat | JIT/Kanban | Forecast     | Order on demand|
| Class | BX         | BY           | BZ            |
| Strat | Reorder pt | Buffer stock | Min/Max       |
| Class | CX         | CY           | CZ            |
| Strat | Bulk buy   | Periodic rev | Eliminate?     |

Vendor Scorecard

Supplier Evaluation Matrix

Criteria Weight Score (1-5) Weighted Score Notes
Quality (PPM) 25%
Delivery (OTIF) 20%
Pricing 20%
Responsiveness 10%
Financial Health 10%
Innovation 5%
Sustainability 5%
Risk Profile 5%
Total 100% __ / 5.0
RATING SCALE:
4.5-5.0  Strategic Partner — expand relationship
3.5-4.4  Preferred Supplier — maintain, develop
2.5-3.4  Approved Supplier — improvement plan required
< 2.5    Probation / Exit — find alternative

Supplier Performance Tracking

KPI Target Q1 Actual Q2 Actual Q3 Actual Q4 Actual Trend
On-Time Delivery 98%+
Quality (PPM) < 500
Lead Time (days)
Price Variance +/- 2%
Response Time (hrs) < 24
Corrective Actions < 2/qtr

Total Cost of Ownership (TCO)

TCO = Acquisition Costs + Operating Costs + Disposal Costs

ACQUISITION COSTS:
  Purchase price
+ Shipping / freight
+ Customs / duties / tariffs
+ Procurement labor
+ Quality inspection
+ Supplier qualification
= Total Acquisition

OPERATING COSTS (over useful life):
  Maintenance & repair
+ Inventory carrying cost
+ Warranty claims
+ Downtime cost (if component fails)
+ Training / support
+ Quality failures (scrap, rework)
= Total Operating

DISPOSAL COSTS:
  Decommissioning
+ Recycling / disposal fees
+ Environmental compliance
= Total Disposal

TCO = Total Acquisition + Total Operating + Total Disposal

TCO Comparison Template

Cost Element Supplier A Supplier B Supplier C
Unit Price
Shipping
Duties / Tariffs
Quality Cost (est.)
Inventory Carry Cost
Lead Time Cost
Risk Premium
Total TCO/Unit
Annual TCO

Demand Forecasting Methods

Method Best For Horizon Data Required
Moving Average Stable demand Short-term 3-12 periods history
Exponential Smooth Trend detection Short-term Recent weighted data
Holt-Winters Seasonal patterns Medium-term 2+ years seasonal
Linear Regression Trend with causal factors Medium-term Demand + drivers
ARIMA Complex time series Short-medium 50+ data points
Machine Learning Multi-variable patterns Any Large datasets
Delphi / Expert New products, disruptions Long-term Expert panel

Forecast Accuracy Metrics

MAD (Mean Absolute Deviation):
MAD = (1/n) x SUM(|Actual - Forecast|)

MAPE (Mean Absolute Percentage Error):
MAPE = (1/n) x SUM(|Actual - Forecast| / Actual) x 100

BIAS (Tracking Signal):
Bias = SUM(Actual - Forecast) / MAD
Target: Between -4 and +4

ACCURACY BENCHMARKS:
| Forecast Horizon | Good MAPE | Acceptable MAPE |
| ---------------- | --------- | --------------- |
| 1 month          | < 15%     | < 25%           |
| 3 months         | < 25%     | < 35%           |
| 6 months         | < 30%     | < 45%           |
| 12 months        | < 35%     | < 50%           |

Logistics Optimization

Transportation Mode Selection

Mode Cost/Unit Speed Capacity Best For
Truck Medium Fast Medium Regional, door-to-door
Rail Low Slow Very High Bulk, long-distance domestic
Ocean Very Low Very Slow Very High International, bulk cargo
Air Very High Very Fast Low High-value, urgent, perishable
Intermodal Low-Med Medium High Long-distance, cost-effective

Warehouse Layout Optimization

SLOTTING STRATEGY:
Fast movers (A items) → Near shipping dock, prime pick locations
Medium movers (B items) → Middle zones
Slow movers (C items) → High racks, far locations

LAYOUT PRINCIPLES:
1. Minimize travel distance for highest-velocity items
2. Group items frequently ordered together
3. Separate receiving and shipping areas
4. Reserve staging areas for cross-docking
5. Maintain clear aisle widths for equipment

Lead Time Analysis

TOTAL LEAD TIME:
Order Processing Time
+ Supplier Manufacturing Time
+ Transportation Time
+ Receiving / Inspection Time
+ Internal Processing Time
= Total Lead Time

LEAD TIME VARIABILITY:
Track actual vs. quoted lead times over 12+ orders
Calculate standard deviation
Use for safety stock calculations

LEAD TIME REDUCTION STRATEGIES:
| Strategy              | Typical Reduction | Effort    |
| --------------------- | ----------------- | --------- |
| Vendor-managed inv.   | 30-50%            | Medium    |
| Local sourcing        | 40-70%            | High      |
| Process automation    | 10-30%            | Medium    |
| Blanket POs           | 20-40%            | Low       |
| Consignment stock     | 50-80%            | Medium    |
| 3PL consolidation     | 10-25%            | Low       |

Supply Chain Risk Assessment

Risk Identification Matrix

Risk Category Risk Event Likelihood Impact Score Mitigation
Supply Single-source failure Dual-source
Demand Demand spike/collapse Buffer stock, flex
Logistics Port congestion Alternate routes
Geopolitical Tariffs, sanctions Nearshoring
Natural Disaster Earthquake, flood Geographic diversity
Cyber System breach Security protocols
Quality Batch failure Inspection, redundancy
Financial Supplier bankruptcy Financial monitoring
RISK SCORING:
Likelihood: 1 (Rare) to 5 (Almost Certain)
Impact: 1 (Negligible) to 5 (Catastrophic)
Risk Score = Likelihood x Impact

ACTION THRESHOLDS:
20-25  Critical — immediate action, executive attention
12-19  High — mitigation plan required within 30 days
6-11   Medium — monitor quarterly, contingency plans
1-5    Low — accept or monitor annually

KPI Dashboard Template

Category KPI Target
Cost SC Cost as % of Revenue 5-10%
Cost Cost per Order Minimize
Service Perfect Order Rate 95%+
Service On-Time In-Full (OTIF) 98%+
Service Customer Fill Rate 97%+
Efficiency Inventory Turns Industry-specific
Efficiency Cash-to-Cash Cycle Minimize
Efficiency Warehouse Utilization 85%
Efficiency Forecast Accuracy (MAPE) < 20%

See Also

Install via CLI
npx skills add https://github.com/travisjneuman/.claude --skill supply-chain-optimizer
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