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

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

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

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

Demand Forecasting Methods

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

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 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

See Also

• Operations
• Finance
• Risk Management