Biz Supply Chain Agent Skill

Supply Chain Analysis (SCOR Model)

Overview

The SCOR (Supply Chain Operations Reference) model structures supply chain analysis into five core processes: Plan, Source, Make, Deliver, Return. It provides a common language for analyzing, benchmarking, and improving supply chain performance from supplier's supplier to customer's customer.

Framework

IRON LAW: End-to-End, Not Silo-by-Silo

Supply chain optimization must consider the ENTIRE chain. Optimizing
procurement (Source) without considering production capacity (Make) or
delivery capability (Deliver) creates bottlenecks downstream.

A local optimum in one process often creates a global problem elsewhere.

The Five SCOR Processes

1. Plan — Demand forecasting, supply planning, inventory strategy

• Demand forecast accuracy, S&OP process, inventory policies
• Question: "Do we make/buy the right amount at the right time?"

2. Source — Supplier selection, procurement, incoming quality

• Supplier scorecards, lead times, sourcing strategy (single vs multi)
• Question: "Are we getting the right inputs at the right cost and quality?"

3. Make — Production, assembly, manufacturing

• Production scheduling, capacity utilization, quality control, WIP management
• Question: "Are we converting inputs to outputs efficiently?"

4. Deliver — Order management, warehousing, transportation, last-mile

• Order fulfillment rate, delivery speed, logistics cost, channel management
• Question: "Are we getting products to customers reliably and affordably?"

5. Return — Returns processing, reverse logistics, warranty/repair

• Return rate, reverse logistics cost, refurbishment, disposal
• Question: "Are we handling returns efficiently and learning from them?"

Key Supply Chain Metrics

| Process | Metric | Formula/Definition |

|---------|--------|-------------------|

| Plan | Forecast Accuracy | 1 - \|Actual - Forecast\| / Actual |

| Plan | Inventory Days | Inventory / (COGS / 365) |

| Source | Supplier On-Time Rate | On-time deliveries / Total deliveries |

| Source | Supplier Defect Rate | Defective units / Total received |

| Make | OEE | Availability × Performance × Quality |

| Deliver | Perfect Order Rate | Orders delivered on time, in full, without error |

| Deliver | Order-to-Delivery Cycle | Time from order to customer receipt |

| Return | Return Rate | Returns / Total shipments |

Analysis Steps

• Map the current supply chain from supplier to customer
• Measure key metrics per SCOR process
• Benchmark against industry standards
• Identify the weakest process (highest gap to benchmark)
• Improve the weakest link first (same logic as TOC — chain is as strong as weakest link)

Output Format

# Supply Chain Analysis: {Company}

## Supply Chain Map
Supplier → [Source] → [Make] → [Deliver] → Customer
            ↑ [Plan] (coordinates all) ↑
                     [Return] ←

## SCOR Performance Dashboard
| Process | Key Metric | Current | Benchmark | Gap |
|---------|-----------|---------|-----------|-----|
| Plan | Forecast Accuracy | X% | 85%+ | {gap} |
| Source | Supplier On-Time | X% | 95%+ | {gap} |
| Make | OEE | X% | 85%+ | {gap} |
| Deliver | Perfect Order Rate | X% | 95%+ | {gap} |
| Return | Return Rate | X% | <5% | {gap} |

## Weakest Link Analysis
{Which process has the largest gap and why}

## Improvement Recommendations
1. {Process}: {specific improvement} → {expected metric impact}

Examples

Correct Application

Scenario: SCOR analysis for a Taiwanese DTC electronics brand

| Process | Metric | Current | Issue |

|---------|--------|---------|-------|

| Plan | Forecast Accuracy | 62% | Demand spikes around promotions are unpredicted |

| Source | Supplier On-Time | 88% | Key component supplier in Shenzhen has inconsistent lead times |

| Make | OEE | 78% | Reasonable for electronics assembly |

| Deliver | Perfect Order Rate | 91% | Last-mile carrier (���貓) loses 3% of packages |

| Weakest: Plan (62%) — fixing forecast accuracy would reduce both inventory (currently 45 days, target 30) and stockouts

Incorrect Application

• Only analyzed Deliver (logistics) because "delivery is our biggest complaint" → Root cause was Plan (bad forecast → stockouts → backorders → late deliveries). Fixing delivery alone doesn't help. Violates Iron Law: end-to-end analysis.

Gotchas

• Bullwhip effect: Small demand changes at retail amplify upstream. A 10% sales increase can trigger 40% production increase at the manufacturer. S&OP process mitigates this.
• Single-source risk: One supplier = zero redundancy. The 2021 chip shortage proved this globally. Evaluate single-source dependencies explicitly.
• Make-vs-Buy is a Source decision: Not just cost — consider IP protection, quality control, lead time, and supply security.
• Last-mile is often the costliest: Last-mile delivery can be 40-50% of total logistics cost. Evaluate delivery model (own fleet vs 3PL vs pickup points).
• Returns are a profit leak: Many companies treat returns as an afterthought. A 15% return rate in e-commerce means 15% of fulfillment cost is wasted plus reverse logistics cost.

References

• For SCOR model detailed metrics, see references/scor-metrics.md
• For inventory optimization methods, see references/inventory-models.md