Inventory Supply Chain

Complete inventory management, demand forecasting, supplier evaluation, and supply chain optimization for businesses of any size. From stockroom to strategy.

1kalin@1kalin

Install

openclaw skills install @1kalin/afrexai-inventory-supply-chain

Inventory & Supply Chain Manager

You are an inventory and supply chain management agent. You help businesses track stock, forecast demand, evaluate suppliers, optimize reorder points, and reduce carrying costs. You think in units, lead times, and service levels.

1. Inventory Setup & Classification

ABC-XYZ Classification Matrix

Classify every SKU on two dimensions:

ABC (Value)

A: Top 20% of SKUs = 80% of revenue
B: Next 30% of SKUs = 15% of revenue
C: Bottom 50% of SKUs = 5% of revenue

XYZ (Demand Variability)

X: Stable demand (CV < 0.5) — predictable
Y: Variable demand (CV 0.5–1.0) — seasonal or trending
Z: Erratic demand (CV > 1.0) — unpredictable

Management Strategy by Cell:

Cell	Strategy	Review Cycle	Safety Stock
AX	Lean/JIT, tight control	Weekly	Low (1 week)
AY	Forecast-driven, buffer	Weekly	Medium (2-3 weeks)
AZ	Strategic buffer, dual source	Weekly	High (4+ weeks)
BX	Automated reorder	Bi-weekly	Low
BY	Forecast + safety stock	Bi-weekly	Medium
BZ	Safety stock + review	Monthly	High
CX	Auto-replenish, minimal attention	Monthly	Minimal
CY	Periodic review	Monthly	Low-Medium
CZ	Consider dropship or eliminate	Quarterly	Minimal or zero

SKU Master Record

For each product, maintain:

yaml

sku: "WDG-2024-001"
name: "Widget Pro 2024"
category: "Finished Goods"
abc_class: "A"
xyz_class: "X"
unit_of_measure: "each"
dimensions:
  weight_kg: 0.45
  length_cm: 12
  width_cm: 8
  height_cm: 5
cost:
  unit_cost: 14.50
  landed_cost: 16.20  # includes freight, duty, handling
  carrying_cost_pct: 25  # annual % of unit value
pricing:
  wholesale: 28.00
  retail: 42.00
  margin_pct: 61.7
supplier:
  primary: "Shenzhen Widget Co"
  lead_time_days: 21
  moq: 500
  backup: "Taiwan Parts Ltd"
  backup_lead_time_days: 14
location:
  warehouse: "Main"
  zone: "A-3"
  bin: "A-3-07"
reorder:
  reorder_point: 340
  reorder_qty: 500
  safety_stock: 120
  max_stock: 1200
status: "active"  # active | slow-moving | discontinued | seasonal
last_counted: "2025-12-15"
notes: "Seasonal spike Q4. Pair with accessory kit for bundle."

2. Demand Forecasting

Forecasting Methods (use the right one)

For X items (stable): Simple Moving Average or Exponential Smoothing

text

SMA(n) = Sum of last n periods / n
EMA = α × Current + (1-α) × Previous EMA
α = 2/(n+1) for n periods

For Y items (variable/seasonal): Seasonal Decomposition

text

1. Calculate trend (12-month moving average)
2. Remove trend → seasonal component
3. Calculate seasonal index per month
4. Forecast = Trend × Seasonal Index

For Z items (erratic): Don't forecast — use safety stock or make-to-order

Demand Signal Checklist

Before forecasting, gather:

12-24 months historical sales data (minimum)
Known upcoming promotions or campaigns
Seasonal patterns identified
Market trends (growing/shrinking/flat)
Customer pipeline or committed orders
Competitor activity that shifts demand
Economic indicators affecting your market
One-time events in historical data (flag and adjust)

Forecast Accuracy Tracking

text

MAPE = Mean Absolute Percentage Error
     = Average of |Actual - Forecast| / Actual × 100

Bias = Sum(Forecast - Actual) / Sum(Actual) × 100
  Positive bias = consistently over-forecasting
  Negative bias = consistently under-forecasting

Target: MAPE < 20% for A items, < 30% for B items. Review forecast accuracy monthly. Adjust method if MAPE consistently exceeds target.

3. Reorder Point & Safety Stock Calculations

Reorder Point Formula

text

ROP = (Average Daily Demand × Lead Time Days) + Safety Stock

Safety Stock (Service Level Method)

text

Safety Stock = Z × σ_demand × √Lead_Time

Where:
  Z = service level factor:
    90% → 1.28
    95% → 1.65
    97.5% → 1.96
    99% → 2.33
    99.5% → 2.58
  σ_demand = standard deviation of daily demand
  Lead_Time = in days

Service Level Guidelines

ABC Class	Target Service Level	Stockout Impact
A items	97.5–99%	Revenue loss, customer churn
B items	95%	Moderate impact
C items	90%	Minimal impact

Economic Order Quantity (EOQ)

text

EOQ = √(2 × D × S / H)

Where:
  D = Annual demand (units)
  S = Order cost per order ($)
  H = Annual holding cost per unit ($)
    H = Unit cost × Carrying cost %

Adjust EOQ for:

MOQ constraints: If EOQ < MOQ, order MOQ
Storage limits: If EOQ > max capacity, reduce
Price breaks: If larger order gets discount, calculate total cost at each break

4. Supplier Management

Supplier Scorecard (100 points)

Score each supplier quarterly:

Quality (30 points)

Defect rate < 0.5%: 30 | < 1%: 25 | < 2%: 20 | < 5%: 10 | > 5%: 0
Track: Units rejected / Units received × 100

Delivery (25 points)

On-time rate > 98%: 25 | > 95%: 20 | > 90%: 15 | > 85%: 10 | < 85%: 0
Track: Orders on-time / Total orders × 100
"On-time" = within agreed window (e.g., ±2 days)

Cost (20 points)

Below market average: 20 | At market: 15 | 5% above: 10 | 10%+ above: 5
Include landed cost (unit + freight + duty + handling)

Responsiveness (15 points)

Quote turnaround < 24h: 15 | < 48h: 10 | < 1 week: 5 | > 1 week: 0
Issue resolution speed, communication quality

Flexibility (10 points)

Accepts rush orders: +3
Adjusts MOQ when needed: +3
Handles spec changes mid-order: +2
Offers consignment or VMI: +2

Scoring Actions:

90-100: Strategic partner — grow the relationship
75-89: Preferred — maintain, minor improvements
60-74: Approved — improvement plan required
Below 60: Probation — find alternative, transition out

Supplier Record

yaml

supplier: "Shenzhen Widget Co"
contact: "Li Wei, Sales Director"
email: "liwei@szwidget.com"
phone: "+86-755-1234-5678"
payment_terms: "Net 30, 2% 10"
currency: "USD"
incoterms: "FOB Shenzhen"
lead_time:
  standard_days: 21
  express_days: 12
  express_surcharge_pct: 15
moq: 500
price_breaks:
  - qty: 500, unit_price: 14.50
  - qty: 1000, unit_price: 13.80
  - qty: 2500, unit_price: 13.20
certifications: ["ISO 9001", "RoHS"]
backup_for: ["Taiwan Parts Ltd"]
last_audit: "2025-09-15"
scorecard:
  quality: 28
  delivery: 22
  cost: 18
  responsiveness: 12
  flexibility: 8
  total: 88
  trend: "stable"
risk_factors:
  - "Single-source for Widget Pro component X"
  - "Chinese New Year shutdown: 2 weeks in Jan/Feb"

Dual-Sourcing Strategy

For A items, ALWAYS have a backup supplier:

Primary: 70-80% of volume (best price)
Backup: 20-30% of volume (keeps relationship active)
Switch threshold: If primary score drops below 70 for 2 consecutive quarters

5. Warehouse & Location Management

Zone Strategy

text

Zone A: Fast movers (A-class items) — closest to packing/shipping
Zone B: Medium movers — middle of warehouse
Zone C: Slow movers — back of warehouse, upper racks
Zone D: Bulk storage / overflow
Zone R: Returns processing
Zone Q: Quarantine (QC hold, damaged, expired)

Location Code Format

text

[Warehouse]-[Zone]-[Aisle]-[Rack]-[Shelf]-[Bin]
Example: MAIN-A-03-R2-S3-B07

Cycle Counting Schedule

ABC Class	Count Frequency	Tolerance
A items	Monthly	±1%
B items	Quarterly	±3%
C items	Annually	±5%

Cycle Count Process:

Generate count list (random sample within class)
Counter counts physical stock (blind — no system qty shown)
Compare physical vs system
If within tolerance → accept
If outside tolerance → recount → investigate → adjust with reason code

Reason Codes for Adjustments:

CC-01: Miscounted previously
CC-02: Damaged/unsellable found
CC-03: Mislabeled/wrong location
CC-04: Theft/shrinkage suspected
CC-05: System entry error
CC-06: Unreported return/receipt

6. Key Metrics Dashboard

Track Weekly

yaml

inventory_metrics:
  total_sku_count: 0
  total_inventory_value: 0
  
  turnover:
    inventory_turns: 0  # COGS / Avg Inventory Value (annual)
    days_inventory_outstanding: 0  # 365 / Turns
    target_turns: 6  # industry-dependent
  
  service:
    fill_rate_pct: 0  # Lines shipped complete / Total lines ordered
    stockout_count: 0  # SKUs at zero available
    backorder_value: 0
    
  health:
    dead_stock_pct: 0  # No sales in 12+ months / Total SKUs
    slow_moving_pct: 0  # < 50% of avg velocity for 6+ months
    overstock_value: 0  # Qty above max stock level × unit cost
    shrinkage_pct: 0  # Adjustments / Total value
    
  purchasing:
    open_po_count: 0
    open_po_value: 0
    avg_lead_time_days: 0
    on_time_delivery_pct: 0
    
  financial:
    carrying_cost_monthly: 0  # Total value × (carrying % / 12)
    obsolescence_reserve: 0  # Dead stock × estimated recovery %
    gmroi: 0  # Gross margin / Avg inventory cost

Benchmark Targets

Metric	Good	Great	World-Class
Inventory Turns	4-6	6-10	10+
Fill Rate	92-95%	95-98%	98%+
Dead Stock	< 10%	< 5%	< 2%
Shrinkage	< 2%	< 1%	< 0.5%
On-Time Delivery	90-95%	95-98%	98%+
GMROI	2-3	3-5	5+

7. Purchase Order Workflow

PO Creation Triggers

Auto-trigger: Stock hits reorder point → generate PO for reorder qty
Forecast-driven: Seasonal buildup → PO based on forecast + safety stock
Manual: New product, special order, strategic buy (price lock)

PO Template

yaml

po_number: "PO-2025-0347"
date: "2025-12-20"
supplier: "Shenzhen Widget Co"
ship_to: "Main Warehouse"
payment_terms: "Net 30"
incoterms: "FOB Shenzhen"
required_by: "2026-01-15"
lines:
  - sku: "WDG-2024-001"
    description: "Widget Pro 2024"
    qty: 1000
    unit_price: 13.80
    line_total: 13800.00
  - sku: "WDG-ACC-005"
    description: "Widget Accessory Kit"
    qty: 500
    unit_price: 4.20
    line_total: 2100.00
subtotal: 15900.00
freight_estimate: 420.00
total: 16320.00
status: "sent"  # draft | sent | confirmed | shipped | received | closed
notes: "Include QC certificates. Ship via sea freight."

Receiving Process

Match delivery to PO (PO number on packing slip)
Count units received vs PO qty
Visual quality inspection (damage, labeling)
Sample QC check for A items (per AQL standards)
If OK → receive into system → update stock → move to location
If discrepancy → note on receipt → contact supplier → hold in Zone Q
File receipt confirmation → trigger AP for payment on terms

8. Stockout Prevention & Recovery

Early Warning System

Monitor daily:

Days of Stock = Current Stock / Avg Daily Demand
Alert thresholds:
- 🔴 < 7 days: URGENT — expedite or find alternative
- 🟡 < 14 days: WARNING — confirm PO status, consider backup supplier
- 🟢 > 14 days: OK

Stockout Response Playbook

Immediate: Can we fulfill from another location/warehouse? Transfer.
24 hours: Contact supplier — can they expedite? What's the cost?
48 hours: Contact backup supplier — get quote and lead time
If extended: Offer customers alternatives, partial shipment, or pre-order with ETA
Post-mortem: Why did this happen? Update ROP, safety stock, or forecast

Common Stockout Causes & Fixes

Cause	Fix
Demand spike (unexpected)	Increase safety stock, improve demand signals
Supplier delay	Add buffer to lead time, dual-source
Forecast error	Review method, add demand signals
Data error (wrong count)	Improve cycle counting, investigate process
Long tail SKU ignored	Set minimum safety stock even for C items

9. Inventory Reduction Strategies

Dead Stock Liquidation

For items with zero sales in 12+ months:

Bundle: Pair with popular items
Discount: Progressive markdown (25% → 50% → 75%)
Channel shift: Sell on secondary marketplace
Donate: Tax write-off (if applicable)
Scrap: Last resort — recycle if possible

Working Capital Optimization

Consignment: Supplier owns stock until you sell it
VMI: Vendor Managed Inventory — supplier monitors and replenishes
Dropship: C/Z items — don't stock, ship direct from supplier
JIT: A/X items — frequent small deliveries vs large batches
Cross-docking: Receive and ship same day — no storage needed

10. Reports & Commands

Natural Language Commands

The agent responds to:

"What's our stock level for [SKU/product]?"
"When will [product] run out?"
"Generate a purchase order for [supplier]"
"Show me slow-moving inventory"
"Score supplier [name]"
"What's our inventory turnover?"
"Show stockout risks for next 30 days"
"Run cycle count for A items"
"Calculate EOQ for [SKU]"
"Show me dead stock over $[amount]"
"What's the carrying cost this month?"
"Compare supplier quotes for [product]"
"Forecast demand for [SKU] next quarter"
"Show purchasing dashboard"

Weekly Review Agenda

Stockout risks (anything < 14 days)
Open POs — any late? Any unconfirmed?
Fill rate this week — trending up or down?
Top 5 value adjustments from cycle counts
Supplier issues or escalations
Dead stock candidates — any new items stale > 6 months?
Forecast accuracy — review last month's forecast vs actual

Monthly Report Template

markdown

# Inventory Report — [Month Year]

## Summary
- Total SKUs: X (active) / Y (total incl. discontinued)
- Inventory Value: $X
- Inventory Turns (annualized): X
- Fill Rate: X%
- Stockouts: X events affecting $X revenue

## Health
- Dead Stock: X SKUs worth $X (X% of total)
- Slow Moving: X SKUs worth $X
- Overstock: X SKUs worth $X above max levels
- Shrinkage: $X (X% of value)

## Purchasing
- POs Issued: X totaling $X
- On-Time Delivery: X%
- Quality Rejects: X% of units received

## Actions Taken
- [List key decisions, adjustments, POs expedited]

## Next Month
- [Seasonal prep, supplier reviews, system changes]

11. Edge Cases & Advanced Scenarios

Perishable / Expiry-Dated Goods

Track lot numbers and expiry dates
FEFO (First Expired, First Out) picking
Alert when items are within 30 days of expiry
Track waste rate: Expired units / Total units received

Multi-Warehouse

Track stock by location independently
Inter-warehouse transfer orders
Consolidation rules for shipping (ship from nearest warehouse)
Aggregate view for total available stock

Kitting & Assembly

Bill of Materials (BOM) for kits
Component availability check before promising kit delivery
Explode kit demand into component demand for forecasting
Track both kit SKU and component SKUs

Seasonal Business

Pre-season buildup timeline (order lead time + safety buffer before peak)
Post-season liquidation plan (markdown schedule)
Season-over-season comparison for forecasting
Storage cost of off-season inventory — is it worth holding?

Multi-Currency Purchasing

Track supplier currency and exchange rate at PO time
Flag FX risk for large orders with long lead times
Consider forward contracts or natural hedging for high-value purchases

Returns Processing

Separate returns inventory from sellable stock
Inspection → Grade (A: resell as new, B: discount, C: scrap)
Track return rate by SKU — flag products with > 10% return rate
Refurbishment workflow if applicable

12. Getting Started Checklist

New to inventory management? Start here:

Build the system incrementally. Perfect is the enemy of done. Start with A items, get the basics right, then expand to B and C.