Reorder Point Automation Tool — Chibuike Dialaekwe

// inventory health

Reorder Point Dashboard KPIs

// analysis

Inventory Position Analytics

Current Stock vs Reorder Point — All SKUs

Green bars = stock above ROP (safe) · Amber = within 20% of ROP (order soon) · Red = below ROP (order now)

Safety Stock Distribution by SKU

Safety stock buffer required per SKU based on demand volatility and lead time variance

Stockout Risk by Service Level Tier

SKU count and average days-of-coverage by service level target across the portfolio

Avg Lead Time vs Reorder Point (Days)

Relationship between supplier lead time and calculated ROP — longer lead times drive higher reorder thresholds

60-Day Stock Depletion Curve

Select a SKU to view its projected stock trajectory, reorder trigger, and safety stock floor

SKU:

// raw data

📊 Raw Dataset

Dynamic reorder parameters for 60 SKUs — 50 shown. Red rows = reorder required now. Download full dataset below.

SKU ID	Product Name	Avg Daily Demand	Demand σ	Avg LT (days)	LT σ	Service Level	Z-Score	Safety Stock	ROP	Current Stock	PO Required	Suggest Qty

// methodology

Problem → Solution → Findings

🔴▶ PROBLEM

Static reorder points were set once during ERP implementation and never updated — 43% of SKUs had reorder points based on demand data more than 18 months old, leading to systematic under-ordering in growing lines
Safety stock calculations used a flat buffer of "2 weeks demand" across all products regardless of demand volatility, lead time variance, or service level requirements — over-stocking slow movers and under-buffering volatile fast movers simultaneously
Planners received no automated alert when stock fell below reorder point — the first indication was a stockout notification from the warehouse, by which point it was already too late to avoid a service failure
Suggested order quantities were calculated manually in Excel without considering economic order quantities, moq constraints, or lead time coverage — resulting in either under-ordering (requiring emergency top-ups) or over-ordering (inflating working capital)

🔵▶ SOLUTION

Dynamic ROP formula: ROP = (AvgDemand × AvgLT) + Z × √(LT × σD² + D² × σLT²) — recalculates automatically when either demand or lead time data is refreshed from the ERP
Service level Z-scores applied per SKU tier: A-class products at 99% (Z=2.33), B-class at 97.5% (Z=1.96), C-class at 95% (Z=1.65) — aligning buffer investment with product revenue contribution
Colour-coded daily reorder alert list generated at 07:00 each morning: red = PO required today, amber = PO required within 5 days, green = stock adequate — pushed to buyers via email and Teams notification
Suggested order quantity includes minimum order quantity constraints, economic order quantity guidance, and lead time coverage calculation to prevent both under and over-ordering

🟢▶ FINDINGS

Dynamic ROP recalculation reduced stockout frequency by 38% in the first quarter — primarily by catching 14 SKUs where demand had grown 40%+ but static ROPs had not been updated
ABC-tiered service levels freed up €67,000 in working capital previously tied in excess safety stock on slow-moving C-class products that had been over-buffered at the same rate as A-class SKUs
Automated morning alert removed the need for planners to manually query the ERP each day — saving 1.5 hours per planner per day across a team of 4 buyers, equivalent to 3 FTE-weeks per month
Emergency purchase order frequency fell from 23/month to 6/month — reducing premium freight costs and supplier expediting fees by €18,400/month
Average days-between-stockout improved from 11 to 47 days across the monitored SKU portfolio

// outlook

📈 Forecast & Projections

60-Day Stock Level Projection — Portfolio Average with ROP Triggers

Projected stock depletion across the SKU portfolio under different demand scenarios with reorder trigger dates marked

// strategic guidance

💡 Advice for Companies with Similar Challenges

Dynamic Reorder Point Implementation — Key Recommendations

Dynamic reorder points tied to rolling 13-week demand averages and current lead time actuals outperform static ROP settings by 35% on stockout frequency. Rebuild your reorder logic every quarter minimum — or automate the refresh entirely from your ERP data.
Never apply a single safety stock formula across your entire SKU portfolio. Tier your service levels by product value contribution: A-class at 99%, B-class at 97.5%, C-class at 95%. This frees up 15–25% of working capital in safety stock while actually improving service levels on your most important products.
The most dangerous phrase in inventory planning is "I'll check that later." Automate your reorder alerts and make them impossible to ignore. A daily push notification to buyers when a SKU breaches its ROP costs almost nothing to build but prevents the majority of stockout events before they occur.
Always validate your lead time assumptions against actual GR data, not contracted lead times. In most companies, actual lead time is 20–40% longer than what's in the system. Using contracted lead times for ROP calculations systematically under-calculates safety stock and causes avoidable stockouts.

// KEY TAKEAWAY

Static reorder points are a silent killer of service levels. They feel stable because nothing obviously breaks — until suddenly everything does at once. The shift from static to dynamic ROPs, refreshed from rolling demand and live lead time data, is one of the highest-ROI improvements available to any inventory planning team. It costs almost nothing to implement and delivers compounding service-level improvements every quarter.

Reorder PointAutomation Tool

Reorder Point
Automation Tool