maji-stock-calculator-v1

Input Parameters

Demand Characteristics

Mean Demand per Week (kg or units)

Demand Std Deviation (kg or units per week)

Annual Demand (kg or units per year)

Lead Time Characteristics

Mean Lead Time (weeks)

Lead Time Std Deviation (weeks)

Ordering Policy

Order Quantity (kg or units per order)

Note: Order quantity is typically constrained by supplier MOQ, pallet configurations, or determined through separate EOQ analysis. This calculator optimises service level given a fixed order quantity.

Cost Parameters

Unit Cost (£ per kg/unit)

Cost of Capital (% per year)

Storage Cost (£ per unit per year)

Storage cost includes warehouse space, handling, insurance, obsolescence risk. Typical: 2-5% of unit cost per year.

Lost Sales Cost (£ per stockout event)

Lost sales cost: Lost margin + expediting + customer relationship damage. Typical: 10-50× unit cost per event.

Quality

Rejection Rate (% rejected on arrival)

Optimisation Results

Optimal Service Level

Stock Level Policy

Safety Stock -

Reorder Point (ROP) -

Maximum Stock Target -

Average Inventory -

Cost Breakdown at Optimum

Working Capital Cost -

Physical Storage Cost -

Expected Stockout Cost -

Total Annual Cost -

Operating Metrics

Expected Stockouts per Year -

Reorder Cycles per Year -

Working Capital Tied Up -

Volatility Drivers

Demand Uncertainty -

Lead Time Variability -

Key Insight: -

Total Cost vs Service Level

The optimal service level balances holding costs (increasing with safety stock) against expected stockout costs (decreasing with higher service levels).

Methodology

This calculator optimises service level policy, not batch size. Order quantity is fixed (determined by MOQ, pallet configs, or separate EOQ analysis).

Safety Stock Formula

SS = Z × √(μ_L² × σ_D² + μ_D² × σ_L²) + Rejection Buffer

Total Cost

Total Cost = Holding Cost + Expected Stockout Cost Holding = [Unit Cost × Capital % + Storage £/unit] × [SS + Q/2] Stockout = Lost Sales £/event × (Annual Demand/Q) × L(Z)

Where L(Z) is the unit normal loss function quantifying expected shortage per cycle.