Replenishment Recommendation

Overview

This skill generates precise replenishment recommendations—what to order, how much, and when—for each SKU-location combination. It combines Economic Order Quantity (EOQ) optimization with demand-driven replenishment policies, respecting real-world constraints such as minimum order quantities (MOQs), supplier capacity, shelf life, warehouse capacity, and working capital budgets. The output is a prioritized, actionable order plan that balances service level targets against inventory investment.

When to Use

During regular replenishment review cycles (daily/weekly purchase order generation)
When inventory drops below reorder point and automated triggers fire
During pre-season build planning for seasonal categories
When supplier lead times change and safety stock recalibration is needed
When working capital constraints require prioritization of limited ordering budget
After a stockout event to determine recovery order quantities

Required Inputs

Input	Description	Format
`inventory_position`	On-hand + in-transit + on-order - backorders - allocated	Numeric per SKU-location
`demand_forecast`	Forward weekly demand forecast (minimum lead time + review period)	Numeric array
`lead_time`	Supplier lead time in days (average and standard deviation)	Numeric
`review_period`	Ordering frequency (days between order opportunities)	Numeric
`service_level_target`	Target fill rate or cycle service level (%)	Numeric
`cost_parameters`	Unit cost, ordering cost per PO, carrying cost rate (% p.a.)	Structured object
`supplier_constraints`	MOQ, case pack, pallet quantity, max order capacity	Structured object
`shelf_life`	Product shelf life in days (for perishables)	Numeric (optional)
`warehouse_capacity`	Available storage in units, cases, or pallets	Numeric (optional)

Methodology

Step 1: Reorder Point Calculation

Compute the reorder point (ROP) that triggers a replenishment:

ROP = (Average_Daily_Demand × Lead_Time) + Safety_Stock

Where safety stock accounts for both demand and supply variability:

Safety_Stock = Z × √(LT × σ_d² + d_avg² × σ_LT²)

Z = Z-score for target service level (1.28 for 90%, 1.65 for 95%, 2.33 for 99%)
LT = average lead time in days
σ_d = standard deviation of daily demand
d_avg = average daily demand
σ_LT = standard deviation of lead time in days

Step 2: Economic Order Quantity (EOQ)

Calculate the cost-optimal order quantity:

EOQ = √(2 × D × S / H)

Where:

D = annual demand in units
S = fixed ordering cost per purchase order (administrative + freight setup)
H = annual holding cost per unit = Unit_Cost × Carrying_Cost_Rate

Adjust EOQ for practical constraints:

Adjusted_EOQ = max(MOQ, round_up_to_case_pack(EOQ))
If Adjusted_EOQ > Warehouse_Capacity_Available: cap at capacity and flag
If Shelf_Life < (Adjusted_EOQ / Daily_Demand): reduce to shelf-life-safe quantity

Step 3: Order-Up-To Level (for Periodic Review Systems)

For periodic review replenishment policies:

Order_Up_To = Demand_During_(LT + Review_Period) + Safety_Stock
Order_Qty = max(0, Order_Up_To - Inventory_Position)

Apply rounding to case pack or pallet quantities:

Final_Order_Qty = round_up_to_nearest(Order_Qty, Case_Pack_Size)
If Final_Order_Qty < MOQ and Order_Qty > 0: set Final_Order_Qty = MOQ

Step 4: Multi-Constraint Optimization

When working capital or warehouse capacity is constrained, prioritize across SKUs:

Priority Score = Service_Level_Gap × Revenue_Weight × Criticality_Factor

Where:

Service_Level_Gap = Target_SL - Projected_SL_Without_Order
Revenue_Weight = SKU revenue share (A-class items weighted higher)
Criticality_Factor = 2.0 for must-not-stock-out items, 1.0 for standard, 0.5 for long-tail

Allocate budget using greedy knapsack: order highest-priority SKUs first until budget or capacity is exhausted.

Step 5: Order Consolidation & Timing

Vendor consolidation: Group orders to same supplier to achieve freight breaks and volume discounts
Full truckload optimization: Aggregate orders to hit FTL thresholds (e.g., 40,000 lbs or 2,500 cubic feet)
Order timing: If projected stockout date > lead time + buffer, delay order to reduce carrying cost
Forward buy evaluation: If a supplier offers temporary discount, compute break-even weeks of supply:
```
Break_Even_WoS = Discount% / (Carrying_Cost_Rate / 52)
```
Only forward buy if expected sell-through is within break-even window.

Output Specification

replenishment_plan:
  generated_at: "2026-02-07T06:00:00Z"
  planning_horizon: "2026-02-07 to 2026-03-07"
  summary:
    total_order_lines: 245
    total_order_value: 1850000
    total_units: 128500
    orders_by_priority:
      critical: 18
      high: 67
      standard: 160
  orders:
    - sku_id: "SKU-11234"
      location: "DC-EAST-02"
      supplier: "SUP-ACME-01"
      recommended_qty: 2400
      unit_cost: 4.50
      order_value: 10800
      order_type: "standard_replenishment"
      priority: "critical"
      reorder_point: 1800
      current_position: 450
      safety_stock: 620
      eoq: 2200
      adjusted_reason: "Rounded up to pallet quantity (2400 = 4 pallets × 600)"
      projected_wos_after_receipt: 6.2
      recommended_order_date: "2026-02-07"
      expected_receipt_date: "2026-02-17"
      projected_stockout_date_without_order: "2026-02-11"

Analysis Framework

Replenishment Policy Selection Guide

Demand Pattern	Variability	Recommended Policy	Review Cycle
Steady, predictable (AX)	Low CoV (<0.3)	Continuous review (s,Q) with EOQ	Event-driven
Moderate variability (AY)	Medium CoV (0.3-0.7)	Periodic review (R,S) with dynamic SS	Weekly
Highly variable (AZ)	High CoV (>0.7)	Min-max with demand sensing	Daily
Slow-moving (CX/CY)	Low/Medium	(s,S) with aggregate ordering	Bi-weekly
Intermittent/lumpy (CZ)	Very high	Poisson or Croston's method for SS	Monthly + event triggers

Key Metrics to Track

Inventory Turns: Annual_COGS / Average_Inventory — higher = more efficient capital use
Fill Rate: Line_Items_Fulfilled_Complete / Total_Line_Items_Ordered
Purchase Order Cycle Time: Days from PO creation to goods receipt
Supplier OTIF: On-Time In-Full delivery performance by supplier
Working Capital Efficiency: Inventory_Value / Monthly_Revenue — target < 1.0 for fast-turning CPG

Examples

Example 1 — Standard EOQ Replenishment

"SKU-11234 (Paper Towels 8-pack) at DC-EAST-02: Current position is 450 units with ROP at 1,800. Weekly demand forecast: 580 units. EOQ calculates to 2,200 units but rounded to 2,400 (full pallet = 600 units × 4). Order value: $10,800. If ordered today, receipt expected Feb 17. Without order, projected stockout Feb 11. Priority: CRITICAL."

Example 2 — Constrained Budget Allocation

"Weekly ordering budget is $500,000 against $850,000 in recommended orders. Applying priority scoring: 18 critical orders ($145,000) fully funded, 67 high-priority orders ($310,000) fully funded, remaining $45,000 allocated to top 12 standard orders by service-level gap. 148 standard orders deferred to next cycle. Projected portfolio fill rate with this allocation: 96.2% (vs. 98.5% if fully funded)."

Guidelines

Never recommend an order quantity below the supplier MOQ — either order MOQ or defer
For perishable goods, cap order quantity at Daily_Demand × (Shelf_Life - Lead_Time - Buffer_Days)
Always show the projected weeks of supply after receipt so planners can validate reasonableness
Flag when EOQ suggests a quantity that exceeds 12 weeks of supply — challenge the ordering cost assumption
Include in-transit inventory in position calculations to avoid double-ordering
When multiple DCs can source from the same supplier, consolidate at the PO level for freight optimization
For new product launches without demand history, use analogous product demand with a 1.5× safety factor
Recalculate safety stock monthly or when demand CV or lead time CV changes by more than 15%
Present the incremental carrying cost of ordering above EOQ so planners understand the trade-off

Replenishment Recommendation

Replenishment Recommendation

Overview

When to Use

Required Inputs

Methodology

Step 1: Reorder Point Calculation

Step 2: Economic Order Quantity (EOQ)

Step 3: Order-Up-To Level (for Periodic Review Systems)

Step 4: Multi-Constraint Optimization

Step 5: Order Consolidation & Timing

Output Specification

Analysis Framework

Replenishment Policy Selection Guide

Key Metrics to Track

Examples

Guidelines

Validation Checklist