Plot
Formula Used
The reorder point triggers replenishment when on‑hand plus on‑order inventory reaches the demand expected during the protection period plus a safety buffer.
How to Use This Calculator
- Enter average demand and choose its time unit.
- Enter average lead time and choose its time unit.
- Set review period to 0 for continuous review.
- Select safety stock method: manual or service-level.
- If using service-level, provide variability inputs.
- Choose rounding and press calculate to view results.
Example Data Table
| SKU | Avg Demand (units/day) | Lead Time (days) | Service Level | Demand SD (units/day) | Lead Time SD (days) | Safety Stock (units) | Reorder Point (units) |
|---|---|---|---|---|---|---|---|
| VALVE‑A12 | 120 | 7 | 95% | 30 | 2 | ≈ 240 | ≈ 1,080 |
| BEARING‑B07 | 55 | 14 | 97% | 18 | 3 | ≈ 205 | ≈ 975 |
| FILTER‑F33 | 20 | 10 | 90% | 6 | 1 | ≈ 60 | ≈ 260 |
Values are illustrative; your computed results depend on your inputs and rounding choice.
Demand and Lead Time Inputs
Reorder point engineering begins with average demand and lead time expressed in compatible units. This calculator converts demand to units per day and converts lead time to days. Expected demand during the protection window is computed as d̄×(L+R), where L is average lead time and R is an optional review period. For example, 120 units/day with L=7 days and R=0 implies 840 units expected consumption before replenishment arrives.
Safety Stock Strategy Choices
Two safety stock paths support different operating realities. Manual safety stock fits when buffer inventory is set by policy, vendor constraints, or service contracts. Statistical safety stock supports variability-driven design and is calculated from a service level target and demand/lead time variability. You can compare both approaches to quantify how much your current buffer differs from a service-level objective.
Service Level to Z-Value Mapping
Service level is converted to a normal quantile z. At 90% service, z≈1.282; at 95%, z≈1.645; at 97.5%, z≈1.960; and at 99%, z≈2.326. Higher z increases safety stock linearly, so tightening service targets has a measurable inventory cost. The model uses a standard inverse normal approximation to compute z internally.
Variability Over the Protection Window
When demand and lead time fluctuate, uncertainty during lead time is modeled as σDL = √(L·σd² + d̄²·σL²). σd is demand standard deviation per day, and σL is lead time standard deviation in days. This captures the combined effect of noisy daily usage and uncertain delivery timing. Safety stock is then SS=z·σDL, increasing when either variability source grows.
Review Period and Rounding Effects
Periodic review systems add exposure because orders are placed every R days, not continuously. Increasing R extends the protection window and raises the reorder point even if safety stock is unchanged. Rounding also matters: using ceiling rounding prevents under-ordering when computed points include decimals, especially with fractional lead times or converted monthly rates.
Operational Use and Traceable Outputs
The Plotly chart visualizes expected inventory position from the reorder point down toward safety stock across the protection days, making the buffer intuitive. CSV and PDF exports provide an audit trail for planners and QA teams. Store the exported summary with supplier lead time data, forecast assumptions, and policy overrides to support decisions.
FAQs
1) What does the reorder point represent?
It is the inventory position that triggers replenishment so expected demand during the protection period is covered, plus safety stock for uncertainty.
2) When should I use a review period R?
Use R when orders are placed on a schedule, such as weekly planning cycles. R adds exposure because inventory can drop before the next order is released.
3) How do I pick a service level?
Choose based on shortage cost and customer impact. Critical parts often target 95–99%, while less critical items may use 90–95% to reduce inventory.
4) What if demand is intermittent or highly skewed?
Normal approximations may misstate risk. Consider intermittent-demand methods, minimum order quantities, or simulation-based buffers when many days have zero demand.
5) Why is ceiling rounding recommended?
Ceiling rounding avoids triggering reorder too late when decimals occur from unit conversions or fractional lead times, reducing the chance of stockouts.
6) Do exports include my inputs and derived values?
Yes. The CSV and PDF summarize inputs, the protection window, safety stock method, and the reorder point values, supporting reviews and documentation.