QAD EOQ and Reorder Point Calculator
Item planning data in QAD, such as order policy, safety stock and order quantity, is often set once and left for years. This calculator derives defensible starting values from demand, cost and lead time so planners can revisit them with evidence.
Your numbers
Purchasing or changeover cost incurred each time you order.
Capital, storage, insurance, obsolescence.
Measure from recent daily or weekly history.
Your results
Assumes normally distributed demand and constant lead time. Validate against your own history and review lot-size and minimum order constraints.
Safety stock and reorder point vs lead time
Sweeps Replenishment lead time from 1 to 90, holding your other inputs fixed.
Item planning parameter review
Get an optional expert review of safety stock and order policy settings across your item master.
Optional. The tool and every export work without this. No spam.
How to use it
Enter annual demand, the cost of placing one order, the unit cost and your carrying cost rate. Then enter the replenishment lead time and the standard deviation of daily demand taken from recent history. Choose the cycle service level you want to hit: it is the probability of not stocking out during a replenishment cycle. The results give an order quantity, a safety stock and a reorder point you can compare with what the planning record holds today. Drag the lead time slider to see how a slower supplier inflates the buffer.
- Use demand history from the same period for mean and deviation
- Treat lead time as receipt to receipt, not order to ship
- Round order quantity to supplier pack sizes afterwards
- Review high-value items first
Formulas used
Economic order quantity is the square root of two times annual demand times order cost, divided by unit cost times carrying rate. Safety stock is the Z score for the service level times the daily demand deviation times the square root of lead time. Reorder point is average daily demand times lead time plus safety stock. Annual cost adds ordering cost, cycle stock carrying cost for half the order quantity, and carrying cost on safety stock.
Reading the result
Safety stock grows with the square root of lead time, so halving the lead time cuts the buffer by roughly 30 percent, not 50. Raising service level from 95 to 99 percent increases the Z score from about 1.64 to 2.33, a large step in stock for a small gain in availability. If safety stock dwarfs cycle stock, the better lever is usually supplier reliability or demand visibility rather than more inventory. Class items by value before applying one policy to all.
Common mistakes
Using monthly deviation as if it were daily inflates safety stock, so convert units first. Applying EOQ where a supplier imposes minimums or price breaks gives a quantity you cannot buy. Ignoring lead time variability understates risk for imported parts. Finally, a formula is a starting point: lumpy or project-driven demand does not follow the normal assumption, and these items often need time-phased planning instead.
Frequently Asked Questions
Where do these values go in QAD?
Item planning data such as safety stock, order quantity and order policy is maintained on the item planning record. Menu names differ by release, so confirm the program in your own menu before loading values in bulk.
What service level should I pick?
Match it to item importance. Many plants use 95 to 99 percent for critical or long lead items and 90 to 95 percent for low-value commodity parts, then review cost against stockout impact.
How do I get demand deviation?
Export daily or weekly usage for the past 6 to 12 months, compute the standard deviation, and convert to a daily figure if you used weekly buckets by dividing by the square root of days in the bucket.
Is EOQ still relevant for MRP-driven items?
For stable, continuous-demand items it is a sound starting point. For items planned lot for lot against firm requirements, safety stock still helps but EOQ matters less.
If you would like item planning parameters analysed across your whole item master rather than one part at a time, Netray can help build that from your ERP data.
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