Use EOQ to analyse order quantity and a separately designed reorder trigger to decide timing. Neither a low closing stock balance nor a large purchase discount is sufficient on its own. A useful inventory MIS connects demand, ordering cost, carrying cost, reliable incoming supplies and lead-time exposure.
This is management-accounting guidance checked on 24 October 2026. The models are planning tools, not statutory minimum-stock rules or guarantees against stockouts. They do not determine inventory valuation under an accounting standard, GST credit eligibility or the legal permissibility of a purchase.
Define the economic model and keep units consistent
ICAI’s material-costing teaching material demonstrates EOQ and stock-level calculations. In the basic model, EOQ = square root of (2 × annual demand × ordering cost per order ÷ annual carrying cost per unit). For order quantity Q, annual ordering cost = annual demand ÷ Q × ordering cost; cycle-stock carrying cost = Q ÷ 2 × annual carrying cost per unit. These formulas assume a consistent time basis and the model’s stable-demand and replenishment assumptions.
Estimate the cost of placing an additional order rather than dividing the entire purchasing department’s annual salary by order count without analysis. Carrying cost should reflect the relevant annual holding burden. If holding cost is expressed as a percentage of price, convert it to a per-unit annual amount. Avoid adding the same financing or storage cost twice through different labels.
The simple EOQ comparison assumes constant purchase price, predictable demand, an applicable replenishment pattern and no unmodelled shortage or capacity penalty. Seasonal goods, short shelf life, irregular demand and supply disruption may justify a different policy. A formula result can be arithmetically correct and operationally unsuitable.
Design the trigger without double-counting the buffer
A conventional maximum-usage stock-level model uses reorder level = maximum usage per day × maximum lead time in days. Its associated minimum stock calculation deducts normal usage during normal lead time; a conventional maximum stock calculation adds the order quantity and deducts minimum consumption during minimum lead time. These are the specific teaching-model relationships illustrated by ICAI, not universal service-level formulas.
An alternative policy can use expected lead-time demand plus separately estimated safety stock. Do not silently combine the two approaches by taking a maximum-based trigger and adding the same inferred buffer again. Define whether days mean calendar or working days, and match the demand rate accordingly. Supplier production time, transit, inspection and internal release delays should be reflected consistently in the measured lead time.
Use an inventory position that represents usable supply
For the operational example here, inventory position means usable on-hand quantity plus valid incoming purchase-order quantity minus unfulfilled demand commitments not already deducted. This is an explicitly defined MIS convention. Exclude cancelled or duplicate orders, and investigate arrivals too late to prevent a shortage. Stock under quality hold cannot automatically support a production release.
Reconcile the position to the stock ledger and open-order report. If commitments have already been deducted from the usable on-hand figure, deducting them again understates availability. Conversely, displaying physical stock alone can trigger unnecessary purchases while a valid shipment is about to arrive. The policy should document how reservations, backorders and open orders are treated.
Constrain the result and compare total relevant cost
EOQ rarely arrives in the supplier’s required purchase pack. Compare feasible neighbouring quantities using the same cost model, then test minimum order quantity, storage capacity, shelf life, cash requirements and arrival scheduling. Rounding upward mechanically is not the same as finding the best feasible quantity.
When price changes with quantity, include annual purchase cost as well as ordering and carrying cost. Recalculate percentage-based carrying cost at the discounted price and apply the actual price-break conditions. The example below assumes an all-units discount; an incremental slab discount or a discount tied to annual commitment needs a different calculation. Report the cost advantage alongside the additional inventory and operational constraints, so management can make a purchase decision rather than merely accept a formula.
Worked illustrations
These illustrations use fictional facts and expressly stated assumptions. Amounts are Indian rupees unless a different currency or unit is specified. They are independent examples, not findings about any actual client.
Illustrative example 1: A basic EOQ calculation
Annual demand is 10,000 units, ordering cost ₹500 per order and annual carrying cost ₹20 per unit. EOQ = square root of (2 × 10,000 × 500 ÷ 20) = 707.1068 units, displayed as 707.11. At the theoretical EOQ, annual ordering and cycle-stock carrying costs are each approximately ₹7,071.07, total ₹14,142.14. This continuous planning result still needs a feasible whole-unit or pack decision.
Illustrative example 2: A maximum-based reorder trigger
Maximum daily usage is 80 units and maximum lead time 12 days, giving a reorder level of 960 units. Normal usage of 60 units for a normal ten-day lead time is 600. The difference is 360 units. Adding that same 360 again to the maximum-based trigger would produce 1,320 and double-count the buffer implicit in these stated assumptions.
Illustrative example 3: Compare position with the trigger
Usable on-hand stock is 600 units, valid timely open orders are 400, and unfulfilled commitments not already deducted are 100. Inventory position under the stated convention is 600 + 400 − 100 = 900. Against a 960-unit reorder trigger it is short by 60. The trigger calls for a replenishment review; it does not mean that the correct order quantity is automatically only 60.
Illustrative example 4: A lead-time deterioration changes the trigger
At maximum usage of 80 units per day, increasing the model’s maximum lead time from 12 to 15 days increases its trigger from 960 to 1,200 units, a rise of 240. Update the measured lead-time basis and investigate the supplier change. This sensitivity calculation is not a statistical guarantee of a particular stockout probability.
Illustrative example 5: Compare feasible purchase packs
Annual demand is 12,000 units, order cost ₹800 and annual carrying cost ₹100 per unit, derived from an assumed ₹500 price and 20% holding rate. Theoretical EOQ is 438.1780 units. For 50-unit packs, Q = 400 gives ordering plus carrying cost of ₹24,000 + ₹20,000 = ₹44,000. Q = 450 gives ₹21,333.33 + ₹22,500 = ₹43,833.33, lower by ₹166.67. Assume both quantities are operationally feasible and purchase price is unchanged.
Illustrative example 6: Conventional minimum and maximum stock checks
Using reorder level 960, normal usage 60 per day and normal lead time ten days, minimum stock is 960 − 600 = 360 units. With order quantity 720, minimum usage 40 per day and minimum lead time six days, maximum stock is 960 + 720 − 240 = 1,440 units. These are internally consistent outputs of the stated conventional model, not legal stockholding limits.
Illustrative example 7: An all-units discount requires purchase cost
Annual demand is 10,000 units and ordering cost ₹500. At price ₹100 and annual carrying rate 20%, the theoretical EOQ is 707.1068; annual purchase, ordering and carrying costs total approximately ₹10,14,142.14. A genuine all-units price of ₹98 is available at Q = 1,000, with carrying cost ₹19.60 per unit annually. Total cost becomes ₹9,80,000 + ₹5,000 + ₹9,800 = ₹9,94,800, a modelled saving of ₹19,342.14. Confirm the discount terms and feasible storage, funding and usage before accepting the offer.
Ten-step verification table
| Step | Verification | Evidence to retain |
|---|---|---|
| 1 | Define the SKU, unit and planning horizon. | Item master and consistent unit conversions. |
| 2 | Validate demand and seasonality assumptions. | Consumption history and approved forecast. |
| 3 | Estimate incremental order-processing cost. | Cost build-up with fixed-cost treatment explained. |
| 4 | Calculate annual carrying cost per unit. | Holding-rate and price reconciliation. |
| 5 | Compute and independently check theoretical EOQ. | Formula, inputs and unrounded result. |
| 6 | Choose and document the reorder policy. | Lead-time, usage and buffer methodology. |
| 7 | Reconcile usable inventory and valid incoming supply. | Stock, quality-hold, commitment and open-order records. |
| 8 | Compare feasible pack quantities and price breaks. | Total relevant-cost alternatives. |
| 9 | Test capacity, shelf life, cash and arrival constraints. | Operational feasibility sign-off. |
| 10 | Monitor actual demand and lead-time deviations. | Exception dashboard and policy revision record. |
Sixteen practitioner FAQs
1. Does EOQ tell us the reorder date?
No. It addresses quantity under stated assumptions. Timing needs a separate trigger and reliable supply-position information.
2. Should monthly demand be mixed with annual carrying cost?
No. Convert to a consistent horizon before calculating; otherwise the apparent precision is misleading.
3. Can all purchasing salaries be treated as variable order costs?
Not automatically. Identify the additional costs relevant to order-frequency changes and explain any allocated amounts.
4. Is purchase price irrelevant to EOQ?
With an unchanged unit price it can cancel from the quantity comparison, but it affects percentage-based carrying cost and matters directly for price discounts.
5. Must a fractional EOQ always be rounded up?
No. Compare feasible quantities and operating constraints rather than applying an automatic upward rule.
6. Does every company need the maximum-usage trigger?
No. Choose an appropriate replenishment policy. The conventional formula is one model, not a universal requirement.
7. Can safety stock be added to any existing trigger?
Check how the trigger was built. Adding a buffer already implicit in the method double-counts protection.
8. Do calendar and working days produce the same result?
Not necessarily. Match the consumption rate and lead-time measurement to the same day convention.
9. Should quality-held inventory be treated as usable?
Only if its release and availability support that conclusion. Report restricted quantities separately.
10. Can every open purchase order increase availability?
No. Validate status, quantity and expected timing; cancelled, duplicate or late supplies can distort the decision.
11. Should reserved demand be deducted twice?
No. Define whether it is already removed from the stock figure and reconcile commitments once.
12. Does a position below the trigger determine the exact order quantity?
No. The shortfall triggers a review; order size follows the replenishment policy and constraints.
13. Is a supplier’s quoted discount always economical?
No. Include purchase, ordering and carrying costs and examine the actual terms and operational consequences.
14. Can an all-units calculation be used for incremental price slabs?
No. Model the particular pricing mechanism; the same discounted price may not apply to every purchased unit.
15. Are these formulas sufficient for perishable or highly erratic items?
Often not. Shelf life, demand uncertainty and disruption can require different policies or a broader model.
16. What should management see beyond a single recommended quantity?
The assumptions, feasible alternatives, cost difference, lead-time exposure and exceptions requiring a purchasing or operations decision.
Conclusion
An effective replenishment MIS makes quantity, timing and feasibility visible together. Validate the inputs, state the policy, compare feasible alternatives and revise assumptions when actual demand or lead time changes.