Before Adjusting a Beauty Store Replenishment Policy, How Can You Understand Changes in Order Quantities and Inventory Capital Usage?

Before Adjusting a Beauty Store Replenishment Policy, How Can You Understand Changes in Order Quantities and Inventory Capital Usage?

Suppose several beauty stores frequently run out of their regular facial cleanser over the weekend, and headquarters plans to increase the target inventory coverage from six days to eight days. Before making the change, the product manager needs to understand which stores will place larger orders, whether the central warehouse can supply them on time, and how much additional inventory capital will be tied up after the products arrive. If stockouts are concentrated in only a few stores, increasing the standard across all stores may cause stores that already have sufficient inventory to order more than necessary.

Start by selecting a group of stores and products, then simulate the old and new parameters using the same business data. PEKON’s suggested quantity simulation can generate recommended order quantities for the selected stores and products before formal ordering begins. The product team can then combine the results with current inventory, in-transit quantities and product costs to decide which stores should enter the pilot first.

Calculate the Additional Order Requirement Before Changing Inventory Standards

Run the simulation in a test environment or within a scope isolated from formal ordering. When using PEKON’s suggested quantity simulation, first confirm that the relevant rules are enabled and linked to the corresponding order type. Then run the old and new parameters separately. If the purpose is only to compare the impact of increasing inventory coverage days, both simulations should use the same stores, products, sales period, available inventory, in-transit quantities and expected delivery time.

Even when two simulations are run on the same day, sales, receiving activities or in-transit updates may occur between them. After exporting the results, compare them by store and product. If the input data has changed, first recalculate the affected stores and products using consistent data. List rows that cannot be recalculated separately to avoid attributing changes caused by sales or deliveries to the new parameters.

It is also necessary to verify which parameter was actually used for each product in each store. If a cleanser in a shopping-district store uses a separately configured coverage period, changing only the default value will not affect that product in that store. Record the actual parameters and suggested quantities used in both simulations in the comparison table. When a row is missing, check the simulation task and product scope first to determine whether the product was excluded from the simulation or whether its calculated suggested quantity was zero.

Convert Changes in Suggested Quantities into Verifiable Inventory Costs

The following is a simplified example. Target inventory equals average daily sales multiplied by the inventory coverage days. The suggested order quantity equals target inventory minus available inventory and in-transit quantities that can arrive on time. If the result is below zero, it is treated as zero. The only difference between the two simulations is the inventory coverage period. For ease of calculation, assume that products are ordered by unit and that carton specifications and quotas are not considered.

Store A sells an average of three cleansers per day. It has six units of available inventory and no stock in transit. Under the six-day standard, the suggested order quantity is 3 × 6 − 6 = 12 units. Under the eight-day standard, it becomes 3 × 8 − 6 = 18 units. Store B sells six units of the same cleanser per day. Its available inventory and in-transit quantity that can arrive on time total 12 units, so the suggested quantity increases from 24 to 36 units.

Both Store C and Store D sell an average of two units of essence per day. Store C has eight units of available inventory and another four units that can arrive on time. Its existing stock is just enough for six days, so it needs four additional units under the eight-day standard. Store D has a combined available inventory and timely in-transit quantity of 17 units, so it does not need replenishment under either standard.

When summarizing the results, break down the total difference by store and product. Store C’s suggested essence quantity increases by only four units, but its cost-based increase is the same as Store B’s 12-unit increase for cleanser. If some products require higher coverage standards while others require lower standards, first summarize the increases and decreases in suggested quantities and their corresponding costs separately, then calculate the net change. Before placing actual orders, verify carton specifications, quotas and supply availability.

Distinguish Suggested Order Value from Actual Inventory Capital Usage

The RMB 1,200 in the table is calculated by multiplying the change in suggested quantity for each product by the unit inventory cost confirmed by the brand and then adding the results together. Even if the simulation includes retail prices or amounts calculated using retail prices, unit cost must be used when estimating inventory capital usage.

If the old and new plans start with the same opening inventory, products arrive according to the respective suggested quantities, and unit costs, sales, returns and other inventory movements remain the same, the inventory cost held by stores under the new plan will be RMB 1,200 higher at the same point in time. After the pilot, actual inventory usage should be reviewed using inventory quantity and cost at the same point in time, while in-transit quantities should be checked separately.

Headquarters should also verify where the additional products come from. If all additional store deliveries are transferred from existing central warehouse inventory, the increase in store inventory corresponds to a decrease in central warehouse inventory. If the central warehouse needs to make additional purchases as a result, the purchasing quantity and payment arrangements should be reviewed separately. The simulation can estimate how much additional inventory needs to be arranged, but the business return can only be evaluated after the pilot produces actual delivery and sales results.

Start with Stores Where the Cause of Stockouts Is Clear

The first pilot group can include stores that experience repeated stockouts during normal operations, have reliable inventory data and can be supplied by the central warehouse on time. If Store B’s cleanser still sells out early despite timely supply, the brand can first test this product in that store. The simulation indicates an additional suggested order of 12 units, equivalent to RMB 480 at cost. If Store C rarely runs out of essence, the old parameter can be retained for now. If stockouts are caused by delivery delays, the delivery arrangement should be reviewed first.

Before the pilot begins, headquarters should define the number of complete replenishment cycles to observe and the acceptable ending inventory range. During the pilot, compare actual orders, delivery times, stockout periods and ending inventory. Where possible, retain comparable stores that continue using the old parameters as a reference group.

If Store B receives the cleanser on time, its stockout period becomes shorter and its ending inventory remains within the predefined range, the policy can be expanded to similar stores. If inventory increases but the stockout period does not become shorter, first check whether the products arrived before the demand peak and whether actual sales exceeded the original estimate. If the additional products frequently accumulate, narrow the pilot scope or return to the previous parameter.

For enabled and fully configured PEKON suggested ordering projects, headquarters can first verify parameter definitions and default values, then maintain applicable differences by store or product. The suggested quantity simulation outputs recommended quantities for stores and products according to effective rules. The results can be exported, allowing the operations team to prepare an old-versus-new comparison table and use unit costs provided by finance for conversion.

If the brand is still evaluating whether its existing system can support replenishment requirements, refer to the Inventory Management System Selection Guide to compare how different systems support data analysis, suggested quantity generation and ordering execution.