Replenishment Based on Sales

Created by Support Team, Modified on Tue, 9 Dec, 2025 at 12:03 PM by Support Team


Purpose

To generate replenishment quantities for stores based on sales history within a defined date range. This module helps stores or merchandisers identify items that require restocking and create the corresponding Store Delivery Request by referencing sales performance and available warehouse stock.


Prerequisites

  • User must have access to E-Retail > Replenishment Module > Replenishment Based on Sales.

  • If replenishing for multiple stores at once, ensure Store Group is set up in E-Retail > Master Setup > Location Setup > Store Group Setup. This allows users to replenish for a group of stores (e.g., Boutique stores, Department stores) in one action.



Steps

1. Open the Module

  1. Go to E-Retail.

  2. Navigate to Replenishment Module.

  3. Select Replenishment Based on Sales.


2. Enter Sales History Period

  1. In Sales History From, select the start date.

  2. In To, select the end date.

    • This date range determines the sales used to calculate Daily Sales Quantity.


3. Enter Sales Units

  1. In Sales Units (From) and To, define a sales unit range.

  2. Common practice: 1 to 100, since sales above 100 often indicate bulk/special transactions.


4. Select Warehouse and Store

  1. Choose the Warehouse as the stock source.

  2. Select the Store requiring replenishment.

Stock formulas shown in the module:

  • W/H Stock = Warehouse stock-on-hand minus allocated quantity.

  • Store Stock = Store stock-on-hand plus in-transit quantity.


5. Document Information

  • Doc No auto-generates after saving.

  • Doc Date defaults to today’s date.

  • Enter Document Name if required.

  • A Store Group may be selected instead of a single store.


6. (Optional) Apply Product Filter

  • Click Product Filter to narrow down items by vendor, category, etc.

  • This step is optional.


7. Load the Data

  1. After entering all required fields, click Load.

  2. The system will display SKUs that match the criteria.

  3. A Replenish column (highlighted in yellow) will appear.

    • It auto-fills based on the Sold column.

    • User may override and input any number manually.


8. Review SKU Details

The document will display the following information:

General Item Details

  • Product Code

  • SKU Code

  • Description

  • Retail Price

  • Colour Desc

  • Size Name

  • DSD (Direct Store Delivery – usually not applicable)

  • W/H Stock

  • Daily Sales Quantity

Store Separator Section

  • Sold (total sold within the selected period)

  • Stock (store stock-on-hand)

  • Replenish (editable by user)


9. Save the Document

  • Click Save to generate the replenishment document.

  • The Doc No will appear after saving.


10. Confirm the Document

  • Click Confirm to finalize the replenishment.

  • The system will automatically generate a Store Delivery Request for the store.


11. Cancel Rules

  • Document can only be cancelled before confirmation.

  • After confirmation, cancellation must be done in Store Delivery Request, since that is the document created upon Confirm.


Notes / Tips

  • ⚡ The Replenish column is fully editable.

  • ⚡ The Sold value comes directly from the sales history period selected.

  • ⚡ Product Filter is optional but helpful for targeted replenishment.

  • ⚡ Using Sales Units 1–100 avoids abnormal sales records.


Important Operational Behaviour

Weekly Run

  • Replenishment Based on Sales is generally executed once every week as part of routine stock fulfilment.

No Carry-Forward Quantities

  • If the warehouse does not have sufficient stock to fulfil the current week’s replenishment suggestions,
    the next week’s replenishment run will not add or carry forward the unfulfilled quantities from the previous week.

  • The system recalculates fresh suggestions every week based on:

    • Sales performance for the selected date range

    • Latest store stock on hand

    • Safety levels or operational norms

  • This keeps each week's replenishment clean, accurate, and based on real-time stock conditions.


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