Reorder Point
Any store, warehouse, or enterprise faces the need to optimize inventory. To avoid interruptions in trade, it's crucial to determine the moment when it is necessary to replenish existing product stocks.
The reorder point or replenishment moment is such a level of warehouse stocks at which a new order for supply should be placed to replenish stocks.
In this demo example, one of the variants of calculating the reorder point is implemented:
,
- RP — Reorder Point
- AC — Average Consumption
- TS — Time to Supply
- SS — Safety Stock
Algorithm Description
1. Import
In the submodel Data Import, data is imported from the file goods.mgd:
| Name | Caption |
|---|---|
 id |
Product ID |
 sale_date |
Sale date |
 quantity |
Quantity |
2. Data Cleaning
In the Data Cleaning submodel, it is checked whether the data meets the minimum requirements for analysis.
In the Data Verification node, records are filtered in which the product ID is not specified, the quantity sold is zero, or the sale date of the product is not specified:
(Quantity > 0) AND (Product ID is not Null) AND (Sale Date is not Null)
Products can be repeated, i.e., the same product can be sold once or more times at different times and in different volumes.
3. Reorder Point Calculation
In the Calculations submodel, there are two input configurable variables:
| Name | Description |
|---|---|
 supply |
supply |
| safety_stock |
safety_stock |
In the Reorder Point Calculation node, based on grouped data and variables, the reorder point is computed as:
quantity/(DaysBetween(sale_date_Max,sale_date_Min)) * supply + safety_stock,
quantity— the sum of each product soldsale_date_minandsale_date_max— the earliest and latest sale date for each product
The DaysBetween function returns the total number of days between two dates.
Download and open the file in Megaladata. If necessary, you can install the free Megaladata Community Edition.