Optimum Lot Size “GR” – Groff Reorder Procedure
Lot sizing allows us to define rules for the quantity of replenishment proposals created by SAP. The lot sizing procedures available in SAP S/4HANA can be grouped into the following
- Static lot-sizing procedures
- Period lot-sizing procedures
- Optimum lot-sizing procedures
In this blog, I will explain one of the Optimum lot sizing procedures called “Groff Reorder Procedure”
Groff Reorder Procedure
Starting from the first requirement, the system groups requirements into a lot until the average additional storage cost per period is greater than savings in the lot size independent cost per period.
It is recommended that you use Groff reorder procedure if the product has fairly regular requirements.
Master Data Settings
- In “MRP 1” view of the material master, select the required MRP type and then in the lot sizing parameters, select “GR” as lot size. Maintain the lot size independent ordering cost and the storage cost indicator. In this example, we are using 1000 as the ordering cost and the storage cost indicator is 1.
- In the “Accounting 1” view of the Material Master, maintain the price for the material. In this example, I have used a standard price of 10.
Configuration Settings for Storage Costs
- To maintain the storage costs indicator, navigate to IMG > Materials Management > Consumption-Based Planning > Planning > Lot-Size Calculation > Define Lot-Sizing Procedure and click on “Storage Costs Indicator”. Alternatively use the T-Code OMI4. In this example, I have used storage costs as 10%. This means, If the price of a material is $10, it would cost $1 to store it for a period of 365 days.
- Planned independent requirements are maintained on a weekly basis in this example. Starting from week 47, a weekly requirement of 1000 KG are maintained.
In the stock requirement screen below, you can see the system has grouped requirements from 20/11/2023, 27/11/2023, 04/12/2023 and 11/12/2023 into one planned order of 4000 quantity.
- For the first requirement on 20/11/2023, both the order cost savings and the average additional storage costs is zero because the time in storage is zero.
- For the requirement on 27/11/2023
Order Cost Savings = 1000 / (7 x 8) = 17.857
Addl. Storage Costs = (1000 x 10 x 10 x 7) / (100 x 365) = 19.178
Average Addl. Storage Costs = 19.178 / 14= 1.369
- For the requirement on 04/12/2023
Order Cost Savings = 1000 / (14 x 15) = 4.762
Addl. Storage Costs = (1000 x 10 x 10 x 14) / (100 x 365) = 38.356
Average Addl. Storage Costs = 19.178 / 21 = 1.826
- For the requirement on 11/12/2023
Order Cost Savings = 1000 / (21 x 22) = 2.164
Addl. Storage Costs = (1000 x 10 x 10 x 21) / (100 x 365) = 57.534
Average Addl. Storage Costs = 19.178 / 28 = 2.054
- For the requirement on 18/12/2023
Order Cost Savings = 1000 / (28 x 29) = 1.231
Addl. Storage Costs = (1000 x 10 x 10 x 28) / (100 x 365) = 76.712
Average Addl. Storage Costs = 19.178 / 35 = 2.191
As the additional storage cost increases over the period, the order cost savings decreases. For the requirement dated 11/12/2023, you can see that the order costs saving (2.164) is marginally larger than the average additional costs (2.054). For the next requirement dated 18/12/2023, the average additional costs (2.191) has exceeded the order cost savings (1.231). Hence the system takes the accumulated requirements upto 11/12/2023 and creates a planned order of 4000 quantity.