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Hello all,
I'm having some troubles on forecasting when a given material is going to have obsolencence problems.
This is the data I have:
First, I have a table with the actual stock and the obsolencence date for each material:
Material code | Obsolencence date | Actual stock |
001 | 25-07-2022 | 2.300.000 |
002 | 24-06-2022 | 14.502.000 |
003 | 12-09-2022 | 21.530 |
004 | 02-06-2022 | 4.845.623 |
005 | 04-09-2022 | 2.312.451 |
006 | 07-12-2022 | 1.545 |
… | … | … |
Second, I have another table with the forecasted consumtions on each date for each material:
Material code | Quantity to be consumpted | Date |
001 | 50 | 18-03-2022 |
002 | 100 | 18-03-2022 |
003 | 150 | 18-03-2022 |
005 | 100 | 18-03-2022 |
006 | 400 | 18-03-2022 |
001 | 350 | 18-03-2022 |
006 | 152 | 18-03-2022 |
003 | 620 | 19-03-2022 |
005 | 600 | 19-03-2022 |
002 | 235 | 19-03-2022 |
006 | 1545 | 20-03-2022 |
001 | 3625 | 20-03-2022 |
006 | 150 | 20-03-2022 |
006 | 250 | 20-03-2022 |
005 | 350 | 21-03-2022 |
006 | 150 | 21-03-2022 |
005 | 265 | 21-03-2022 |
006 | 321 | 21-03-2022 |
005 | 890 | 21-03-2022 |
… | … | … |
So I'm having troubles on computing the sum of forecasted consumptions for each material before each obsolescence date.
As an example of material 001, would be all lines that matches material code 001 and is always before the obsolescence date:
Does anybody know hoy could I compute this, please?
Thanks a lot in advance.
Please provide sanitized sample data that fully covers your issue. If you paste the data into a table in your post or use one of the file services it will be easier to work with. Avoid posting screenshots of your source data if possible.
Please show the expected outcome based on the sample data you provided. Screenshots of the expected outcome are ok.
https://community.powerbi.com/t5/Desktop/How-to-Get-Your-Question-Answered-Quickly/m-p/1447523
Just did. Thanks for the advice 🙂