I am already looking into it. My aim is to use date science to accomplish this task. This will ensure optimum level of stocks. Reducing the upkeep cost and providing high availability. And not for the past three months it should be year to year companrision. And then adding all past years to predict better results by correlating. The variables that correlate with demand of stock can be many.
A helping hand is always good. You are welcome. We would need a data analyst to correlate different factors and drive a working equation for this model. Then we can translate that into programming to make the magic happen.
We have implemented it in semi manual way. We have simple report which shows the consumption of item based on a start and end date - usually we use trailing 3 months but can adjust. We also have current stock report by item. We then divide the current stock level by this average consumption - and calculate out of stock date - this is done in excel after downloading the 2 reports from ERPNext. Trying to introduce this simple calculation in ERPNext - should be a good starting point??? Simple stock divided by trailing sales (as proxy for projection).
Any pointers on how to perform the excel calculation part in ERPNext?
A logic can be implemented that can do these excel calculations. My point of correlating the whole year is in consideration of seasons.
Many items are connected to the part of the year.
1- an item sales increases gradually for 3 months reaching its peach and then declines abruptly the following next month
2- an items sales was already low for last three months and then increased abruptly the next month