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Monday, October 01, 2018

Inventory Problem Using Machine Learning

As a long time supply chain optimizer and design hack, this intrigued me.  And the pattern by product type interested me too.

Machine learning: A solution to backorder problem and inventory optimisation   Posted by PS Dhillon in DSC

For any business, the worst scenario is getting out of product inventory when customers are ready to buy your product. Keeping a stock of every item in the store is another burden to carry for every business. This trade off has been even more problematic in current times, when manufacturing firms are flooding with SKUs (Stock Keeping Unit) ranging from product sizes, flavours, styles etc. To cater personalised demand companies are customising products by adding various features to it & this is making life even more complex for all parts of businesses involved in the whole supply chain.

To understand this problem, lets take an example of a toothpaste. There are more than 6–7 popular brands such as Colgate, Pepsodent, Close up, Dabur, Himalaya, Meswak etc with each having 4–5 toothpaste different sizes ranging from 50gm to 300 gm & 4–5 different variants such as Sensitive, Germi-check, Gumcare, Whitening etc. ...

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