AI in Inventory Management

             “Managers tend to overcomplicate the process and the tools, but most of the time the real benefits lay on simplifying the process and getting accurate data about the stock.”

Following an interesting course about Inventory Management, we received this phrase in a conclusion e-mail, that made me think. Indeed, there is no real solution or framework to optimize perfectly your inventory, unless you know how to predict the future and therefore I would love to meet you.

However, my interest into Data Analytics and AI resurfaced, as it’s the type of problematic that this scientific field is trying to solve during the last 20 years. The fact that there is not an all-done solution for Inventory Management, is because information is always lacking. Therefore, how can we get this information? AI, indeed, can be a great help.

The most talkative example here (of course…) the giant of retail Amazon. They developed many tools that help them to manage better their inventory, hence having the possibility to make it grow.

Inside the Warehouses: Automating and Monitoring Inventories

When a company is in the field of retail, movements inside warehouses and number of goods are growing exponentially. It’s humanly impossible to make no mistake and follow perfectly everything: thus, Amazon developed Kiva (see picture below), a small automated robot that move pallets of goods inside the warehouse in an optimized way, reducing human needs & enable the tracking of movements.


Demand Forecasting for Inventory Management:

              Automating the movements inside your warehouse will give you more information about the present activity of your inventory; but the greatest challenge of this century is to be able to predict the future.


Let’s imagine that you are an important water bottle supplier, and that you faced stock shortage during a heatwave this summer. A way to prevent this kind of event is to try to analyse your sales throughout a determined time framework, taking also into account pertinent variables, such as the temperature. Therefore, you could develop an ordering policy depending on the weather forecast and optimize even more your stocks.

This AI field related to this type of problematics is Time Series Analysis, which is also extremely used in the stock market and high-frequency trading.


If you are interested to have more insights about Time Series Analysis, I advise you to take a look at this video, that will introduce to the theory of this concept.

              To conclude, we can clearly state that AI have been developed to solve knowledge management problems, that have been and will always be an issue. However, thanks to this technology decisions are taken with more insights, and show the power of the symbiosis between humans and machines.


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