Supply Chain Management’s Artificial Intelligence Future

Supply Chain Management’s Artificial Intelligence Future

Aerial Photography Of Trucks Parked

Supply Chain Management’s Artificial Intelligence Future Artificial Intelligence will continue to cut up the economy and remake it in a more efficient light. Jobs that pay less than $20 per hour are going to continue to see the most seismic disruption as these skills are easiest to replicate with an Ai.

83% of those jobs are in danger of being replaced by Ai systems being deployed at firms such as McDonalds and Kroger.

How will these jobs be replaced? Will there be a replacement for people who lack a high school degree or any advanced skills?

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Jobs that require human emotions, intelligence and creativity seem to be irreplaceable. However we just witnessed an Ai-created work of art sell at Sotheby’s and we are seeing automated psychiatrists being created through Ai as well.

Chain Management is a complex skill that is being more and more efficiently run by artificial intelligence systems. A skill some thought would have stayed under human oversight for much longer than it is looking currently in the industry. The delivery industry has been utilizing artificial intelligence algorithms for a number of years.

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Location, street layout, traffic patterns and weather forecast are included in the artificial intelligence parameters.

The core value for artificial intelligence is to make accurate predictions.

In the delivery business, it is important to make more precise predictions with help of advanced statistics. Using advanced stats, it is more efficient to predict the roads and time for the delivery. So there is the natural connection between Delivery and Supply Chain Management.

Predicting demands for the future can be a big problem for supply chain management.

There are several areas that are important inputs for machine learning model, including promotions, media, web, market model, new products, and historical demands.

The output from a machine learning model is going to include promotional lift, halo effect, segment, NPI launch profiles, seasonality and web lift. All of the information is going to run through demand modeling by Base-Line processing.

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There is a lot of information that needs to be collected before running all of the data through a machine learning model. Having comprehensive data sets can be the most important requirement to increase the accuracy of a prediction and so many participants in the supply chain industry will have to work to clean their data.

As time passes, there will be more data collected from the internet and nowcasting of individual behaviors will most likely proliferate and predictions will become closer to what has occured in real life. This is what makes many people worry about Facebook, Google and Amazon’s seemingly insurmountable lead in the data race.

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Supply Chain Management’s Artificial Intelligence Future Written by Yan Zimo