Artificial Intelligence in the Supply Chain

Artificial Intelligence in the Supply Chain

Like it or not, artificial intelligence is set to take over your world. It may well have already done so and if you’re in business, it’s coming at break neck speed. There can be few doubts that AI is going to make revolutionary changes to the way supply chains work, but let’s take a look at exactly what that means.

Algorithms, maths and statistics are all at play when it comes to AI, and though their implementation isn’t yet at a stage of maturity, the potential is massive. It’s all about how machines perceive their actions and their output in order to be more effective, both in terms of time and cost.

When a machine is always trying to better itself, artificial intelligence in the supply chain is working in the best way possible. Even better still, the machine won’t ask for a pay rise or extra holidays.

However it is achieved, if a machine can learn and adapt through experience, it has to be beneficial, even if it all sounds a bit too sci-fi for some people’s liking.

In terms of machines adapting and improving function, artificial intelligence in the supply chain isn’t necessarily a new phenomenon. For about twenty years, demand algorithms have had the capability to examine historical order data and make calculated forecasts, which is AI in the supply chain in all its automated glory.

Nothing new then, but certainly a work in progress.

As data input streams are increased and become more varied, the forecasts that an algorithm suggests are more informed and more detailed, further adding value to the whole process. The scope is always increasing, not just in terms of data input either.

Geographically, AI in the supply chain is informing bigger orders over larger areas, and what’s more, it’s getting them right too. If you can make an educated guess about orders and forecasts, you’re heading in the right direction, but if AI can make these guesses into informed, researched and well respected facts, then the age of the estimate may well be about to end.

When you think about it, it all makes total sense. Eradicating human error is one way of looking at it, and whilst this may go hand in hand with eradicating human work load, when your sole focus is on optimising the effectiveness of a supply chain, you want to shave off as much room for error as you possibly can, and then keep doing it. And keep doing it again.

Artificial intelligence in the supply chain is already upon us, and the more data streams we can feed it, the more useful the beast becomes. 

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