September 15, 2023 | Supplier Management Technology
Your phone chimes and you have a delivery notification of your most awaited product, right on time! But ever wondered how businesses manage to get the right products to the right place at the right time? That's where supply chain management comes into play. And with the integration of machine learning, supply chain management is becoming smarter and more efficient in an increasingly challenging business environment.
This blog discusses how machine learning for supply chain optimization is reshaping the game.
Traditional supply chain management has never been a walk in the park. It’s always an uphill task trying to balance the scales when it comes to supply and demand. Fluctuations are common — be it customer needs, sudden disruptions such as a global pandemic or a ship stuck in the Suez Canal, and the constant puzzle of managing inventory and transportation. It’s a constant challenge for supply chains to manage multiple tasks at the same time — and with precision.
Machine learning is a subset of artificial intelligence, and it’s here to turn supply chain challenges into opportunities. This is where machine learning for supply chain optimization works behind the scenes.
Machine learning dives into historical sales data, market trends, and even things like social media sentiment to predict what customers will want next. No more overstocking or running out of popular items. It's almost like having a crystal ball for inventory.
Supply chains situations can change in the blink of an eye. Machine learning systems are like superheroes in real-time adaptation. If a tweet suddenly makes a product go viral, these systems adjust things on the fly, making sure you get your orders on time.
eCommerce supply chains ensure that your packages find the quickest route to your door. Wonder how? Machine learning crunches tons of data to figure out the most efficient paths. That means less fuel, lower transportation costs, and less impact on the environment. It's a win-win!
Machines and vehicles need to stay in top shape for smooth supply chain operations. Machine learning can predict when something is about to go wrong, allowing for repairs before a breakdown occurs.
Predicting potential supply chain disruptions is a big part of risk management. Machine learning can analyze various data sources, such as news and social media, to spot early warning signs of trouble.
If you have been getting your orders on time and with real-time tracking updates, you can thank machine learning. It constantly optimizes delivery routes, reduces wait times, making customers happy at the end.
Machine learning for supply chain optimization isn't just a theory; it's changing the game right now.
Major eCommerce giants use machine learning to predict what products people will buy together or what people will buy following a recent purchase. This might not sound like a big deal, but it means they can pack an order faster and save time and money, or they might give people the option to get the delivery of two products at the same time.
And there are courier companies that want to constantly optimize delivery routes. With machine learning, they can figure out the best way to deliver packages — which means less fuel, fewer emissions, and lower costs.
Machine learning needs good data to work its magic — and that’s the bottom line. Without quality data, the results can be downright disappointing. There's also this question of transparency that machine learning can sometimes feel like a "black box", as in the decisions it makes could come without any explanation. That can be a concern, especially in industries where clear explanations are essential.
It's important to remember that machine learning is a tool, not a replacement for humans. It needs skilled people — such as data scientists and supply chain experts — so it can produce a meaningful output to make things work. And getting everyone on board with these changes can be a challenge too.
With growth in the uptake of Internet of Things (IoT), supply chains will become even more connected. That will also mean products will communicate with each other, letting us know where they exactly are, how they're doing, and when they'll arrive.
There's also blockchain technology — often linked to cryptocurrencies — which is finding its way into supply chain management, offering greater transparency, traceability, and security. It's like a digital ledger that keeps everyone honest.
Machine learning for supply chain optimization is the way forward for global businesses, and business leaders should brace for change if they haven’t already. Machine learning is turning the complex and rigid world of supply chains into one that's agile, responsive, cost effective, and more often turning the challenges into rewards.
Data-driven decisions and machine learning will be the major force propelling supply chains to new possibilities. And the time to embrace this tech revolution is now — for those who want their supply chains to be smarter, faster, and more efficient.