It’s no secret that there have been many disruptions to supply chains in recent years, highlighting a critical need for businesses to improve their planning, and many businesses are turning to the use of machine learning.
Machine learning, a type of AI that enables computer systems to learn from data, identify patterns, and make decisions without being programmed, can substantially improve a company’s processes. As more and more businesses adopt its use, the machine learning market will only continue to grow, driving significant economic growth.
While many companies have already utilized machine learning in robots within their factories and warehouses, the technology can also be used to streamline many aspects of the supply chain.
The many uses of machine learning
Machine learning can be used to solve a vast array of problems along the supply chain. To name just a few, machine learning can automate tasks, improve safety, and predict risks.
The technology can optimize transport routes and schedules by analyzing real-time traffic data and finding the most efficient course. This can reduce the cost of fuel and improve customer satisfaction through better delivery tracking and faster arrival of their items.
Another way machine learning can be used is for inventory management. Overstocking and understocking cost businesses billions worldwide, but with the use of AI, companies can more accurately predict the demand for their products and determine when they need to restock. This saves the company thousands of dollars in over/under stocking costs and ensures customers always have access to the products they want.
Machine learning can also be used to accurately predict when a piece of machinery might fail. Unexpected breakdowns of equipment can be a major safety concern for workers or consumers, and they can be costly to deal with. By using AI to monitor the performance of a machine, companies can perform maintenance when it’s needed and avoid a breakdown altogether.
Benefits of incorporating machine learning
More than the obvious benefits of improved monitoring and automated tasks, the use of machine learning can also greatly improve a company’s economic outlook.
Organizations that implement machine learning can use it to gain a competitive edge over others. AI can reduce expenses and increase profits by maximizing efficiency along the supply chain, which can result in an improved customer experience, satisfaction and retention.
Machine learning can also improve employee well-being and safety on the job. These systems can be used to eliminate the manual or dangerous elements of a job through streamlined tasks and better predictions of when equipment may fail.
A growing market
AI is becoming more and more prominent in almost every industry and walk of life, but many believe that its implementation in supply chains will have the biggest economic impact. McKinsey estimates that, globally, businesses will bring in between $1.3 and $2 trillion a year in economic value while using AI, and Goldman Sachs expects the use to bring the cost of logistics down by at least 5%.
There is still much to learn about this emerging technology and its abilities, but it’s clear that it’s worth investing in.
If you’re interested in learning more about the use of AI in supply chain and manufacturing, I recommend checking out our NASCES, NAMES, PMWS, BMWS, and EUSCES events, where these topics are widely discussed.
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Colleen Douglas
Senior Marketing Coordinator
Executive Platforms
Colleen joined the Executive Platforms team in May of 2022. She has five years of experience in event marketing, with an emphasis on copywriting and digital strategies.
Colleen has a BA Honours in Business Communications from Brock University and a Diploma in Digital Media Marketing from George Brown College.