How Technological Advancements such as IoT, Big Data and Machine Learning can Revolutionise the Supply Chain
By Graeme Wright, CTO for Manufacturing and Utilities Services, Fujitsu UK and Ireland
Graeme Wright, CTO for Manufacturing and Utilities Services, Fujitsu UK and Ireland
Supply chains typically do not make national headlines, but in 2018 when KFC – one of the world’s leading fast-food chains – ran out of chicken in the UK, it became a major news story and the supply chain became front-page news. Consequently, 700 stores temporarily shut down operations and the complexities of supply chain and the workings behind it which we take for granted, were brought to the fore.
In today’s modern supply chain, digital and technological advancements have added new dimensions, which can add significant layers of data. This, in turn, can enable supply chains to become faster, more reliable, more cost effective and even more tailored for the end user.
The Internet of Things, the data harvester
Advancement in technology that can deliver real benefits in the supply chain is the Internet of Things (IoT). The rise of IoT means sensors can be added to almost anything, and as a result we can automate many processes using technologies such as RPA (Robotic Process Automation) and AI (Artificial Intelligence), but the true benefit comes when manufacturers put it all together with people in order to transform the power of the supply chain in real-time. Having this real-time data enables manufacturers to reduce costs, as precise insights into when customers will buy which products enable better planning production and help reduce storage time.
Having this real-time data enables manufacturers to reduce costs, as precise insights into when customers will buy which products enable better planning production and help reduce storage time
The benefits of getting a real-time, holistic view of where its things are, what state they’re in, what they’re doing, and how they’re doing it, is of invaluable benefit to any business – not just in the supply chain.
When we apply this to real-life situations, this means being able to anticipate problems and avoid them, so manufacturers always ensure their deliveries are on time. For instance, if manufacturers know they have to produce X number of items for delivery in Birmingham by the 5th of May – having a holistic view across the entire supply chain, from before and during the factory process, all through to reaching the customer – can help manufacturers foresee any issues before they arise. By identifying points of failure such as with the sourcing raw materials – such as if there’s a problem in a country where they originate – they can have a contingency plan in place and switch to a different supplier where there are no potential problems, and ensure the process continues to run smoothly and to schedule.
Getting ahead with Machine Learning
What IoT ultimately provides is a wealth of data to the supply chain process. The ability to look deeper into every pinpoint of the supply chain means that manufacturers can make better decisions about how to run their operations and ensure they get the right products to the right customers and at the right time with a lower cost at the right quality.
The power of data also means manufacturers can widen their reach to their customers, and offer new types of services and features, which will further their relationship and open up opportunities for new revenue streams. Allowing manufacturers to extend their reach to the customer even when there are 3rd parties in the supply chain.
But how can manufacturers truly harness the power of the data they are harvesting? One solution is through Machine Learning.
Significant challenge manufacturers’ go through with their supply chain is being able to predict the future demands of the production. But now thanks to Machine Learning – commonly confused with Artificial Intelligence, although is very similar – we are seeing it take the large volumes of data being supplied from IoT, and without human input, can distinguish patterns that lead to a known problem and improve forecasting accuracy.
As well as improved levels of forecasting, ML can also be applied to aid manufacturers with the physical maintenance of its assets across its network. In practice, this means it will be able to alert the manufacturer to any potential issues on the horizon with equipment and make recommendations in real-time, so they can be fixed ahead of becoming a costly issue or putting a halt to production and delivery.
The power of data – reap the benefits
The data that supply chains can garner through connecting the entire supply chain is almost certainly one of the biggest untapped resources they have, and not using it properly could hinder their business’ future.
When used in the right way, technology can help revolutionise the supply chain and in turn deliver real business value.