Optimising the Supply Chain in the Era of AI


What is AI technology?

AI is able to produce information through thinking and learning from data. This information can allow supply chains to be even smarter in their decision making with AI’s capability of predicting without human bias. AI is being used in a number of industries, but within supply chain management its main advantages are automation, error reduction and decreasing lead times. 

How can we optimise our supply chains for AI? 

Implementing AI into your supply chain is no easy feat, and quite often supply chain traditionalists may scoff at any pitfalls in the early adoption of the technology but with perseverance it can be extremely beneficial to all those within the supply chain. Based on our vast experience working with companies who are integratingAI into their supply chain, we’ve found that in order to optimise your supply chains for AI and make AI work for you, it’s important that you:

1)   Provide access to data: Machine learning requires data to learn from, so you will need to ensure that access is provided to both internal and external data to ensure the utmost accuracy in the information AI produces.

2)    Provide access for users: AI cannot solve everything, and there are some instances whereby you need human intervention. This is why access must be granted to many users who can override any decisions that AI has made.

3)    PreserveAutonomy: When a new piece of technology comes into a business it always takes a bit of getting used to, but its important not to dedicate too many man hours to AI. The purpose of it is to promote efficiency and learn from its mistakes.This is the whole concept of machine learning.

4)   Ensure Scalability: Year on year the usage of AI is continuing to grow, however whilst many companies revealing the amazing benefits of integrating AI, many struggle to scale its impact as a study from Mckinsey found.


How can AI be used in supply chain and logistics

With AI technology, there are endless possibilities of its use within supply chain and logistics. It’s been used within planning, merchandising, inventory in terms of distribution centres and shops, it can even be implemented in terms of the routes used to distribute products. But what’s the big deal? Well research has indicated that AI can save a lot of time and money for manufacturers, Mckinsey found that61% of manufacturers who implemented AI reduced their costs, whereas 53%increased their revenues.

Inventory Efficiency

A lot of attention has been spent recently on the scrutinising of many petrol stations’ Just In Time (JIT) management system. Of course, one of the main reasons companies implement JIT is due to its ability in making inventory management more efficient. AI is able to raise an issue when it is comparatively analysing both the warehouse stock and sales. This allows companies to prevent overstocking (and in doing so, being compliant with JIT).

As we mentioned earlier, it’s best to include not only internal data, but external data too. External data such as weather forecasts and seasonal demand allow companies to alternatively stock more products to take advantage of demand. It also helps supply planners in their decision making, so that they can ensure that there are no bottle necks within the process

Logistical Efficiency

Logistics is currently in the headlines with its lack of drivers, but AI can help ease the pain felt by the driver shortage and more. Fleet management AI technology gives fleet managers real time tracking data which provides a wealth of information to make the right decisions on timings, locations, and methods of delivery. This data supports the reduction of other inefficiencies within the logistical process including the avoidance of bottlenecks, optimal efficiency for fuel and reducing fleet downtime.  

Manufacturing Efficiency

Many organisations are applying AI technology to their manufacturing processes in order to analyse the performance and observe any deviancy from typical performances. Using this data, AI can then ensure that the perfect formulation of value, cost and quality is produced, improving the overall product life cycle. Product defects, lead times and more are improved when AI is being utilised within the manufacturing process. With an AI system that communicates between sales, inventory and logistics, supply planners can utilise this data to ensure that trends are spotted, therefore dictating the manufacturing schedule and ensuring the highest profitability possible.

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