AI and Predictive Analytics in Supply Chain Optimisation

Planning your supply chain is vital to ensure a smooth delivery process for your products. Supply chain forecasting is made up of several key components, which include:

• Stock analysis
• Demand forecasting
• Route optimisation
• Scheduling
• Staffing and resourcing

AI can handle many of the tedious, complex, or large-scale processes that these components entail – freeing up valuable time for your business operations. Here’s how it does it.

Predictive Analytics

Predictive analytics involve a deep understanding of factors at various stages of the logistics process. This is already possible through human planning, but AI takes it to the next level with larger databases, quicker processing, and more accurate results.

Demand Planning

Demand forecasting is incredibly useful for not over- or under-stocking your products. This prevents customer disappointment, maximises your revenue, and lowers the potential for dead stock. AI can predict trends based on a wide range of factors, making it ideal for demand planning.

Route Planning

Even the route your goods take, whether at the last mile or throughout the logistics journey, can be optimised by AI. This could involve discovering the perfect string of delivery methods to cut costs and delivery times that could otherwise be inefficient to map out by a human planner.

Alongside your general supply chain, your inventory management can also be optimised through the use of AI. In particular, predictive analytics play a large role in this process – anticipating customer demand, updating stock levels, and feeding through order recommendations.

Stock Management

Predictive analytics for stock management involves a combination of demand forecasting and agentic capabilities. By having your AI agent communicate with your stock software and orders site, you can keep both places up to date, and inform any future stock production based on buyer trend analysis.

Buyer Trends

Analysing buyer trends for both your company, and the wider market, are an important part of your predictive analytics. AI casts a wide net over many different factors, and is able to predict trends based on factors that might otherwise go unnoticed.

E-Commerce Integrations

Integrating your e-commerce software with AI is another great way to improve your inventory optimisation. It offers an interconnected way of working, feeding data directly into AI that can enhance its outputs and tailor it to your business. AI could even serve as a fulfilment agent, completing orders and replenishing stock autonomously as needed ­– creating an e-commerce platform that truly works for you.

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AI comes with a large amount of data, primarily as this is needed to train its understanding and responses. With this data comes an opportunity for you to reduce your overheads and make tactical decisions that bring in more revenue. While AI does come with a cost itself, it can lead to a number of cost-saving benefits, which include:

• Reducing your margin for error by making decisions based off a broad range of data
• Lowering the amount of time needed by human operators through rapid machine operations
• Increasing the value of customer feedback with quick analytics and insights through AI customer service agents
• Highlighting deficiencies in your supply chain, or even your products, and leading to a more efficient production and delivery process.

Alongside your general supply chain, your inventory management can also be optimised through the use of AI. In particular, predictive analytics play a large role in this process – anticipating customer demand, updating stock levels, and feeding through order recommendations.

Stock Management

The best part of AI in logistics is that it’s a new technology. There is still plenty more room for it to grow, and dozens of potential applications that have yet to be realised.

Investing in this technology now will only make it easier to adopt in the future, leading to even more benefits down the line. However, that future is uncertain, so it’s good to temper your expectations by first looking at the trends.

In the future, AI could have:

1. Greater Accuracy. More sophisticated reasoning could lead AI to produce more accurate outputs, reducing the margin for error and speeding up your logistics processes.
2. Increased Datasets. Access to larger amounts of data gives AI a better overview of customer behaviours and user patterns, meaning it can produce more accurate, tailored outputs.
3. Improved Integration. As it stands, the application of AI is rather limited when it comes to integrating with the supply chain. However, future versions like Agentic AI could seamlessly fit in with your existing systems and begin producing measurable results.
4. Driverless Vehicles. From Amazon drones to self-driving vans and cars, driverless vehicles have long been a pipe dream for logistics. A more adaptable and aware AI could make this a reality, safely delivering goods to passengers in select areas without the need for a human driver. In this regard, the ethics of both who is responsible for the vehicle in the event of an accident, and the ethics of replacing human jobs, are still being considered.

AI is already making waves in every industry, and your logistics is no exception. Sadly, it doesn’t quite have the capabilities to do everything quite yet, but it is still a useful tool that can enhance the cost-effectiveness of your logistics operations.

If you want access to logistics backed by the latest techniques and technologies, then Allegro Logistics have you covered. Our streamlined service helps bring your goods from A to B with low costs and no hassle. Get in touch today to get started.

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