When it comes to the management of an effective food and beverage supply chain, Machine Learning (ML) has a great role to play. The technology can reduce waste, improve inventory management, and deliver invaluable planning insights. Let’s take a deeper look. 

1. Overstocking and Understocking

Managing an effective supply chain is all about data. With accurate data food and beverage manufacturers can reduce the waste associated with overstocking and understocking, thereby streamlining their inventory management tools and delivering a fresher product to their consumers. At first sight, it's very challenging to predict accurately how many goods or ingredients you will need. But the most efficient food and beverage businesses invest in specialized enterprise resource planning (ERP) software, and highly customized software as a service (SaaS) applications. Machine learning algorithms power advanced data analysis tools and mitigate the destructive effects of overstocking and under stocking situations. 

2. Improving Transparency 

Supply chain transparency is an important aspect of running a food and beverage manufacturing company. With increasing food safety regulations, manufacturers must be as transparent as possible about the path and detail of their supply chains. Machine learning and AI (Artificial Intelligence) tools can monitor every stage of the supply chain; ensuring complete transparency. Since many food & beverage companies have complex and large product lines, using an electronic food safety management program such as Cashmere can help you track all your products, ensuring total FDA transparency compliance at all times. 

3. Gaining a Competitive Advantage 

When inventory management platforms powered by ML manage a food and beverage supply chain, its users immediately gain a strong competitive advantage in the marketplace. The data supplied by ML informs businesses what their most valuable goods are, and the insights it provides can have a big impact on their profit margins. What’s more, analytical inventory management tools, powered by ML and AI, can also reorganize and restructure a manufacturer’s replenishment process, optimizing their income.

4. Automation

Machine Learning platforms that power and manage supply chains run via automated processes. This means you don’t have to code them, or spend hours of human labour inputting data. The ML tools build prediction and demand planning models automatically for their users — they’re embedded into the platform — so business owners can focus their time on what matters to them. 

5. Reducing Waste and Spoilage

Inventory management software, with machine learning at its core, can ascertain and present the remaining shelf-life of produce, and businesses can more accurately plan for when and where to send this produce. As a result, waste and spoilage is reduced. You’re not assessing the shelf life of your produce by a visual inspection, you’re working with up-to-date, accurate data, and supply chain visibility can finally become crystal clear. 

As Machine Learning continues to evolve and develop and becomes a central focus to the food and beverage industry, leading companies such as Cashmere are spearheading the technology and its capabilities. Get in touch today to learn more!