Analytics, AI, and Cloud Power Modern Inventory Management

Every stage and function across a global supply chain is critical, given that a failure of any link in the chain can disrupt the overall process. That said, inventory management is arguably among the most consequential of supply chain functions. That’s because it serves as the fulcrum for the entire end-to-end process, balancing the inbound flow of materials and products with outbound shipments to distributors or retailers, or direct to customers.

Ideally, of course, the entire supply chain process is regulated by both existing and expected customer demand. In this regard, inventory management itself must be both reactive and proactive. It must respond rapidly to actual shifts in demand but also use every tool at its disposal to anticipate how demand may change and to adjust supply chain production rates and shipments accordingly.

Fortunately, companies can tap a variety of technologies and services to ensure that they—and their suppliers—can meet fluctuating customer demand. In particular, data analytics, AI, and cloud can help meet these demands. Collectively, these three technologies give companies visibility in two directions: the customer marketplace as well as the chain of supplier, logistics, and transportation players that produce and deliver the necessary products.

Experts recommend following these best practices:

Put data analytics at the core: Big data analytics is one of the most important inventory management aids, especially on the market demand side of the equation. By crunching ever-larger volumes of data, companies have been able to better forecast demand, shifting from reactive to more proactive in the process. The data feeding and analytics engines can include everything from actual sales numbers and trends to social media posts, weather forecasts, and information on labor strikes.

Blend in AI and ML: Big data analytics is increasingly being enhanced with artificial intelligence (AI) and machine learning (ML) technologies. For example, these technologies are helping drive a shift from traditional demand planning methods to automated “demand sensing,” a topic we’ll explore further in an upcoming post.

Utilize the cloud: Better anticipating demand, of course, is of little value if the supply chain isn’t agile and responsive enough to rapidly ramp production and delivery up or down as necessary. Cloud can provide that scalability.

Rethink inventory management: The inventory management function requires end-to-end visibility across the supply chain, and the best way to get this comprehensive visibility is via overarching cloud services encompassing everything from customer raw materials-handling to final customer sales. In particular, several considerations are essential:

• Enabling data gathering on cloud-enabled technology, with API-driven integration as well as traditional interfaces, ensures the most up-to-date data from the extended supply chain, beyond the four walls of the enterprise.
• Visibility into inventory across your supply chain helps improve effective utilization of inventory, in turn minimizing excesses and shortages.
• Real-time visibility into demand and supply changes across network enables supply chains to react faster, minimize the bull-whip effect, and work with leaner inventory without compromising on customer service levels.
• With visibility into demand across multiple tiers, inventory replenishment can be automated to improve operational efficiency.

Like so many other pieces of the supply chain, inventory management must evolve to keep up with changing customer demands. Fortunately, data analytics, AI, and cloud can collectively give companies visibility into the customer marketplace and their network of supplier, logistics, and transportation partners.  

Learn how GEP can help you optimize your inventory management as well as your end-to-end supply chain at www.gep.com.