Data drives better decisions. That’s the foundation underpinning supply chain analytics, a discipline that allows organizations to mine insights from its procurement, manufacturing, inventory management, warehousing, and distribution activities.


Leveraging these insights, companies gain the opportunity to reduce costs, increase efficiencies, better manage potential risks, plan more effectively, and create a more resilient supply chain that’s capable of flexing in response to today’s challenges.


In this article, we’ll walk you through a complete explanation of supply chain analytics: what it is, why it’s important, what benefits it can offer, and what challenges companies might encounter in this arena. With this understanding, you’ll have a better grasp on this logistics concept—and whether it’s something you want to investigate further.

What Is Supply Chain Analytics?

Supply chain analytics involves analyzing the data from all the activities along the length of a company’s supply chain—including procurement, manufacturing, inventory management, warehousing, and distribution. As a crucial aspect of supply chain optimization, supply chain analytics offers companies the opportunity to make better decisions as they plan, source, produce, and deliver products.


Supply chain analytics may gather data from a variety of different systems: inventory management, order management, warehouse management, and transportation management—among others. Some of these systems may come with their own analytics tools already installed. Other companies may choose an external solution that integrates all of their systems and gathers data in a single spot.


What Is the Objective of Supply Chain Analytics?

The objective of supply chain analytics is to give an organization the data-driven insights it needs to make better business decisions, both now and into the future. Supply chain analytics offers companies a way to spot emerging problems, better manage future risks, plan more effectively for the future, and create efficiencies that reduce both costs and waste.

What Is an Example of Supply Chain Analytics?

PepsiCo’s Sales Intelligence Platform offers a tangible example of the power of supply chain analytics in practice. The company—whose brands include Lay’s, Doritos, Cheetos, Quaker, and Frito-Lay—uses the platform to combine data from retailers along with data from PepsiCo’s own supply chain predict when items will go out of stock. After all, simply put, if items aren’t available on grocery store shelves, they simply can’t be sold.


With the data from their Sales Intelligence Platform, PepsiCo’s field teams can approach store owners with a recommended list of items to stock up on to prevent out-of-stock situations. As a result of its supply chain analytics efforts, PepsiCo has seen a measurable decrease in out-of-stock scenarios, while increasing sales.

What Is the Benefit of Supply Chain Analytics?

Supply chain analytics offer better insight into a company’s operations, including areas that are going well and areas that could be improved. When paired with machine learning tools, supply chain analytics software can transform a massive amount of historical data into useful, actionable information.


All of this allows a company to:


The Challenges of Supply Chain Analytics

Of course, as with any initiative, companies will experience some challenges in their supply chain analytics activities, which include:


Better Data, Better Visibility, Better Decisions

Supply chain analytics offer companies a significant opportunity—a chance to use the past to improve upon the future. This includes the possibility for reducing costs, increasing efficiencies, managing potential risks, and planning more effectively—all of which add up to a supply chain that’s built to last.

Want to talk with our experts further about leveraging technology to manage and optimize your supply chain? Reach out for a complimentary consultation. We’d be happy to help you uncover new efficiencies to help your supply chain perform at its peak.

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