Supply Chain Analytics

Every day, every hour, every second, millions of parts, packages and shipments move their way down the supply chain. Around the world, businesses rely on the supply chain to ensure their products are delivered on time, and their customers are kept happy. Like most things in today’s world, this volume of activity comes with a good amount of real-time data – real-time data that your business needs to ensure that the supply chain keeps moving effectively and efficiently.

The insight supply chain analytics provide goes to the heart of how businesses perform overall. With significant amounts of cash resources tied up in inventories, materials, production and manufacturing fees finding ways to make the supply chain work harder and more productively can literally mean the difference between life and death of a business.

And not just financially. From increased sales, faster order fulfillment and customer satisfaction, consistent and reliable supply chain management is the key driver of success across the board. An investment in supply chain analytics is an investment in the future of your business.

Starting with the procurement of raw materials and extending through production, distribution and transportation, effective supply chain management requires the use of big data and supply chain analytics to ensure supply chain visibility across every facet of an organization.

Supply chain analytics allow businesses to make data-driven decisions based on relevant, real-time data visualized for easy consumption. Supply analytics make use of the multitude of available data to uncover patterns and insights along the length of the supply chain to help inform business decisions and correct inefficiencies along the supply chain.

Different types of supply chain analytics include:

    Descriptive analytics. These supply chain analytics provide for supply chain visibility, allowing for both internal and external real time data analysis. Effectively, it’s a dashboard telling you what’s happening now. Examples of descriptive analytics include average supplier lead time, number of dollars invested in inventory and other things you need to know to keep your operation running smoothly and efficiently today.

    Predictive analytics. These are the supply chain analytics that help organizations understand future scenarios and their business implications – things like disruptions to the supply chain, inventory management issues and other potential issues can mitigate risk and inform future decisions. This is telling you what will happen in the future.
    Examples of predictive analytics include forecasts for inventory management, estimated product demand – these are descriptive analytics, but with an added layer of what’s happening tomorrow.

    Prescriptive analytics. These are the supply chain analytics that help organizations solve problems and inform collaborations for maximum effect. Organizational solutions provided by prescriptive supply chain analytics can come both internally within an organization, or with a logistics, manufacturing or other partner along the supply chain. This is telling you what you should do next. You can use prescriptive analytics to build an effective inventory management system, or optimizing the lead time and manufacturers you use when building out a leaner supply chain. Prescriptive analytics leverage predictive analytics, but allow for more operational capabilities.