on August 15, 2019
In a study published by The Hackett Group, 66% of supply chain leaders say advanced supply chain analytics are critically important to their supply chain management. But surprisingly, supply chain managers are still asking what supply chain analytics actually are.
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 their 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 an astounding amount of 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 inventory, materials, production, and manufacturing fees, finding ways to make the supply chain work robustly and efficiently can literally mean the difference between a profit or a loss for a business.
And not just financially. Consistent and reliable supply chain management is the key driver of success across the board from increased sales to faster order fulfillment to customer satisfaction. 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, 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. Effective it’s a dashboard telling 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. These supply chain
° 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 and inventory management issues. Predictive analytics can help 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 and 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 optimize 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.
So why are supply chain analytics so important?
Supply chain and real-time data analytics make businesses smarter, quicker, and more efficient across the entire length of the supply chain and organization. A recent Gartner survey revealed that 29% of surveyed organizations said they have achieved high levels of ROI by using analytics.
Effective use of supply chain analytics allows businesses to better understand and predict future risks by identifying patterns and trends throughout the supply chain.
By analyzing real-time customer data, supply chain analytics can also help businesses predict future demand allowing for informed decisions on purchase orders, RFQs, new products, and end-to-end customer needs.
Supply chain analytics can be used to monitor warehouse inventory, responses from partners and suppliers, and other aspects of the supply chain to achieve a leaner, more productive supply chain across the board.
In the modern world, your business needs a modern approach to analyze the complexity of a global supply chain. Supply chain analytics allow businesses to parse through, understand, and implement changes to ensure their supply chain management is optimized for the 21st century.