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The Growing Importance of Utilizing Analytics in the Supply Chain

Supply Chain executives can no longer dismiss the importance of using analytics in the supply chain. Analytics provide invaluable insight into business operations of any size, and according to McKinsey and Company, applying analytics in complex supply chain processes can lead to increased capacity, better efficiency, and higher profit margins. To understand the growing importance of using analytics in the supply chain, let’s take a closer look at the driving forces.

E-commerce Generates More Supply Chain Data, Enhancing Analytics in the Supply Chain

Part of the surge in interest in analytics in the supply chain is the direct result of increased eco-commerce. E-commerce generates a vast volume of supply chain data, which can be used to create near-real-time forecasts and accommodate sudden changes in demand. This information can leverage existing and real-time data to identify future trends as well, also known as predictive analytics.

Analytics in Distribution and Manufacturing Benefit Supply Chain Processes

As explained by the Harvard Business Review, predictive analytics have the greatest potential to impact supply chain processes involving storage and infrastructure. The annual spending on storage and infrastructure within supply chains is expected to double by 2020, and this investment will be built with analytics-based tools and resources.

Analytics in the supply chain will help reduce the downtime associated with routine maintenance, identifying indicators of potential system failure earlier, as well as noting Increased productivity through more efficient “routes” for foot traffic within warehouses. Savings derived from analytics should have a positive impact on product pricing, benefitting customers and creating competitive advantage for businesses.

Structured Analytics Move Logically From Identification to Recommendation

Often, predictive analytics take center stage of the Analytics discussion, but it is only part of a much larger system of analytics. Analytics are broken into the following three categories:

  • Descriptive Analytics in the Supply Chain Improve Collaboration, “This Is What Is Happening and Why.”
  • Predictive Analytics Identify Future Problems, Opportunities and Demands. “This Is What May Happen in the Future and Why.”
  • Prescriptive Analytics Determine What Activities Are Needed to Attain the Best Outcome. “This Is What Needs to Happen to Reach the Desired Outcome and Why.”

The logical sequence of descriptive to prescriptive analytics provides a complete, data-driven path from understanding your existing operation and moving toward your business goals. The benefits derived from descriptive, predictive, and prescriptive analytics also counteract arguments against investing in big data and analytics. Furthermore, analytics and reporting enhance visibility across all organization levels, ranging from executives to Operations management at distribution centers.

Analytics in the Supply Chain Will Continue to Grow in Importance

Analytics are not a passing phase of supply chain evolution; they are the cornerstone of all existing supply chain processes. Even companies that have not yet leveraged analytics for in-house improvement are contributing to the Big Data mountain, which is being used by other businesses, says Bernard Marr of Forbes. Rather than waiting for the eruption of the Big Data volcano, protect your company by implementing and using analytics within your legacy and new warehouse systems today. Contact Veridian to learn more about implementing them today.