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How Can Predictive Supply Chain Analytics Strengthen ERP Systems?

November 5, 2013BY AMS Editor

Supply Chain AnalyticsPredictive supply chain analytics can strengthen ERP systems if distributors can integrate their individual applications.

A post on the Logistics Viewpoints blog discusses a new methodology called predictive replenishment, which the author says “generates value by integrating strategic, tactical and operational processes.”

The strategic function would include a supply chain network design that constantly evolves and connects products to processes downstream. The tactical function employs demand sensing and inventory optimization to forecast demand using point-of-sale information and other “market-driven demand signals.” The operational function uses order fulfillment and transportation planning to develop orders and shipments.

Bringing predictive supply chain analytics into the integrated set of supply chain applications merely means an expansion of the definition of ERP. Traditional ERP systems strived to provide an end-to-end application for managing supply chain operations. Now that new items such as predictive analytics and dynamic supply chain design exist, they should ideally become part of a new, expanded ERP system.

In the short term, if companies don’t have these integrated capabilities in their existing ERP and aren’t planning to change ERP systems, then they need to look to robust enterprise integration applications. A good EIA will help to ensure that data flows from one application to the other in a consistent, predictive manner with little or no manual resource requirements.

The Logistics Viewpoint blog post goes on to say that implementing predictive analytics requires good, granular analytics so that a company can understand and then act on buying pattern data.

The bottom line is that the ideal ERP for today’s environment includes not only traditional ERP functionality, but also functionality for predictive analytics, dynamic supply chain network design, and automated creation of the perfect order using functions that include available-to-promise calculations.

While analytics started as an enterprise-class solution, it’s now filtering down to the midmarket level. It’s not just for large distribution supply chains. Midmarket distributors and retailers must take advantage of the edge that supply chain analytics can provide to stay competitive.

Source: Logistics Viewpoints, October 2013

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