The manufacturing and distribution environments are becoming more complex every day. Where 20 years ago it was enough for an aerospace manufacturer to build aircraft that flew efficiently, the same factory is now being asked to accommodate different seat arrangements; a wide variety of cabin interior options; and myriad different colors, media devices, and other fine details. “The number of options has proliferated and added a lot of complexity to the supply chain,” says Richard Lebovitz, LeanDNA’s CEO, “across nearly all manufacturing verticals.”

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In a recent Supply Chain Management Review study exploring the information and analytics needs of supply chain professionals, it was immediately clear that a new horizon is in view for supply chain professionals around the world. Leaders see the need for better tools—tools that do more than just provide data about where they’ve been. One of the most compelling research findings addresses the obstacles leaders face when implementing new supply chain analytics tools into their systems. Here’s a look at the breakdown of responses.

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In a new special edition white paper, the Supply Chain Management Review shows how LeanDNA drives supply chain efficiency by moving manufacturing teams from slow, manual spreadsheet analytics processes into a high-speed, cloud-based platform that is purpose-built to tie together shortage reduction, supplier management, lean principles, and more.

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In a new special edition white paper, Zodiac Aerospace reveals how they used LeanDNA’s collaborative analytics platform to get rid of slow, manual spreadsheet processes and save millions of dollars through better-informed decisions and automated prescriptive analytics.

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Cut Through the Data Craze With Collaborative Analytics

When business analytics first became available to US companies in the 1950s, capabilities were limited and technology was often prohibitively expensive. It was decades before most companies made analytics a standard practice in their organizations. Business leaders continued to rely on their experience and intuition to make critical decisions. But as analytics technology evolved, insights became more valuable and leaders took notice. By the 1980s, most large companies were employing some form of analytics for decision support.

Fast forward 30 years and companies like General Electric are making multi-billion dollar investments in their analytics infrastructures. It’s more than just Big Data; leaders know that their data is only as valuable as the insights it provides. As analytics have evolved and improved, decision-makers are demanding more from their analytics than ever.

Continue Reading “People, Not Data, Will Transform Your Supply Chain” →