The LeanDNA-List celebrates the hard work of our customers, who day-in and day-out work to optimize inventory, reduce shortages, and empower their companies to operate more efficiently. These winners represent the tenacious, knowledgeable, and hands-on users and champions of LeanDNA.
Continue Reading “Integra’s Doug Dollberg, Leader of Growth”
We love space around here. Maybe it’s our collective backgrounds in aerospace, or maybe it’s just our (some may say nerdy) interest in the worlds beyond our own. Whatever it may be, as we fly towards the 50th anniversary of Neil Armstrong’s legendary first steps on the moon, we’re reflecting: On both the impact that moment had in America, and the way it changed innovation in our world.
Collaborative Analytics for Morgan Advanced Materials
Supply chain management is becoming increasingly complex. Today’s manufacturing is more global and requires synchronization of material deliveries from suppliers throughout the world. There is increasing pressure to analyze complex data to prioritize and manage daily tasks, pressures from clients to quickly meet their changing demands, and pressures to deliver on time regardless of the product complexity and routine demand changes. In a time like this, agility and collaborative analytics are vital. Suppliers must utilize timely information shared across all people in the operation. The result of doing so? Clearly aligned critical decision making that keeps up with client expectations.
As the supply chain leader of a large multisite organization, how do you organize and drive an effective, sustainable process to attack the biggest inventory management problems on a daily basis across complex teams with multiple ERP systems? Have you ever been in a meeting where inventory optimization was brought up as a top priority by leadership without clear direction on how exactly to attack the issue?
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.”
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.
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.
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.
It has taken decades for supply chains to adopt analytics at a large scale. For many years, supply chain leaders relied on instinct and experience to make critical inventory decisions. But over the years, as capabilities have grown more powerful and impactful, leaders have seen how much business value can be delivered by implementing advanced analytics.
This infographic traces the evolution of supply chain analytics—from the 1950s when the first large-scale business analytics program was initiated in the U.S., through the present day and into the future as business leaders seek to bring their data and people together in a collaborative analytics platform.
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.