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.
Every day, supply chain leaders from around the world tell us about their struggles with dirty ERP data. Issues like duplicates, inaccuracies, obsolete data, and missing lead times all lead to increased costs and manufacturing delays. Cleaning up bad ERP data can seem like a daunting task, and it often holds teams back from addressing other technology projects or operational improvements. Where do you start? How will you spare resources to work on it? Is there ever a good time for an ERP data cleansing project?
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.
Artificial intelligence, machine learning, Internet of Things, algorithms, cloud-based software—these buzzwords are commonly heard in the industry, but what do these technologies really mean for supply chains? How will advances in supply chain software affect the future for leaders?
Hello from Chicago! I’m here attending the APICS 2018 supply chain conference, and I’m spending time around some brilliant minds in manufacturing and supply chain. I’d like to share a little of what I’ve encountered here through great speaker sessions and conversations with industry leaders.
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.