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.
One of the balancing acts for manufacturers and supply chain leaders is having the right inventory levels. But it’s often difficult to identify ways to reduce inventory without sacrificing on-time delivery performance. LeanDNA is featured in this article in Modern Materials Handling, which highlights how our Factory Analytics solution:
- Provides advanced, collaborative analytics focused on inventory, rather than traditional MRP or factory planning tools
- Performs analysis and sizing parameters automatically
- Recommends action opportunities for increased profitability
- Standardizes best practices across the organization
- Improves on-time delivery performance into the 90th percentile or above
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.
I just finished my first day at the Supply Chain Insights Global Summit in Philadelphia and spent the day in the analytics track with manufacturing and technology leaders from across the country. The message from day one was clear: there’s a lot of talk about the technology behind analytics, and not enough focus on the human side that will ultimately yield results.
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.
Modern manufacturing has brought warehouses increasingly into the manufacturing process. According to Logistics Management, Manufacturing Execution Systems (MES) and Warehouse Management Systems (WMS) are coming together. LeanDNA is mentioned as one of the new technologies driving the charge. Read the highlights below or read the full article on Logistics Management.
Digital transformation is necessary for enterprises, but many business leaders don’t know where to start. Recently, TechRepublic created a cheat sheet on the benefits and how-tos of digital transformation, and featured quotes from Richard Lebovitz, CEO of LeanDNA. Below are highlights from the article, or check out the full article on TechRepublic.
¡Hola! Each day, LeanDNA sets out to delight customers and transform supply chains around the world through collaborative analytics. To support our global users, we’re always making improvements and additions to the tool. Today, we are pleased to announce that LeanDNA now offers Spanish language support!
As part of a company-wide initiative to reduce working capital and inventory costs, your leadership has just asked you to analyze your supply base and determine the top 10 suppliers requiring improvement. You need an action plan and KPIs to measure performance improvements for those suppliers—and fast. Your supplier development team is struggling to come up with streamlined ways to track supplier performance, understand the root cause of performance issues, and actually drive improvements. Now it’s time to scramble as a team to develop and implement an improvement strategy. But where do you start? You need the right supplier performance management tools to achieve these objectives.
Supply chain executives are always on the hunt for improvements to efficiency that lead to cost savings. Improving processes is often low-hanging fruit that can be done quickly with the right tools in-hand. In this post, I’d like to show you how our customers have saved millions through inventory optimization and cost reductions by leveraging new supply chain predictive analytics technology that leverages AI and cloud computing. I’ll also touch on Deloitte’s 2018 MHI Annual Industry Report, which discusses trends of next-generation supply chains, and the tools most leaders believe will disrupt the industry. Automation is right at the top of the list.