Manufacturers have access to more data than ever before. But in an era when industries are being transformed by groundbreaking innovations, why don’t more supply chain professionals have tools to automate reporting and surface insights that drive real impact? Using the same tools that have been around for decades doesn’t work anymore; information is outdated by the time it’s ready for use. Today, the world’s biggest aerospace manufacturers are using predictive analytics to drive a new era of collaborative intelligence. With collaborative analytics, companies bring their data and people together to solve inventory optimization problems and make impactful decisions faster and more confidently.
In this session, LeanDNA CEO Richard Lebovitz is joined by manufacturing leaders from Morgan Advanced Materials to discuss how supply chain transformation is driven by people—not analytics alone. They’ll share how the real-world application of AI-driven, collaborative analytics has brought people and data together at Morgan and other companies, allowing teams to tackle common challenges and drive real, lasting business improvements.
- Learn how to connect teams, suppliers, managers, and executives across all sites in the organization with collaborative analytics
- Understand potential new analytics tools offer for improving on-time delivery performance into the 95th percentile or above while reducing inventory by an average of 13.5 percent in the first year
- See how prescriptive supply chain analytics help create a culture of accountability with visibility and action tracking
Why Is It Important?
Over the last 15 years, the aerospace manufacturing sector has experienced major organizational disruptions through global outsourcing, demand growth, and increased aircraft platform complexity. More than one manufacturer has landed in the news for missing target delivery dates and being the cause of airplane completion delays. Many of these issues could have been predicted—and avoided—had manufacturers effectively used the data within their systems to make critical business decisions. Historically, extracting those advanced analytics from the IT department and delivering them to actual users was a cumbersome, time-consuming, expensive process that required an ERP, multiple spreadsheets, phone calls, emails, and myriad other tools. The limitations of these legacy technologies can thwart the goal of improving end-to-end supply chain performance. However, leading companies are transforming at a rapid pace. These companies are adopting new digital technologies and artificial intelligence (AI) to transform traditional supply chain management and automate labor-intensive, repetitive tasks and processes such as tactical procurement, inventory optimization and supplier performance management.
Purpose-built predictive and prescriptive analytics are replacing the antiquated ways of the past and providing advanced decision-making tools that help companies optimize inventory decisions while providing specific actions that they need to take to improve their bottom lines. These advanced analytics, linked with deep domain expertise, are coming together to create solutions that provide dashboards and workflow supply chain professionals require to optimize today’s most complex operations. As inventory and supply chain systems become more complex, they actually require more advanced processes to translate that data and insights to help reduce inventory, improve performance, and increase efficiency.