Machine learning—it’s a ubiquitous buzzword that’s used loosely but at the same time widely misunderstood. Like many powerful technologies, machine learning has the potential for great business benefit, but if wielded in the wrong way can result in wasted time and resources, and poor business decisions.

We’ve compiled six important tips for businesses considering applying machine learning to supply chain planning problems, based on our nearly 10 years of experience building and delivering machine learning solutions. You’ll learn important points every supply chain organization should consider before diving into a demand planning machine learning project, including:

• How to set and track specific business objectives at the start
• A phased approach for a solution that meets your objectives today and as your needs change
• How to apply the four dimensions of machine learning data: volume, granularity, quality, and variety
• Insight into operationalizing your machine learning solution for sustainable business value
• Tips for assembling the right team with the skills and resources to ensure success

As many as 75 percent of companies are still using spreadsheets to optimize their inventories. And most still use ABC Classification, which dates all the way back to 1951. 

Increasing supply chain complexity and demand uncertainty is creating a staggering array of variables, leaving planners that rely on last century’s solutions with little chance of meeting both service levels and financial goals in a sustainable way.

There’s a better way to optimize inventory. Service-driven inventory optimization is the new and proven way to optimize inventory in the digital age.  This ebook, based on hundreds of successful deployments, will introduce you to the new building blocks for optimizing inventory in the digital age so you don’t get left behind.  It will reveal:

• Why traditional approaches are incapable of meeting today’s long-tail demand complexities
• Why probability forecasting is replacing the traditional ‘one-number’ deterministic forecasting approach
• Important considerations for selecting the right IO solution
• How businesses like yours are slashing inventory and increasing service levels using a service-driven strategy

American companies across the board are striving to reduce their dependence on China as a source of manufacturing, but one industry sector is especially keen to bring production back to the U.S.

Kunal Mehta, head of consulting with Blueprint, says 3D printing has an opportunity to prove its value as manufacturers struggle with disruptions in supply chains triggered by the coronavirus pandemic.

Modern technology provides us with a dazzling array of devices, machines and vehicles designed to create more efficient supply chains, promote a cleaner environment and generally enrich our lives. But none of it runs without batteries.

Benchmark your freight performance with the latest national and regional shipping volumes and expenditures.