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
Credit: Google News