Machine learning for procurement analytics

In this episode of the O'Reilly Podcast, O'Reilly's Ben Lorica sat down with Eliot Knudsen, Field Architect at Tamr. Lorica and Knudsen discuss the role of prescriptive analytics in driving business change, using feedback to train machine learning algorithms, coalescing various sources of business data, and the importance of explaining your algorithms in order to relay their value. The idea behind prescriptive analytics is that you're combining forecasting ability with a specific process or change that folks want to drive in their business--whether it's how they onboard their customers, whether it's how they negotiate with their suppliers, whether it's how they move different products or materials through their supply chain. Feedback is one of these fascinating things, where ultimately there are different ways that these systems are tuning and learning. You're growing, and based upon data and other heuristics, you're changing how your algorithms predict and fit themselves to these points.