We've just begun to scratch the surface of the impact of machine learning on the enterprise. Organizations are applying machine learning algorithms to business processes to automate manual tasks and identify patterns in transactional data to drive strategic decisions. Many applications are focused on efficiency and automation, but that trend is shifting. More and more businesses are using machine learning to develop disruptive new business models. What does this mean for your organization?

Just shy of 60 years old, machine learning has never looked so good. Exponential data growth, advanced algorithms, and powerful computer processing are enabling the technology to fulfill its ultimate destiny: identifying profitable opportunities and avoiding unknown risks by evaluating massive volumes of complex data and delivering accurate results in real time. However, during the Americas' SAP Users' Group (ASUG) Webcast "Guide to the Machine Learning Galaxy: How Your ERP Knowledge Enables Value-Driven Intelligent Processes," Darwin Deano, principal and chief SAP Leonardo officer, and Denise McGuigan, senior manager and Deloitte reimagine platform leader (both from Deloitte Consulting LLP), forewarned that machine learning is only as good as the algorithm. And the algorithm is only as good as the data. Deano advised, "Data evolves over time. Even though ERP systems provide a strong foundation for identifying opportunities and delivering on the promise of machine learning, it does not factor in information outside the core structure, nor does it move with information as it changes."