In this episode, we interviewed Gijs Meuleman, CEO of Sensorfy, specialist in predictive solutions for industrial companies. Sensorfy designs and develops predictive maintenance solutions to processes sensor data near the source, with machine learning on the edge.   We discuss how to transform a transactional business model into service-based, data-enabled business that is more closely aligned with benefits realized by the end customer. We also discuss how predictive maintenance impacts operations cost structures to allow leaner maintenance organizations while sustaining service levels.   Key Questions:  Why is predictive maintenance one of the most widely adopted IoT use cases?  How do you evaluate the different parameters to decide if predictive maintenance makes sense in a specific situation?   How do predictive analytics enable business model innovation?  What is the current level of maturing in industrial equipment markets in terms of adopting service based business models?