The process mining field came here to stay. This is demonstrated by the growing interest in the last decade, both in academia and industry. Being at the intersection of many disciplines, process mining techniques transform structured information into valuable models, which provide a fresh and formal insight into the real execution of processes within an organization. Still, there is way more to do than what has been accomplished: process discovery techniques may suffer from noisy, incomplete event logs and may fail to choose the right representational bias; conformance checking suffers from the inherent complexity of working at the state-space level, and in case of large inputs this fact prevents from enhancing process models with additional perspectives. In this paper I will provide an historical overview of the field, describe its current challenges, and vaticinate its long-term future.