As the world moves toward data and analytics to evaluate progress (and it should), we need to be careful that the movement is meaningful. This must-read is full of cautionary tales, including a chapter on medicine, of mis-use of metrics to evaluate performance that ended up doing more harm than good and box-checking in place of real evaluation. The author also makes a strong case that the growing performance measurement industry and its costs are crowding out the resources needed to achieve the goals we are measuring. He gives examples of the growing attention shift toward what is quantifiable that leads to neglect of less-tangible, but more important skills. The author acknowledges the value of using data to measure progress, giving three powerful examples of successful metric use to improve health. But he also describes the harm of paying providers based on quantifiable quality and savings metrics, that lead to stinting on care and cherry-picking more lucrative patients. He described how changing executive compensation at Mylan coincided with a six-fold increase in the cost of EpiPens. At the end, he gives a concrete Checklist of When and How to Use Metrics that every policymaker should have tacked over their desk. We have to be much much smarter about how we collect data, what we we collect, and what we do with it.