Description
Book SynopsisNearly all our safety data collection and reporting systems are backwardlooking: incident reports; dashboards; compliance monitoring systems; and so on. This book shows how we can use safety data in a forward-looking, predictive sense.
Predictive Safety Analytics: Reducing Risk through Modeling and Machine Learning contains real use cases where organizations have reduced incidents by employing predictive analytics to foresee and mitigate future risks. It discusses how Predictive Safety Analytics is an opportunity to break through the plateau problem where safety rate improvements have stagnated in many organizations. The book presents how the use of data, coupled with advanced analytical techniques, including machine learning, has become a proven and successful innovation. Emphasis is placed on how the book can meet you where you are by illuminating a path to get there, starting with simple data the organization likely already has. Highlights of the book are the real
Table of Contents
1. Safety in Numbers: A Data-Driven Approach. 2. Analytics Defined. 3. The Safety Data Repository. 4. Use Cases. 5. Where to Go from Here.
