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Nearly all our safety data collection and reporting systems are backward-looking: incident reports; dashboards; compliance monitoring systems, and so on. This book shows how we can use safety data in a forward-looking, predictive sense. It contains real use cases where organizations have reduced incidents by employing predictive analytics.
Rob is part of the leadership team at First Analytics, a boutique analytical consulting firm. First Analytics designs and implements predictive analytics and machine learning solutions. The firm services multiple industries with many applications. With an enabling engagement model, the firm teams up with its clients to build their in-house capabilities and systems. In his role as Vice President at First Analytics, Rob helps companies develop and execute programs to cultivate their analytics competency. He brings experience to bear stemming from more than thirty years as an analytics professional, starting as an econometrician. His career has consisted of consulting, product development, client service, technical, and sales roles within software, consulting, and market research firms. Rob has participated in or led safety analytics implementations in the railroad, utility, oil and gas, and manufacturing industries. He has spoken on predictive safety analytics in venues such as National Safety Council congresses, an OSHA safety conference, human and organizational learning conferences, manufacturing forums, private analytics consortiums, and conferences and webinars sponsored by software companies.
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.
