{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/a889629c90214fdf8e39cc5c9110e6d0\" frameborder=\"0\" width=\"1152\" height=\"864\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":864,"width":1152,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":864,"thumbnail_width":1152,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/a889629c90214fdf8e39cc5c9110e6d0-512526f72c44e1c1.gif","duration":275.371,"title":"Turning 134,000 Work Orders Into Smarter Fleet Decisions","description":"In this video, I walk you through how predictive analytics can transform fleet maintenance decisions, using a project with Raise Holdings as a case study. By analyzing over 134,000 maintenance work orders, we identified over $8 million in potential multi-year savings and developed a model that predicts high-cost repairs with 98% accuracy. Our findings led to a clear decision framework that segments assets into three actionable categories, uncovering $800 million in savings potential. I emphasize that analytics must drive decisions, and we built an interactive dashboard to provide clarity for various stakeholders. I encourage you to consider how we can implement these insights for smarter maintenance strategies."}