video1.0<iframe src="https://www.loom.com/embed/a889629c90214fdf8e39cc5c9110e6d0" frameborder="0" width="1152" height="864" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>8641152Loomhttps://www.loom.com8641152https://cdn.loom.com/sessions/thumbnails/a889629c90214fdf8e39cc5c9110e6d0-512526f72c44e1c1.gif275.371In 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.