<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/b0f20f83a33c4cf4974f8f7cbc4cd3d3&quot; frameborder=&quot;0&quot; width=&quot;1206&quot; height=&quot;904&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>904</height><width>1206</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>904</thumbnail_height><thumbnail_width>1206</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/b0f20f83a33c4cf4974f8f7cbc4cd3d3-00001.gif</thumbnail_url><duration>103.19</duration><title>How Enertiv Tracks (and Predicts) Equipment Conditions</title><description>In this video, I will discuss one of the most challenging aspects of the capital planning process, which is knowing when to make equipment replacement decisions. Often, asset managers and operations teams rely on rules of thumb and personal memories to make these determinations. However, with the right data, these decisions can be made more effectively, resulting in deferred capital costs and timely investments. I will explain how our energy platform&apos;s equipment conditions feature helps in making these determinations on your behalf by calculating runtime hours and tracking equipment conditions. By leveraging both predictions and manual assessments, we can ensure that equipment is being used optimally.</description></oembed>