video1.0<iframe src="https://www.loom.com/embed/487ae077962b4756b7ce24ec9f4381b9" frameborder="0" width="1720" height="1290" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>12901720Loomhttps://www.loom.com12901720https://cdn.loom.com/sessions/thumbnails/487ae077962b4756b7ce24ec9f4381b9-c023fe8b86fd981e.gif248.333333This Loom announces a new warehouse AI capability to deploy a labor management system. The speaker explains that with the right data and algorithms, sites can build their own labor management software to track productivity by person and shift, compare earned versus direct hours, and analyze pace versus engineered standards to maximize throughput and minimize cost. The demo shows overall performance at 86.6% for the week, with example variances such as case pick measuring 40.1 seconds versus a 35.4-second standard and another case pick area at 30.3 seconds versus a 55-second standard. It also covers analyzing time allocation for roles like material handlers and identifying productivity drops around breaks and post lunch roll times, including differences in volatility between first and second shifts.