PowerBI Materiel Readiness Brief
Twenty-two hours back, every cycle.
For battalion maintenance leaders who were spending most of a work week every reporting cycle assembling a readiness brief by hand. Built by RIG's founder as a battalion maintenance officer.
Who it is for
Maintenance chiefs and officers who owe their commanders a recurring materiel readiness brief. Before the brief was automated, each cycle took roughly 35.5 hours of combined staff effort: pulling maintenance data, reformatting it, reconciling numbers that did not match, and rebuilding the same slides. Skilled maintainers were spending that time as data clerks, and by the time the brief reached leadership the picture was already aging.
What changed in their work
Total effort fell from 35.5 hours to 13.5 per cycle, about 62 percent, and the brief's principal owners now spend 2.5 hours on it. Leadership gets a current readiness picture instead of a stale one, and the hours that came back can go to maintenance management instead of slide assembly. The review itself changed too: with the assembly work gone, it stopped being a status recitation and became a decision forum on root causes, owners, constraints, and actions.
The brief was piloted with 2d LAR Battalion in November 2024, then tailored by 3rd Battalion, 2nd Marines, and it earned a Notable Achievement in the inaugural Marine Corps Innovation Challenge (2026).
How adoption was designed
- Low barrier to entry. Usable with minimal Power BI proficiency, because adoption could not depend on a training pipeline units did not have time for.
- Built to flex. A second battalion tailored it to its own structure instead of receiving it as a mandate.
- A path past the pilot. License upgrades, custom GCSS reports to align data across the hierarchy, and direct-query capability give it a defined route from pilot to enterprise.
How it is built
A Power BI automation layer over the unit's existing maintenance data: the data flows into a prebuilt model and the brief assembles itself. Because it standardizes how readiness data is structured, it also lays the groundwork for future AI tools, which depend on exactly that kind of clean, consistent data.