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PowerBI Materiel Readiness Brief

Your week back, every cycle.

Maintenance reporting automation that gave Marine units their hours back — and built the on-ramp for AI adoption.

35.5 → 2.5 hrs per unit, per reporting cycle — a 93% reduction in manual effort
From Data to Readiness: The PowerBI MRB Initiative — click to view full size.

The challenge

Materiel readiness reporting in Marine Corps units was a manual, repetitive burden. Each reporting cycle, maintenance personnel consolidated equipment data by hand into recurring readiness briefs — roughly 35.5 hours of staff effort per unit, per cycle. The process pulled skilled Marines away from actual maintenance management, and by the time a brief reached leadership, the picture it painted was already aging.

The approach

RIG built the Materiel Readiness Brief as a Power BI-driven automation layer over the unit's existing maintenance data — a catalyst for moving the Service toward a “servant-focused” data model in which reporting tools serve the operator instead of consuming them.

  • Automation over re-entry: maintenance data flows into a prebuilt Power BI model instead of being reassembled by hand every cycle.
  • Low barrier to entry: deployable by any unit with minimal Power BI proficiency — no specialized training pipeline required.
  • Collaborative adaptability: piloted with 2d LAR Battalion in November 2024, then tailored by 3rd Battalion, 2nd Marines — validating that the tool flexes to different unit structures.
  • Scaling roadmap: a defined technical path — license upgrades, custom GCSS reports to align data across the hierarchy, direct-query capability, and scaled refinement — so adoption can grow beyond the pilot units.

The outcome

Reporting effort dropped from 35.5 hours to 2.5 hours per unit, per cycle. Leadership gets a current readiness picture instead of a stale one, and maintenance Marines get their week back. Because the brief standardizes how readiness data is structured and consumed, it also serves as a strategic entry point for future AI adoption — the foundation is in place before the first model is ever trained.

93% less manual effort35.5 hours of consolidation work reduced to 2.5 per reporting cycle
Multi-unit validationPiloted by 2d LAR Battalion, adapted by 3rd Battalion, 2nd Marines
No training pipelineUsable with minimal Power BI proficiency out of the box
AI-ready foundationStandardized data structures that future AI tooling can build on

Working with RIG

USMC Veteran-Founded PMP Credentialed SAM Registered CAGE 1ZQ50 UEI RCK1Q86TJ946 DoD-Aware Delivery

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