CommandIQ turns integrated-resilience training into a readiness picture a commander can act on. This walkthrough follows the Commander’s Readiness Overview for the 99th Airborne Division — an example division — through suicide-prevention (ACE) analytics: from who is ready to intervene, to where usage and outcomes lag, to which capability and which units need attention, to the pattern underneath. Everything below is aggregate and unit-level; no individual Soldier is ever named or surveilled. The same engine extends to other integrated-resilience topics, including sexual assault prevention and response (SAPR).
Watch the 3-minute video above, or follow the beat-by-beat walkthrough below.
Every commander faces the same suicide-prevention readiness question: across the whole division, who is actually prepared to step in for a struggling Soldier, and who still needs practice? This is the Commander’s Readiness Overview for the 99th Airborne Division — one screen, the entire division. Because the training is peer-to-peer intervention rehearsal, the first thing it shows is coverage: a usage heatmap, brigade by brigade and battalion by battalion. Green units are rehearsing well above the division average; pale-red cells are running cold. At a glance you see where the program has taken hold and where it hasn’t.
Coverage isn’t the same as capability, so we switch from usage to outcomes. Across nearly two thousand rehearsed interventions, 82% got the Soldier to safety — and 18% left the Soldier alone. That 18% isn’t a grade; it’s a training signal. It tells you exactly how much room there still is to close the gap before it ever matters in real life.
The model itself is Ask, Care, Escort — the three moves of a peer intervention. The capability profile breaks the division’s performance down across all three. Here, Care is the strongest, but Ask lags well behind — the hardest step is opening the conversation and asking the question directly. That single insight tells a commander where to aim the next block of rehearsal for the whole division.
Readiness is more than outcomes, so the same view carries sentiment and stage. Confidence to intervene climbs from a 4.5 before training to an 8 after; effectiveness and willingness to recommend move the same direction — real belief that the rehearsal works. The stage distribution sorts every Soldier from needs-practice up to ready-to-intervene, so you know not just the average, but the shape of readiness across the force.
The system does the triage for you. The at-risk units card ranks every unit by the rate at which its Soldiers left someone alone — the highest suboptimal rates float to the top. These are the battalions running above the division’s average on the outcome that matters most. This is where a commander spends their attention first.
Click into one of those units and the picture sharpens. For this cavalry battalion, 40% of the combat-arms group left the Soldier alone — 11 points above the unit’s own average. It’s aggregate only; no individual is ever named. But it points a finger: within the tip-of-the-spear population, the intervention is landing least.
The demographic breakdown tells you why it isn’t just a knowledge gap. Filter by time in service and the story inverts what you’d expect: the newest Soldiers do fine, while the longest-tenure group — 43% of them — is the one leaving Soldiers alone. That’s not people who never learned the material. That’s a culture and command-climate signal, the kind a commander can actually act on. The same analytics engine tracks other integrated-resilience topics the same way — sexual assault prevention and response (SAPR), for one — so a single readiness picture can span the whole resilience portfolio.
From one division-wide screen, a commander moves from who’s ready, to where usage and outcomes lag, to which capability, to which units, to the exact pattern underneath — all from aggregate training rehearsal, never individual surveillance. Suicide-prevention readiness you can see, and act on, before it ever becomes a crisis.
Start with the overview
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