Case study
CNAFR Enterprise Planning and Force Development
Enterprise planning and force development for Navy Reserve aviation, a large and spread-out organization where the hard part is keeping a lot of moving pieces pointed in the same direction.
Purpose
Enterprise planning and force development for Navy Reserve aviation, a large and spread-out organization where the hard part is keeping a lot of moving pieces pointed in the same direction.
Overview
This is my current job, doing enterprise planning and force development at Commander, Naval Air Forces Reserve, or CNAFR, one of the Navy's largest and most spread-out aviation organizations.
The enterprise covers reserve aviation squadrons, support facilities, training commands, and functional organizations scattered across the country. Planning at this level means taking fleet and joint guidance and turning it into real decisions about force development, capability, infrastructure, and readiness for a force that works on reserve schedules.
What this work involves
A lot of the work is force development. The Aviation Operational Support Force is being reshaped to support distributed carrier operations and expeditionary basing, and reserve aviation has a growing role in it, so I spend time lining up reserve force structure, facilities, and manpower with where the fleet is headed as that design takes shape. Close behind that is capability and infrastructure. Decisions about reserve aviation facilities and basing carry long lead times and real money, and this work connects operational requirements to the facility and infrastructure choices that follow from them.
Much of the rest is coordination. Aviation, logistics, personnel, operations, and facilities each plan on their own timelines and protect their own equities, and getting a senior leader's intent into one coherent plan takes steady work across all of them. Part of that is taking guidance that arrives in raw form and putting it into reserve force planning language pitched at the right level for a workforce that is distributed and often part-time.
Why this connects to AI
The things that make enterprise planning hard are the same things AI-assisted workflows tend to be good at. Institutional knowledge is scattered across people and commands, and the same planning products get rebuilt from scratch every cycle. Doing this job gives me a close, operational view of where AI could genuinely help, from pulling readiness data together to holding onto knowledge as people rotate out and keeping a distributed force aligned.
Current state
This is active work, running alongside the AI workflow and education projects in the rest of this portfolio.
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