Post-Structural Systems Architecture:
Diagnosing and Redesigning the U.S. Army Holistic Health and Fitness System for Autonomous Soldier Readiness

Executive Summary

The Army’s Holistic Health and Fitness (H2F) system is a critical investment in readiness. The H2F system improves performance, recovery, and health across the force (Headquarters, Department of the Army, 2020; Thompson et al., 2026). However, if the H2F program does not deliberately transfer readiness ownership back to the Soldier, it can create a dangerous dependency: a force that performs well in garrison, yet struggles when austere environments strip away expert support, facilities, data systems, and routine oversight.

That dependency is a readiness risk. In a centralized H2F program model, Soldiers may come to rely on embedded experts to interpret data, regulate recovery, plan fueling, and sustain performance. Expert-driven performance can improve short-term outcomes, but it can also create a Human Systems Integration vulnerability (Department of Defense, 2022). A Soldier who requires constant external inputs to maintain readiness becomes a high-maintenance asset in an operational environment that will not reliably provide those inputs.

In Large-Scale Combat Operations (LSCO), units will fight in austere conditions under contested logistics and degraded communications. Combat conditions may degrade or entirely sever access to the Soldier Performance Readiness Center (SPRC), embedded H2F Performance Teams, and the H2F Management System (H2FMS). Under those conditions, a Soldier who cannot self-regulate sleep, fueling, recovery, and training adaptation is not fully prepared for decentralized operations. A readiness program that depends on continuous expert management in garrison may unintentionally produce fragility at the point of need.

This paper argues that Army leaders must evaluate H2F not only by what it improves in controlled environments, but also by what still works when direct program support is no longer readily available. Its central claim is that the H2F program must move beyond expert-managed optimization and toward deliberate capability transfer, so that Soldiers can sustain readiness when combat operations isolate them from the institutional support architecture.

To examine that problem, this paper presents Post-Structural Systems Architecture (PSSA), an original framework that combines Foucauldian discourse analysis (FDA) with Human Systems Integration (HSI) (Foucault, 1995; Department of Defense, 2022). The purpose is to identify credible architectural failure modes and their implications for HSI, not to make universal claims about every H2F program in the Army. This paper uses PSSA not to argue that the H2F system is ineffective across the force, but to diagnose how certain structures and processes within the H2F program may unintentionally reinforce dependency in high-resource environments. Using Soldier narratives from an embedded H2F setting, the paper identifies these dynamics and offers a field-testable architecture to reduce them. 

The proposed solution is an Army Regionally Aligned Readiness and Modernization Model (ReARMM)-aligned transition from continuous expert control to phased Soldier ownership (Headquarters, Department of the Army, 2024). Across the force-generation cycle, H2F Performance Teams should deliberately reduce clinical reliance and build operator-level readiness maintenance. Through coaching methods such as Motivational Interviewing, guided self-regulation, and rapid micro-experiments, practitioners can transfer the knowledge, judgment, and habits Soldiers need to manage their own performance under degraded conditions.

The objective is not to make H2F less relevant. It is to make its effects more durable. In that sense, the highest achievement of the H2F program is not permanent indispensability in garrison, but deliberate capability transfer before combat. The objective is an operationally autonomous Warfighter who can sustain readiness when expert support, facilities, and dashboards are no longer readily available.

Full White Paper coming Q2 2026