A major gap is our failure to evaluate long-term affordability as systems mature, whether working with commercial off-the-shelf (COTS) or custom modifications. We default to technical performance and immediate data while neglecting Reliability, Availability, and Maintainability (RAM) metrics.
Executives should build integrated data and financial reporting systems that can track funds and performance across all five appropriations. They also need to stand up cross-func - tional teams that include engineer - ing, logistics, finance, and product support functions to enable holistic life-cycle management. It is further advisable to imple - ment digital models and portfolio- level analytics to unify visibility of both legacy fleet sustainment and new system development efforts. Fi - nally, executives should develop le - gal and process pathways for repro - gramming budget authority as O&M savings emerge, ensuring resources can move fluidly within the portfolio. Key takeaway. The steps listed above enable organizations to shift from siloed programs to an agile, data-driven portfolio approach. Model as a Single Source of Truth Digital engineering reduces func - tional silos by establishing a shared source of truth across program man - agers, systems engineers, logisti - cians, and operators throughout the life cycle. This shared digital baseline supports concurrent engineering, strengthens doctrinal alignment, and enables operational data to refine de - sign assumptions over time. • Concurrent engineering. Logis - ticians are brought into the vir - tual design room on day one to map the mission thread down to individual replacement compo - nents before the physical layout is frozen. • Doctrinal alignment. This enforces compliance with defense acqui -
sition doctrine (e.g., DoD Instruc - tion 5000.88), making systems engineers explicitly accountable for designing reliability and main - tainability directly into the plat - form alongside baseline form, fit, and function. • Closed-loop feedback. As dem - onstrated by modern legacy air - craft teardowns, physical assets can be translated into living digi - tal models. Real-world opera - tional data from the field is fed back into predictive systems, continually tightening engineer - ing estimates and closing the gap between digital digits and physi - cal hardware. (Intelligent defense industry-based predictive main -
tenance framework: Digital Twin perspective, 2026)
Pareto Framework for Executive Action
Leading effectively in a digital ac - quisition environment requires fil - tering out data noise to enable rapid, confident leadership decisions. In - stead of overwhelming executives with thousands of data streams, or - ganizations must apply the Pareto Principle (the 80/20 rule) to isolate the top 20 percent of critical metrics— led by RAM and material cost data— that mathematically dictate program return on investment. By coupling Pareto metrics with predictive cost models and AI-enabled
SEPTEMBER –OCTOBER 2026 | DEFENSE ACQUISITION MAGAZINE 13
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