The A&D Readiness Gap | Part 1 of 3

In December 2025, Boeing completed its acquisition of Spirit AeroSystems, reintegrating roughly 15,000 employees and the production of 737 fuselages back in-house. The move wasn’t about building more planes. Boeing already had the factory space. It was about building the operational capability to produce them reliably: direct control over quality, stability, and the supply chain systems that connect design to delivery.

That decision signals something bigger than one company’s strategy. Across aerospace and defense, healthcare, and financial services, organizations are investing aggressively in expansion while the operational systems that convert investment into performance lag behind.

The result is a widening readiness gap between what organizations can theoretically produce and what they actually deliver. Leaders are confusing scale with readiness, investing in volume without fixing the system constraints that prevent throughput.

Leaders are confusing scale with readiness, investing in volume without fixing the system constraints that prevent throughput.

Throughput is a systems problem, not a space problem

The aerospace and defense industry offers the clearest illustration of this gap because the data is so stark.

Commercial aircraft backlogs now exceed 14,000 units, roughly a decade of production at current rates, and defense backlogs have surged 24% in just two years to $747 billion. Investment is flowing, but output is not matching. The structural mismatch between airline demand and production capacity is unlikely to normalize before 2031.

When executives see backlogs of this magnitude, their instinct is often to invest in more capacity: more factories, more lines, more capital. But the constraint is somewhere else entirely.

A Roland Berger survey of aerospace companies found that 65% cite personnel shortages as their primary constraint, while only 34% point to missing production capacity. The bottleneck isn’t square footage.

Recent McKinsey research reinforces the point directly. Targeted operational improvements have helped defense manufacturers boost production rates by 50 to 150% within 12 months, by unlocking capacity that already existed in their current footprint, assets, and workforce. The implication is clear: operational readiness first, then capital investment, not the other way around.

The capacity is there. The systems to use it often aren’t.

In my experience leading transformation programs across major A&D organizations, the companies that achieve sustainable production growth invest as deliberately in operational capability as they do in physical capacity. Simpler, well-governed solutions deployed consistently outperform sophisticated architectures that never scale.

Where the readiness gap shows up

This gap becomes visible across several dimensions. Three in particular recur across industries.

The workforce you can’t hire fast enough. The Aerospace Industries Association reports industry-wide personnel turnover well above the national average, with persistent shortages in engineering and skilled trades that directly constrain production. A&D turnover ran roughly 13% in 2023, more than triple the U.S. average of 3.8%, with attraction and retention challenges intensifying through 2025.

The demographics make it worse. The average certified aircraft mechanic is 54 years old, and over one-third are already past 60. Across the broader A&D workforce, a quarter of employees are at or beyond retirement age.

These numbers tell a story about where throughput actually lives. New facilities require training periods before reaching full productivity, and institutional knowledge takes years to develop. Workforce capability simply doesn’t scale on the same timeline as factory construction.

The problem is even more acute below the surface. As a recent War on the Rocks analysis argued, the true bottleneck in U.S. weapons production isn’t the prime contractors. It’s the tier 2 and tier 3 suppliers, often capital-constrained, thinly staffed, and operating with no slack.

The Department of Defense has lost more than 40% of its small business suppliers in the past decade. No amount of prime-level expansion compensates when the lower tiers can’t keep pace.

And while traditional suppliers struggle, a different kind of competitor is emerging. Defense tech startups raised a record $49.1 billion in 2025, nearly double the prior year. Companies like Anduril Industries, which grew revenue from approximately $236 million in 2022 to over $1 billion in 2024, are operating on fundamentally different production models: self-funded R&D, software-defined architectures, and manufacturing timelines measured in months rather than years.

Anduril’s announcement of Arsenal-1, a 5-million-square-foot autonomous weapons production facility in Ohio, signals an intent to compete not just on technology but on industrial scale. Traditional primes aren’t losing contracts to budget constraints. They’re losing them to companies that treat operational readiness as a core design principle.

Health systems are living a version of this same dynamic. The 2025 NSI National Health Care Retention & RN Staffing Report found hospital nurse vacancy rates at 9.6% with RN turnover at 16.4%, producing an average $4.75 million in annual turnover-related losses per acute care hospital.

Like A&D, the response has largely been to spend on the symptom (travel nurses, sign-on bonuses, retention incentives) rather than build the operational systems that reduce the dependency, like standardized onboarding, knowledge transfer from experienced clinicians, and staffing models that flex with demand. Expanding beds doesn’t increase throughput when the workforce to operate them isn’t ready, and paying more for the same constrained labor pool doesn’t change the math.

Quality systems that can’t keep up with volume. Quality management in A&D manufacturing operates under stringent standards, with every production line adding hundreds of inspection points. Manual processes that work at lower volumes become constraints at higher ones.

Boeing’s recent trajectory illustrates this directly. After implementing increased inspection points at Spirit AeroSystems, the company reduced 737 fuselage defects by an average of 45% since March 2024. But that improvement required additional quality resources, additional process time, and ultimately the decision to bring the entire operation in-house. Production capacity existed long before the quality infrastructure could support it.

Financial institutions face a structural version of the same constraint. IBM’s Institute for Business Value found that 94% of core banking modernizations miss their timelines. The reason mirrors what happens on a production floor: legacy core systems carry decades of compliance logic, data dependencies, and business rules that each need validation during migration. At smaller scale, teams manage. At enterprise-wide modernization, those governance layers become the bottleneck, just as manual quality checks do when production rates increase. The technology investment is happening. The operational infrastructure to absorb it hasn’t caught up.

Data that doesn’t connect. In A&D, engineering, production, quality, and supply chain data frequently reside in separate systems that don’t communicate. PLM, MES, quality management, and ERP platforms each hold a piece of the picture. A typical commercial aerospace OEM works with more than 200 direct tier 1 suppliers and 12,000 tier 2 and tier 3 suppliers. Coordinating information across that network through manual processes and disconnected systems is a constraint that more factory space won’t solve.

This fragmentation carries a compounding cost beyond slowing human decision-making. It prevents predictive analytics and automation from functioning at scale.

Organizations investing in AI and machine learning discover that the models require integrated data foundations that don’t exist yet. The readiness gap determines whether those investments produce outcomes or remain experiments.

The pattern isn’t industry-specific

Step outside A&D and the same structural dynamic is visible.

In healthcare, hospital expenses rose 7.5% in 2025 while operating margins held at roughly 2%, according to Kaufman Hall’s National Hospital Flash Reports. The sector is spending more but isn’t producing proportionally more.

Hospital M&A tells a related story: 2025 transacted revenue hit a record low of $18.5 billion, with 43.5% of deals involving financially distressed organizations, a new high. Systems are consolidating, but the underlying operations are strained.

In financial services, banks have increased technology spending by approximately 9% annually, outpacing revenue growth of 4%, yet many struggle to demonstrate measurable returns. The pattern is the same: more investment, not proportional outcomes.

The details may differ but the structural pattern is the same. Investment in expansion is outpacing investment in the systems that convert expansion into performance. The organizations pulling ahead aren’t those spending the most; it’s those building capability alongside capacity.

What leaders should be asking

If your expansion isn’t delivering proportional returns, the question isn’t whether to invest more. It’s whether the underlying systems can convert that investment into output. That question applies whether you’re ramping a production line, scaling a health system, or modernizing a core banking platform.

It also explains why most AI initiatives stall at pilot. The technology typically works, but the operational systems to support it often don’t. Data integration, governance frameworks, workforce capability, standardized processes: these are the foundations that determine whether any investment in expansion or technology produces returns. Organizations that skip the systems work will keep getting the same result regardless of what they layer on top.

Transformation fails less because of technology and more because of misaligned incentives, unclear ownership, and over-engineered solutions. The organizations that will lead their industries in the next decade aren’t necessarily those with the largest capital budgets. They’re those that recognize readiness as the precondition for performance and invest accordingly.

The harder question, what building that readiness actually looks like in practice, is where most transformation programs fail and where organizations that get it right will separate from the rest.

That question becomes even more urgent when the investment is in AI, where the gap between a successful pilot and enterprise-scale production is almost entirely a readiness problem. That’s where this series goes next.

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Active Digital helps organizations close the readiness gap between capacity and capability, building the operational readiness that turns infrastructure investments and AI initiatives into measurable performance, at industry speed.

Courtney Schultz is a Director at Active Digital, specializing in large-scale digital and AI transformation in highly regulated environments, with deep experience leading complex programs across aerospace & defense and enterprise operations.