The Cost of Inaction
Why Engineering Strategy Teams Need Data-Driven Modelling to Guide Technology Decisions
In aerospace and other complex engineering organizations, few teams have as much long-term influence on life cycle performance and costs as those responsible for engineering strategy, technology adoption, and development methodologies. The decisions made here shape not only how aircraft (or i.e. a submarine) are designed and modified, but how they are supported, maintained, and sustained over decades.
This article argues that without quantitative lifecycle modelling, engineering strategy teams systematically underestimate the cost of delaying technology and methodology adoption—and that this leads to higher cost, lower availability, and reduced design influence over decades.
New tools, digital methods, and engineering approaches are continuously evaluated. Yet one factor is often underestimated or left implicit in decision-making:
The cost of not acting.
In this context, “not acting” does not mean doing nothing. It means continuing with established tools, methodologies, and processes instead of implementing and systematically applying the best available alternatives, particularly during early design, development, and modification phases. It includes postponing the adoption of improved design-influence methods, maintainability analysis, lifecycle modelling, or digital engineering capabilities, even when their potential benefits are already understood.
In complex, long-lifecycle programme, such inaction is not neutral. It is a deliberate choice that locks in assumptions, limits future design flexibility, and allows inefficiencies to propagate across development, production, and sustainment, creating measurable technical, operational, and financial consequences over decades.
Inaction Is Not “Standing Still”
Figure 1. The figure shows that influence over life cycle cost is highest early, while costs are progressively committed and realised later. Delaying action reduces influence and makes inefficiencies irreversible.
When engineering organizations defer the adoption of improved methodologies, digital tools, or new support concepts, the Programme does not remain unchanged. Instead, inefficiencies compound over time.
What begins as a “delay” often turns into:
- Higher lifecycle costs
- Reduced availability and performance
- Design decisions that are harder and more expensive to reverse
- Lost opportunities to influence maintainability early, when it matters most
These effects rarely appear in short-term budgets and are typically not visible in early-phase cost estimates and high-level tools which is why they are easy to underestimate.
Where the Cost of Inaction Accumulates
1. Escalating Lifecycle Costs
Decisions made, or postponed, during early design and modification phases have a disproportionate impact on Life Cycle Cost (LCC). Delaying improvements in design influence, maintainability, or support concepts often results in:
- Increased maintenance man-hours
- Longer turnaround times
- Higher repair volumes and increased spare consumption
- Inefficient support structures that become locked in for decades
For complex systems, Life Support Cost (LSC) typically accounts for the majority of total LCC, often in the range of 60–70% over the system’s lifetime. As a result, even small inefficiencies in maintainability, reliability, or supportability can dominate long-term programme economics.
Without quantitative modelling, these costs remain largely invisible during decision-making. They only become apparent once the aircraft is in service, when design flexibility is limited and corrective actions are costly.
For example, a one-hour increase in average corrective maintenance per flight hour, applied to a fleet of five aircraft each flying 2,000 hours per year over a 25-year service life, can result in tens of thousands of additional maintenance hours. When translated into labour costs, spare parts consumption, aircraft downtime, and reduced availability, the cumulative effect can amount to millions in additional lifecycle cost. These costs are typically invisible at design freeze, yet they are fully predictable through early, data-driven lifecycle simulations.
Data-driven lifecycle simulations make it possible to quantify how “waiting” today translates into millions in additional cost over 10, 20, or 30 years, enabling engineering strategy teams to evaluate the true financial impact of postponing action.
2. Reduced Availability and Operational Performance
In aviation and complex defence programme, availability is not only an operational metric, but also a contractual and reputational one.
When you postpone maintainability improvements, reliability growth, or optimized support concepts the outcomes probably are:
- Aircrafts are unavailable for missions
- Suboptimal resource allocation (overinvestment + wrong resources)
- Maintenance becomes reactive rather than planned
- Small inefficiencies multiply across fleets and years
Even marginal reductions in availability can have a significant downstream impact on customer satisfaction, penalties, and long-term programme economics.
3. Missed Design Influence Opportunities
One of the most expensive moments to realize a mistake is after the design is frozen.
Engineering strategy teams understand this, yet without early-phase modelling, it is difficult to quantify:
- How design choices affect maintainability and sustainment effectiveness
- How alternative architectures influence long-term support
- How early trade-offs impact modification costs later in the lifecycle
The cost of inaction here is subtle but severe: once the opportunity to influence design is lost, improvement becomes exponentially more expensive.
4. Fragmentation of Methods and Tools
When formal adoption of new methodologies is delayed, teams often create local workarounds:
- Isolated tools
- Inconsistent assumptions
- Non-standard processes
Over time, these “temporary solutions” harden into systemic inefficiencies that complicate integration, certification, sustainment planning, and knowledge transfer.
The cost is not only financial, it is organizational complexity that slows future change.
Making the Cost of Inaction Visible
Engineering strategy teams are expected to justify decisions with evidence, not intuition.
Data-driven modelling enables teams to:
- Compare acting now vs. acting later
- Quantify the lifecycle impact of alternative designs
- Evaluate maintainability and supportability early
- Assess the consequences of different adoption timelines
Translate engineering choices into LCC, availability, and risk metrics. Most importantly, it allows teams to simulate differences between designs and methodologies before they are locked in when influence is highest and cost is lowest.
From Awareness to Action
Without quantitative insight, even well-founded proposals can stall due to uncertainty or competing priorities.
By explicitly modelling the cost of inaction, engineering strategy teams can:
- Build defensible, data-based business cases
- Clearly communicate long-term consequences to leadership
- Prioritize investments with measurable impact
- Reduce risk through scenario comparison
- Align engineering decisions with lifecycle objectives
Inaction becomes visible. Trade-offs become explicit. Decisions become intentional.
Conclusion: Inaction Is a Decision, Make It an Informed One
For modern aircraft manufacturers, engineering strategy organizations are catalysts for innovation. But innovation does not happen by intention alone.
Not influencing design early has a cost.
Not improving maintainability has a cost.
Not modernizing has a cost.
The difference between success and regret is often whether these costs are understood before decisions are made.
Data-driven lifecycle modelling does not force action, but it ensures that when teams choose to wait, they understand exactly what that choice will cost.
