New Systems Engineering: Avoiding the Illusion of Readiness
New Systems Engineering: Avoiding the Illusion of Readiness
Introduction to Requirements Cascades
Generally, in Systems Engineering for complex system development, the most dangerous problems are often the ones that remain hidden until late in the process. Moreover, one of the most persistent is the illusion of readiness — the belief that a system is on track simply because schedules are being met or documents look complete. In reality, hidden gaps in requirements, unclear definitions, and unverified interfaces can derail even the most well-resourced programs. Hence, this article examines how the V-Model, when applied with rigor, exposes these gaps early and ensures that every commitment made in development is later proven in validation.
About This Series:
Sequentially, this article is the second in a continuous education series that simplifies the complexity of the V-Model in systems engineering. It builds on the foundation from Part 1, connecting practical engineering methods with Objectivist philosophy to show how precise definitions and disciplined verification turn the V-Model into a working strategy, not just a diagram. Together, these insights help align requirements, design, and proof across every stage of complex system development.
What Is a Requirement Cascade?
Consequently, in Systems Engineering, a requirement cascade is the structured flow of requirements from the highest-level objectives down to the smallest component specifications. At the top, vehicle-level requirements capture the full intent: safety, performance, regulatory compliance, and user experience. Therefore, these then break down into system-level requirements, followed by subsystem and component requirements.
Furthermore, each level inherits constraints from above while adding the detail needed for its scope. Moreover, this cascade ensures traceability — every line item in a component’s specification links back to a higher-level objective.
Additionally, the growing complexity of modern vehicle assemblies and their functions makes this discipline essential. Without it, teams can misinterpret, lose, or redefine requirements in isolation. This is why Systems Engineering exists: to bring clarity to complexity and ensure that every part of the product aligns with the whole.
Hence, to develop meaningful requirements, first define the function. Once defined, teams can test it conceptually before design begins. In practice, definitions often differ between OEMs — and even within departments — as well as between OEMs and Tier I suppliers. Early, documented agreement on these definitions is critical. Corporate practices of carry-over and reuse also require scrutiny, as a design proven in one program may fail to meet the intent, performance targets, or integration conditions of a new application.
The Illusion of Readiness — Common Traps
Overall, when upstream requirements remain unclear or incomplete, teams may believe they are ready to proceed — but they are not. Moreover, this false readiness often emerges when documents appear complete, schedules move forward, and milestone reviews pass without deep scrutiny.
Initially, in the early stages of the Statement of Requirements (SOR) process, requirements typically fall into three categories:
Given — carried from existing standards or regulations.
Known — understood from experience or prior designs.
Unknown — developed through supplier collaboration.
Therefore, each carries risk. Outdated given requirements may no longer apply. Incidentally, known requirements can be assumed without proof. Unknown requirements left unresolved too long stall integration and force late-stage rework. Additionally, risks grow when placeholders (“TBD”) linger into mid- or late development, silently eroding readiness.
Common traps include:
Reusing old requirement sets without verification. Carry-over and reuse may save time, but must be validated against the new assembly’s intent, performance, and integration needs.
Leaving placeholders in critical requirements. Each TBD is a missing commitment; too many push design into reactive mode.
Treating government standards as requirements. Regulations must be translated into explicit, testable engineering requirements that fit the system architecture. Skipping this step almost always leads to compliance gaps and performance issues.
The Illusion of Readiness — High-Risk Shortcuts
Once a program appears to move smoothly, teams may feel pressure to accelerate progress by cutting corners. In Systems Engineering, these shortcuts often undermine the very commitments the V-Model is meant to protect. They can mask incomplete work until integration — when fixing the problem becomes most expensive and disruptive.
High-risk shortcuts include:
Defining interfaces late or superficially. Interfaces — the mechanical, electrical, and logical connections between subsystems — must be defined early and verified against the evolving design. Teams can confirm mechanical and electrical fits more easily; logical interfaces, such as signal compatibility and timing, are far more complex. Left vague, they can trigger late-stage mismatches requiring redesign or software rework.
Skipping requirement translation from regulations. Government regulations may drive features, but their language is not an engineering requirement. Each statement must be converted into measurable, testable criteria aligned with system architecture and performance targets. Skipping this step invites compliance gaps and validation uncertainty.
Assuming subsystem readiness without integration evidence. A subsystem may meet its own specifications, yet still fail in the full vehicle. Without staged integration checks, timing, data formats, or load conditions may fail in ways not visible at the subsystem level.
In practice, these shortcuts trade small, early investments for large, late costs — a gamble complex vehicle programs cannot afford.
An Objectivist Perspective: Metaphysics and Clarity in Systems Engineering
In Objectivist philosophy, metaphysics is the study of reality — identifying what exists and the nature of its existence. Therefore, applied to Systems Engineering, metaphysics means defining exactly what the system is before attempting to build or verify it. Moreover, without that clarity, requirements become guesses, and validation turns into an exercise in chance.
From this perspective, the left side of the V-Model is an act of recognition, not invention. Furthermore, we are not arbitrarily deciding what the system should be; instead, we are discovering and describing it in terms precise enough to be built. This process demands definitions rooted in observable facts, measurable performance, and verifiable interfaces — never vague aspirations or untested assumptions.
Clarity at this stage is more than operational efficiency — it is an ethical obligation. In the Objectivist view, proceeding without understanding “what it is” means evading reality. In engineering, that evasion manifests as defects, recalls, and loss of trust.
Metaphysics also reinforces that complexity does not excuse ambiguity. As vehicle systems grow more integrated and functions span multiple domains (mechanical, electrical, and logical), the temptation to leave gaps for later increases. The Objectivist answer is the opposite: fill those gaps now, in definition, so the right side of the V-Model has a concrete target to verify.
In short, metaphysical clarity forms the foundation for everything that follows in the V-Model. Without it, even the most rigorous verification and validation plans build unstable ground beneath them.
An Objectivist Perspective: Epistemology and Proof in Systems Engineering
In Objectivist philosophy, epistemology is the study of knowledge — how we know what we know, and how we validate that knowledge. Hence, in Systems Engineering, epistemology translates into one guiding question: How do we know this will work?
Applied well, epistemology prevents one of the most common failures in complex engineering: assuming something will work because it has always worked before or because it worked in a different context. Newly developed functions within the supply chain may fail to deliver the same performance once integrated into the total vehicle assembly. A proven design from the past can still fail if it is not re-verified against the new system’s intent, performance targets, and integration conditions.
This mindset demands more than running standard tests. It requires deliberate verification and validation at every level of the requirement cascade — from components to subsystems to the full vehicle. Each test must map back to the original intent, proving not only that the part functions in isolation, but also that it works as intended within the complete system.
By embedding epistemological discipline into development, teams replace assumption with evidence. They create a chain of proof linking every design decision to objective validation, reducing late-stage surprises and ensuring delivered performance matches the promise defined at the start.
Automotive Example: A Safety Feature Gone Wrong
Several years ago, a vehicle program introduced an advanced occupant sensing system to improve airbag deployment decisions. On paper, the system requirements appeared complete. Overall, the Statement of Requirements listed all major functions, with only a few placeholders marked “TBD.” Internal teams assumed those open items would be resolved once the Tier I supplier finalized the design.
However, one “TBD” requirement defined a critical logical interface between the occupant sensing ECU and the crash management system. Consequently, the OEM assumed the supplier would design it to match the rest of the vehicle architecture. Then, the supplier assumed the OEM would provide the exact timing and data format. Neither side verified the interface early in development.
By the time full-vehicle integration began, the mismatch delayed airbag trigger decisions during specific crash modes. Although the team eventually corrected the issue through a late-stage engineering change, it required emergency validation, cost overruns, and a six-week launch delay.
From a V-Model perspective, this failure traces directly to weak metaphysical clarity and a lack of epistemological rigor:
Metaphysics — “What is it?”
In Systems Engineering, metaphysics is an applied, stepwise process that produces the functional design definition: what the function is, what it must do, the operating conditions and constraints, and the success criteria. The output is a coherent functional design proposal that flows directly into requirements and architecture.Epistemology — “How do we know?”
In Systems Engineering, epistemology is a disciplined, systematic process for generating objective evidence that the design will work as intended in the full vehicle context. It relies on tools such as DFMEA, PFMEA, digital-twin simulation (MiL/SiL/HiL), formal ICDs, and DVP&Rs.
Closing Thought: Development of Requirements in Systems Engineering
In conclusion, the V-Model is more than a process diagram — it is a discipline of commitments that begins with developing clear, testable requirements and ends with proving that every one of them is met. Applied metaphysics in this context is the structured process of defining what the function is — its scope, constraints, and success criteria — so those definitions flow into well-formed requirements. Applied epistemology is the disciplined, systematic use of engineering tools such as DFMEA, PFMEA, digital-twin simulations, formal ICDs, and DVP&Rs to build objective evidence that teams meet those requirements in the intended environment.
When applied with rigor, the V-Model closes the loop between definition and proof, ensuring that teams not only write requirements but also validate them in practice. Without this discipline, even experienced teams can fall into the illusion of readiness, where schedules advance while critical unknowns remain unresolved.
In the automotive industry, the cost of that illusion is measured not just in program delays or budget overruns, but in safety risks, regulatory failures, and erosion of trust. The occupant sensing system example shows that a single undefined requirement or unverified interface can be the weakest link in an otherwise strong program — and that these failures are entirely preventable when requirement development follows the full intent of the V-Model.
Coming Up
Part 3 will explore how the V-Model drives proactive alignment between OEMs, Tier I suppliers, and the broader supply chain, ensuring that commitments defined on the left side are fully proven through verification and validation on the right. By securing that alignment early, and grounding it in the Objectivist principles of clarity and accountability, engineering teams can turn the V-Model from a static diagram into a living strategy for delivering safe, reliable, and fully validated systems.
References
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INCOSE Systems Engineering Handbook – Overview of systems engineering principles, including V-Model context
www.incose.org/products-and-publications/se-handbook -
ISO/IEC/IEEE 15288: System Life Cycle Processes – International standard defining system development and verification processes
www.iso.org/standard/63711.html - 3. ISO 26262: Road Vehicles – Functional Safety – Automotive functional safety standard where the V-Model is often applied
www.iso.org/standard/43464.html
References to Systems Engineering Series:
- What V-Model Really Means in Automotive Systems Engineering: https://georgedallen.com/what-v-model-really-means-in-automotive-systems-engineering/
- Requirement Cascades and the Illusion of Readiness: https://georgedallen.com/new-systems-engineering-avoiding-the-illusion-of-readiness/ <—You are here
- Bridging the Center – Integration as Reality Check: https://georgedallen.com/new-systems-engineering-v-model-supply-chain-alignment/
- Why the Right Side Fails – Verification Isn’t Testing: https://georgedallen.com/new-systems-engineering-v-model-risk-management/
- The Loop Within the V – Feedback and Continuous Learning: https://georgedallen.com/new-systems-engineering-the-loop-within-the-v-lifecycle-assurance/
- V-Model in the Real World – Politics, Timelines, and Design Drift: https://georgedallen.com/new-systems-engineering-v-model-in-the-real-world/
Systems Engineering References
About George D. Allen Consulting:
George D. Allen Consulting is a pioneering force in driving engineering excellence and innovation within the automotive industry. Led by George D. Allen, a seasoned engineering specialist with an illustrious background in occupant safety and systems development, the company is committed to revolutionizing engineering practices for businesses on the cusp of automotive technology. With a proven track record, tailored solutions, and an unwavering commitment to staying ahead of industry trends, George D. Allen Consulting partners with organizations to create a safer, smarter, and more innovative future. For more information, visit www.GeorgeDAllen.com.
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