New System Requirements: The First Line of Defense
New System Requirements: The First Line of Defense
Introduction: Why Requirements Matter
Every system begins with functional intent. To begin with, that intent must be expressed in a proper description statement, communicated clearly, and preserved as design details evolve. Without this initial clarity, engineering teams risk building solutions without a shared understanding of purpose. In systems engineering, the vehicle for capturing and communicating intent is the Requirement. A requirement is more than a line in a document. Rather, it is a disciplined statement that expresses what the system must achieve, under what conditions, and with what measurable outcomes. In this sense, requirements are proactive: they give structure to intent, transform vision into guidance, and align stakeholders on the essentials before design begins.
At the same time, requirements also serve a protective role. When phrased with clarity and precision, they prevent ambiguity, redundancy, and contradiction from creeping into the system. For example, “system shall respond in less than 200 ms” sets a measurable boundary; “system shall respond quickly” invites misinterpretation. Strong requirements reduce the risk of divergence and, as a result, keep complexity from entering unnoticed.
In the automotive domain, this dual role is especially vital. Thousands of parts and millions of lines of software must integrate across suppliers, functions, and regulatory frameworks. Consequently, a single vague or conflicting requirement can ripple into rework, delays, or safety risks that multiply as the program matures. Clear requirements stop those errors at the source.
Thus, requirements are both the expression of functional intent and the first line of defense against uncontrolled complexity. Ultimately, they form the foundation on which later disciplines—Complexity Reduction and Optimization—can succeed.
Requirements as a Concept
At its core, a requirement is the structured expression of intent. It captures what the system must accomplish, under what conditions, and with what constraints. As a result, requirements transform broad goals into actionable guidance. They provide a bridge between functional intent and design, ensuring that every engineering activity traces back to a clearly defined purpose.
Philosophically, requirements differ from specifications. A specification describes how something should be implemented; a requirement defines what must be achieved. For example, “vehicle must stop within 40 meters at 100 km/h” is a requirement. “Use four-piston calipers with 320 mm discs” is a specification. Confusing the two is common. However, when design details are embedded in requirements too early, flexibility disappears and unnecessary complexity becomes locked in.
Requirements also act as a discipline of communication. They align stakeholders—engineering teams, suppliers, regulators, and customers—on shared expectations. Without this common language, misunderstandings multiply. An imprecise phrase in one document can ripple into months of redesign, whereas a clear requirement prevents the issue at its source.
In addition, requirements carry a protective function. They guard against uncontrolled growth by setting measurable boundaries. Ambiguity opens the door to unnecessary features, hidden assumptions, and divergent interpretations. By contrast, precision closes that door. In this way, requirements are not passive paperwork; they are active tools of control.
Seen as a concept, requirements are both proactive and protective. They give shape to functional intent and provide the first safeguard against complexity. Ultimately, this dual nature makes them indispensable in systems engineering.
The Role of Requirements in Containing Complexity
Complexity often enters systems at the very beginning—not through design flaws, but through poorly defined requirements. Ambiguity, contradiction, or overreach at this stage creates ripples that spread into architecture, integration, and validation. Once embedded, these flaws are expensive to detect and even harder to remove.
To begin with, ambiguity invites divergence. If one team interprets “fast response” as 500 milliseconds and another interprets it as 50 milliseconds, both may proceed confidently. Yet when their outputs meet, incompatibility appears. A single vague word creates rework that measurable language could have prevented.
In addition, overlapping requirements multiply interfaces. When multiple teams generate similar but uncoordinated requirements, functions may overlap. For example, an ADAS camera requirement may specify data rates, while a display requirement specifies refresh intervals. If the two do not align, additional conversion layers or redundant logic appear. Each extra interface introduces propagation risk.
Moreover, over-specified requirements lock in unnecessary complexity. When a requirement dictates design details rather than intent—“must use four-piston calipers”—it eliminates flexibility. Future opportunities to simplify or optimize vanish, because the complexity has been codified as a rule.
Finally, missing requirements leave gaps. Without explicit statements, assumptions fill the void. Teams often design for their own interpretation, and those interpretations diverge. When integration reveals the mismatch, the cost of correction can be ten times higher than if the gap had been addressed early.
Therefore, clear and precise requirements contain complexity at its source. They prevent it from taking root in design and spreading unchecked. By enforcing alignment, they keep systems stable before growth makes errors irreversible.
Types of Requirements
Requirements do not emerge from a single place. Instead, they flow from different sources, and each source shapes the nature of the requirement. By classifying them this way, engineers can better understand authority, flexibility, and the potential for complexity.
To start, engineering design–born requirements capture intent directly from the design process. Functional requirements define what the system must do. Example: “The braking system shall stop the vehicle within 40 meters at 100 km/h.” Performance requirements specify how well it must do it. Example: “The infotainment system shall boot in less than three seconds.” These originate within engineering teams and evolve as designs mature.
Next, government and regulatory requirements set the boundaries of safety and compliance. They ensure the system does not cause harm and meets legal standards. Example: “Airbags must deploy within 30 ms of a crash event.” These requirements are mandatory and typically non-negotiable, making them some of the most influential drivers of system design.
In addition, assembly and interaction requirements describe how subsystems connect. For instance: “The ECU shall communicate with the powertrain controller at 500 kbps over CAN.” Because interfaces multiply so rapidly, clarity here prevents propagation more effectively than almost any other category.
Finally, customer and perception-driven requirements reflect user expectations. Quality and reliability requirements define defect tolerance and lifetime. Example: “The ECU shall operate for 10,000 hours without failure.” Customer-driven requirements capture usability and experience. Example: “Navigation shall reroute within five seconds after a missed turn.” These requirements often come from market research or field feedback.
Therefore, by tracing requirements back to their sources, engineers can prioritize which are negotiable, which are mandatory, and which demand the most vigilance to prevent unnecessary complexity.
Common Failures in Requirements
Requirements fail in predictable ways, and the failure often reflects their source. By recognizing where each type originates, engineers can anticipate the risks and prevent complexity from creeping in unnoticed.
To begin with, engineering design–born requirements often fail through ambiguity or over-specification. A vague statement like “system shall respond quickly” leaves room for multiple interpretations. One team may target 500 ms, another 50 ms. Misalignment appears later at integration. In addition, over-specification locks in design choices—“must use four-piston calipers”—that restrict future flexibility and add unnecessary complexity. Missing boundary conditions create similar problems by leaving engineers to fill gaps with assumptions.
Furthermore, government and regulatory requirements typically fail because of timing. Regulations may change late in development, forcing costly redesigns. Over-interpretation also appears: teams sometimes add layers of constraint beyond what the law requires, creating more work without real compliance benefit.
Similarly, assembly and interaction requirements are frequent sources of contradiction. One subsystem may specify a CAN bus speed of 250 kbps, another 500 kbps. Without coordination, integration fails. Ownership issues also emerge when multiple teams define overlapping requirements for the same interface, multiplying dependencies instead of clarifying them.
Finally, customer and perception-driven requirements fail due to unclear or conflicting expectations. Phrases such as “reliable system” or “high quality” lack measurable criteria, leaving validation teams unable to prove compliance. In global markets, different customer groups may value speed, durability, or cost differently—creating requirements that pull in opposing directions.
Therefore, by tracing failures to their sources, organizations see not just the symptom but the root cause. Strong requirements discipline begins with understanding where each requirement comes from and where it is most likely to falter.
Best Practices for Strong Requirements (by Source)
Strong requirements do not appear by chance. They require discipline, review, and tools tailored to their source. By applying best practices at the point of origin, engineers reduce ambiguity, prevent contradictions, and contain complexity before it grows.
Engineering design–born requirements. The key here is clarity and validation. Every requirement must be measurable: “<200 ms response” is testable, “respond quickly” is not. Simulation and modeling validate feasibility before hardware exists, ensuring requirements reflect achievable targets. Peer reviews further expose hidden assumptions or over-specification.
Government and regulatory requirements. Early involvement of compliance experts prevents surprises. Teams must trace each requirement directly to a legal clause or standard, avoiding over-interpretation. Strong traceability also protects the program if regulators issue late changes: engineers can quickly identify affected items and update only what is necessary.
Assembly and interaction requirements. Interfaces demand standards and coordination. Using shared libraries, common protocols, and agreed data definitions reduces contradictions. Cross-functional reviews bring together teams that own different interfaces, ensuring consistency before integration. Simulation adds another layer of protection, testing interface behavior virtually before connectors or code exist.
Customer and perception-driven requirements. Translation is critical. Abstract expectations like “high quality” must be converted into measurable criteria: “99.9% uptime,” or “navigation reroute in <5 seconds.” Structured market research and voice-of-customer tools provide the data for this translation, while field feedback refines requirements across model years.
Best practices are not optional extras—they are the foundation of disciplined engineering. By tailoring practices to the source, organizations ensure requirements remain both a true expression of functional intent and a strong defense against uncontrolled complexity. This way, failures and best practices map directly back to the origin of the requirement, helping teams see where vigilance matters most.
Automotive Examples
Automotive programs provide clear examples of how requirements from different sources shape systems—and how mistakes at this stage can ripple downstream.
Engineering design–born requirements. Functional and performance requirements drive vehicle capability. For example, an EV braking system may require “stopping from 100 km/h in under 40 meters.” A performance layer adds “brake fade shall remain under 10% after 20 consecutive stops.” If either is vague, testing expands unnecessarily, and complexity grows in validation.
Government and regulatory requirements. Safety laws define mandatory boundaries. Airbags must deploy within strict time windows, and EV batteries must meet thermal runaway standards. When requirements are misinterpreted—such as adding redundant tests not specified in the regulation—program costs rise without improving safety.
Assembly and interaction requirements. Interfaces dominate E/E architecture. A CAN bus running at 500 kbps in one ECU and 250 kbps in another forces redesign late in development. Similarly, mismatched connector pinouts between suppliers can halt integration. Clear, standardized interface requirements prevent these propagation cascades.
Customer and perception-driven requirements. Market expectations often focus on usability. “Infotainment shall boot in less than three seconds” is a requirement born from customer demand. If the requirement were left as “system shall boot quickly,” validation teams would face conflicting interpretations across regions.
Each example shows the same principle: clarity at the requirement stage prevents complexity from multiplying later. By recognizing the source—engineering, government, assembly, or customer—teams can apply the right discipline early and keep systems aligned.
Organizational Discipline
Even strong individual requirements cannot stand alone. Large programs contain thousands of them, flowing from multiple sources and evolving over years. Without organizational discipline, requirements fragment, lose traceability, and generate uncontrolled complexity.
Requirements management tools. Platforms such as IBM DOORS or Jama provide centralized control. They maintain traceability from requirement to test case to validation report. With proper use, every requirement has an owner, a history, and a measurable status.
Ownership and accountability. A requirement without an owner quickly drifts. Clear assignment—whether to a system engineer, a supplier, or a compliance lead—ensures each requirement remains current and relevant. Ownership also prevents duplication, since engineers know who to consult before adding new requirements.
Cross-functional reviews. No requirement exists in isolation. Safety, manufacturing, and service all depend on clarity. Regular cross-functional reviews expose gaps and contradictions before they propagate. For example, a manufacturability review may flag a tolerance requirement that is technically possible but impossible to achieve in volume production.
Change management. Requirements evolve as regulations shift, customer expectations change, or new technologies emerge. Formal impact analysis ensures updates ripple in a controlled manner rather than spreading chaos. Linking changes to engineering development projects keeps revisions deliberate, not accidental.
Lessons learned. Capturing failures and successes from past programs prevents repetition. Requirements that caused complexity once can be rephrased or standardized in future projects.
Organizational discipline turns requirements into more than a collection of statements. It makes them a living system of commitments—traceable, owned, and aligned across the program.
Conclusion: The First Line of Defense
Every engineering program begins with functional intent, and requirements are how that intent takes form. They are not paperwork; they are structured commitments that guide design, align stakeholders, and establish measurable outcomes. When handled with discipline, requirements serve as both a proactive expression of purpose and a protective barrier against uncontrolled complexity.
The sources of requirements—engineering, government, assembly, and customer—each bring their own risks. Ambiguity, contradiction, or overreach at this stage multiplies as the program matures. By classifying requirements by source, engineers can anticipate where failures are most likely and apply tailored best practices. Clear language, strong traceability, simulation, and peer reviews prevent problems before they spread.
Automotive examples demonstrate how fragile this stage can be. A vague boot-time requirement, a misinterpreted regulation, or a mismatched interface speed can force rework that costs months and millions. Yet the opposite is also true: clear, precise requirements stabilize programs, reduce validation burdens, and make later efforts in Complexity Reduction and Optimization possible.
Organizational discipline provides the structure to keep requirements alive. Tools, ownership, cross-functional reviews, and change management ensure that thousands of commitments remain traceable and actionable. Without this structure, even strong requirements lose force.
Ultimately, requirements are the first line of defense. They capture functional intent with clarity and guard against complexity before it takes root. The next article turns to Change Management and Impact Analysis, examining how disciplined processes keep evolving requirements from destabilizing entire 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 Complexity in Systems Engineering Series:
- What Do We Mean by Complexity?
- The Growth of Complexity
- Counting Complexity – Why Interfaces Grow Faster Than Parts
- Propagation: How Complexity Spreads
- Complexity Reduction: The Discipline of Simplification
- Optimization: Improving the Existing System
- Requirements: The First Line of Defense <—You are here
- Measuring and Managing Complexity
- From ppm to ppb – The Statistical Reality of Vehicle Defects
- Complexity in Practice: Case Studies & Critiques
Simulation and Virtual Models – Managing Complexity in Verification and Validation
Systems Engineering References
About George D. Allen Consulting:
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