by Sonia Vitolo, Project Consultant at Excellence Innovation
IT projects are developed in increasingly complex contexts, where the real challenge is not only technological integration, but the continuous alignment between business needs and system capabilities.
Complexity is not only technical: the critical point is translating business needs correctly into implementable specifications. When requirements are vague or incomplete, the outcome is predictable: different interpretations, rework, delays, and conflicts between functions.
Requirement quality therefore becomes a structural factor of the project, not a documentary detail. Defining requirements clearly, measurably, and verifiably means reducing ambiguity, making acceptance criteria objective, and creating a concrete link between strategic decision-making and technical delivery.
A requirement may concern application functionalities, operational processes, service levels, data quality, or integrations between systems. For it to be truly useful, it must be understandable, implementable, and verifiable without ambiguity. The SMART approach makes it possible to transform needs that are often informal or high-level into clear, measurable specifications oriented toward implementation.
The SMART acronym identifies five fundamental characteristics: a requirement must be Specific, therefore clear and unambiguous; Measurable, verifiable through objective metrics; Attainable, technically and organizationally sustainable; Relevant, consistent with business and operational objectives; and Time bounded, with deadlines or precise time references. In project contexts involving different functions—business, operations, and IT—these criteria reduce subjective interpretations and foster alignment among stakeholders.
Specificity is fundamental in highly complex contexts. Generic requirements such as “the system must be secure” or “the platform must be efficient” do not guide implementation. A well-formulated requirement defines scope, process, and expected outcome, distinguishing for example between data protection, transaction security, or access management. This precision reduces ambiguity and facilitates coordination among different functions.
Measurability makes it possible to evaluate system performance objectively. Indicators and thresholds—such as response times, availability levels, control accuracy, or processing times—make results verifiable and support control and continuous improvement.
The attainability criterion requires consistency with technological and organizational constraints.
In IT projects, innovation must be aligned with existing capabilities: a sustainable requirement balances evolution and stability, avoiding unrealistic goals that generate delays or operational risks.
Relevance ensures alignment with strategic priorities. Not all requirements produce the same value: some ensure service continuity, others optimize processes or improve the user experience. Explicitly linking requirements to objectives facilitates prioritization choices and resource allocation.
Finally, the time dimension links the requirement to planning. Associating deadlines, milestones, or reference periods makes it possible to monitor progress, coordinate activities, and prevent slippages throughout the project lifecycle.
The difference between a generic requirement and a SMART one emerges clearly in practice. Saying that “the system must be fast” is insufficient; defining instead that “the application must respond within 2 seconds in 95% of cases with 1,000 concurrent users by the next release” establishes clear and verifiable criteria. Similarly, the goal “improve the user experience” becomes operational if translated into “within 6 months, reduce by 30% the average time to complete a digital process, while keeping an abandonment rate below 10%”.
It is also important to distinguish between strategic objectives and operational requirements: the former define the direction, for example improving the user experience or increasing process efficiency, while SMART requirements translate those objectives into concrete specifications that systems and processes must meet. This distinction avoids inconsistent interpretations during implementation and reduces the risk of solutions that are not aligned with expectations.
CONCLUSIONS
In summary, applying SMART criteria in IT projects is not a formal writing exercise, but a governance choice. It means transforming objectives and expectations into clear, measurable, and verifiable elements, reducing ambiguity and making discussion among stakeholders more objective and results-oriented.
The SMART approach is not limited to functional requirements: it can be extended to milestones, releases, performance metrics, and program objectives. Defining targets with deadlines, indicators, and explicit acceptance criteria makes it possible to monitor progress transparently, anticipate risks, and support data-driven decisions.
Adopting it means introducing greater predictability, accountability, and control throughout the project lifecycle. In highly complex contexts, clarity is not an accessory element, but a strategic lever to ensure effective execution and consistency between vision and delivery.
