The audit is moving along smoothly. Procedures are available, records are organized, and questions are answered without hesitation. Then the conversation turns to software. An auditor pauses at a report on the screen and asks, “Can you walk me through how this software was validated?”

The question is not confrontational, and it is rarely asked with suspicion. Yet it often creates an immediate moment of uncertainty. The software may be a spreadsheet used to calculate product expiration dates on labels, a reporting function within a validated system, or a simple tool that has been in place for years. The data are trusted, and the decisions are sound, but explaining why the software can be trusted becomes unexpectedly difficult. In some cases, the organization realizes that the software was never formally validated or that the original rationale was never documented.

In many organizations, software validation exists in practice but not in a way that is easy to explain or defend. Risk decisions were made implicitly rather than explicitly, and documentation does not always tell a clear story. These decisions may have been discussed and agreed upon years earlier, but the rationale was never formally recorded. As a result, a routine audit question can quickly become a stressful discussion, even when no meaningful compliance gap exists.

This moment reflects a broader challenge. Software validation often breaks down not because organizations are careless, but because expectations, risk, and real-world use are misaligned. Understanding how these misalignments develop helps explain why software validation continues to be one of the most persistent sources of audit findings and confusion.

Why Software Validation Continues to Be a Persistent Pain Point

The way software is used within quality systems has changed significantly over time. Today, organizations rely on a wide range of tools to collect data, analyze trends, generate reports, and support quality decisions. Many of these tools were introduced gradually to meet operational needs rather than as part of a coordinated validation strategy.

At the same time, validation practices are often based on legacy approaches developed for large, standalone software systems. When those same expectations are applied to smaller, lower-risk tools, organizations struggle to scale their efforts appropriately. The result is often an approach that is either too informal to defend or so complex that it becomes difficult to sustain.

Familiarity with commonly used tools can further complicate the issue. While software may perform reliably, confidence is sometimes assumed rather than demonstrated. Validation activities may exist, but the supporting evidence is fragmented across procedures, test records, and informal files. In some cases, organizations rely on vendor statements that software has been “validated,” only to discover that internal validation activities were deferred, deprioritized, or never completed. Without a clear narrative linking intended use, risk, and verification, organizations can struggle to explain their approach under audit conditions.

What Actually Requires Software Validation—and What Doesn’t

With this context in mind, the next step is to clarify what actually requires validation. This distinction is where many organizations either create unnecessary work or leave themselves exposed during an audit.

Software validation is not determined by the type or complexity of the tool. It is driven by how the software is used. Validation is required when software supports quality or regulatory decisions, or when it has the potential to impact product quality, patient safety, or compliance. This principle applies equally to commercial applications, internally developed tools, and simple utilities.

In practice, many commonly used tools fall into a gray area. Spreadsheets used to trend complaint data, reports generated from validated systems, calibration databases, or scripts that process test results may require validation if their output influences decisions or records. In contrast, software used solely for administrative or logistical purposes typically does not require validation because it does not affect quality outcomes. Clearly identifying and documenting these distinctions can simplify validation planning and explicitly define out-of-scope systems.

Clarity improves significantly when intended use is explicitly defined. A concise statement describing what the software does, how it is used, and which decisions depend on it provides a strong foundation for validation. Once that boundary is established, the next question becomes how much validation is appropriate.

Scaling Software Validation Using Risk

After determining that software requires validation, the focus shifts to scaling the effort based on risk. This is where validation moves from theory into execution.

Risk in software validation is driven by intended use and potential impact, not by sophistication. The key question is what could happen if the software does not perform as expected. When failure could affect product quality, patient safety, or regulatory compliance, the validation effort should increase accordingly.

A practical way to assess risk is to consider three factors: impact, likelihood, and detectability. Together, these elements support categorizing software as low, medium, or high risk and provide a rational basis for scaling validation activities.

For low-risk software, validation may consist of defining intended use and performing basic functional checks. Medium-risk software typically warrants clearer requirements, targeted testing, and evidence of change awareness. High-risk software, particularly tools that influence product release or patient-related decisions, may require formal protocols, comprehensive testing, and tighter change controls.

Scaling validation does not mean reducing expectations. Every validated tool requires objective evidence that it performs as intended. The difference lies in the depth and formality of that evidence.

Table 1: Scaling Software Validation Based on Risk

What Auditors Actually Look For

Once validation effort has been scaled based on risk, auditors focus on whether the evidence aligns with that approach. They are not typically looking for exhaustive documentation, but for coherent, risk-aligned evidence.

Auditors expect to see a clear definition of intended use, objective evidence that the software performs as intended, and awareness of change. The connection between intended use and verification is more important than the volume of documentation.

Change awareness is a frequent area of focus. Software evolves, whether through version updates, configuration changes, or spreadsheet modifications. Auditors want to see that changes are recognized and assessed in a manner consistent with the tool’s risk level.

Clear, concise evidence that follows logically from risk-based decisions is typically more defensible than extensive documentation that does not reflect how the software is actually used.

Common Gaps That Trigger Audit Findings

Audit findings related to software validation are rarely caused by a complete lack of activity. More often, the issue is that validation decisions and evidence are not clearly connected.

Common gaps include undocumented risk assumptions, testing that is not clearly linked to intended use, and changes that occur without impact assessment. Reliance on historical use or system reputation without objective evidence can also make otherwise reliable software difficult to defend.

Having a documented Master Validation Plan that shows all software has been evaluated and categorized by risk can quickly bring many audit questions to closure.

Another common finding involves failure to maintain validation when changes occur. Changes may be minor in nature, but without evaluation or documentation, earlier validation may no longer be defensible. Even when software developers perform validation activities, organizations are still responsible for evaluating whether changes affect their specific configuration and intended use. Verifying these activities helps ensure data integrity is maintained and reduces the likelihood of audit findings.

Overkill Traps That Create More Risk Than They Remove

Excessive validation effort presents a different challenge. Applying uniform rigor to all software, regardless of risk, can obscure intent and make validation difficult to maintain.

Template-driven validation that does not reflect actual use, or documentation that exceeds practical need, can weaken audit discussions rather than strengthen them. A risk-based approach helps avoid these traps by aligning validation effort with actual impact.

Building a Defensible and Sustainable Approach

A sustainable approach to software validation is built on consistency, clarity, and understanding. Organizations that standardize how they define intended use, assess risk, and scale validation effort are better positioned to explain and defend their approach.

When validation decisions are revisited deliberately as software changes, audits become confirmations of control rather than tests of memory. In that context, validation shifts from a recurring source of stress to a routine part of a mature quality system.

Closing

Software validation does not have to be a source of confusion or unnecessary burden. When validation decisions are grounded in intended use, scaled by risk, and supported by clear, objective evidence, they become easier to explain, maintain, and defend. Approached this way, software validation becomes a practical tool for supporting reliable decisions and sustained compliance.

Note: The author will be leading a one-day course on practical, risk-based software validation at the ASQ Audit Division Conference in Chicago, where these concepts will be explored in greater depth through real-world examples and hands-on exercises.