{"id":74328,"date":"2026-08-24T16:29:36","date_gmt":"2026-08-24T19:29:36","guid":{"rendered":"https:\/\/actiosoftware.com\/?p=74328"},"modified":"2026-09-20T13:35:07","modified_gmt":"2026-09-20T16:35:07","slug":"quality-assurance","status":"publish","type":"post","link":"https:\/\/actiosoftware.com\/en\/blog\/quality-assurance\/","title":{"rendered":"Quality Assurance: How to Elevate Quality Management to a Strategic Level\u00a0"},"content":{"rendered":"

Your company probably already knows what quality is assurance<\/strong>. What is missing, in most cases, is not concept, but architecture. It is the bridge between what the quality team measures every day and what the executive committee decides every quarter. <\/p>\n\n\n\n

This bridge rarely exists spontaneously. It needs to be designed, with processes, indicators, and, above all, deliberate integration between quality and risk. <\/p>\n\n\n\n

 It is precisely this design \u2014 practical, replicable, and measurable \u2014 that this article presents. <\/p>\n\n\n\n

Quality and Quality Assurance: two concepts, one management system<\/strong>\u00a0<\/h2>\n\n\n\n

Quality and quality assurance are not synonyms, but they are not isolated compartments either. Quality is the outcome, while this discipline is the prevention system that increases the probability of this standard being achieved consistently, before the error reaches the customer. <\/p>\n\n\n\n

Quality assurance is the structured set of planned and systematic activities carried out throughout the entire cycle of a process, product, or service, with the objective of generating confidence that quality requirements will be met in a consistent and verifiable manner. <\/p>\n\n\n\n

This distinction becomes even clearer when confronted with a question that frequently appears in managers' searches: what is the difference between quality assurance and quality control?  <\/p>\n\n\n\n

In practical terms, quality assurance acts within the process: it defines standards, prevents failures, and structures governance prior to execution. <\/p>\n\n\n\n

Quality control, on the other hand, acts on the final product: it inspects, tests, and detects deviations after the work has been carried out. One is systemic prevention; the other is spot verification. <\/p>\n\n\n\n

Dimension<\/strong> <\/td>Quality Assurance (QA)<\/strong> <\/td>Quality Control (QC)<\/strong> <\/td><\/tr>
Focus <\/td>Process and prevention <\/td>Product and detection <\/td><\/tr>
Performance moment <\/td>Before and During Execution <\/td>After execution <\/td><\/tr>
Objective <\/td>Reduce the probability of failure <\/td>Identify past failures <\/td><\/tr>
Responsibility <\/td>The entire organization <\/td>Technical\/Operational Team <\/td><\/tr>
Nature <\/td>Proactive and systemic <\/td>Responsive and punctual <\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

This table summarizes why treating QA as synonymous with inspection is a costly strategic mistake: organizations that confuse the two concepts tend to invest their energy in the wrong part of the process, reacting to nonconformities instead of preventing them. <\/p>\n\n\n\n

How to Set Up a Quality Assurance Program in Five Steps<\/strong> <\/h2>\n\n\n\n

A mature quality assurance program does not arise from a single initiative. It is built in layers, with each layer addressing a specific limitation of the previous one.  <\/p>\n\n\n\n

Below is the sequence we observed working in medium and large companies<\/strong><\/a> with well-established governance structures. <\/p>\n\n\n\n

1. Diagnosis and mapping of critical processes<\/strong> <\/h3>\n\n\n\n

Before implementing any standardization, it is necessary to know where a failure is most likely to occur and what its impact would be.  <\/p>\n\n\n\n

This means mapping the processes of highest operational, financial, or regulatory criticality, prioritizing those where a quality failure quickly turns into business risk. <\/p>\n\n\n\n

This diagnosis must be linked to process architecture<\/strong><\/a> <\/strong>of the organization, rather than being treated as an isolated initiative of the quality department. <\/p>\n\n\n\n

2. Standardization of criteria and acceptance policies<\/strong> <\/h3>\n\n\n\n

Without objective criteria, quality assurance becomes just an opinion. This stage defines what is considered \u201ccompliant,\u201d using measurable, versioned, and auditable parameters, not only for physical products, but also for digital deliverables, services, and operational decisions. <\/p>\n\n\n\n

3. Automation and continuous testing<\/strong> <\/h3>\n\n\n\n

This is where digital quality assurance takes center stage. Isolated manual tests do not scale with the speed of modern operations, especially in environments with continuous software delivery, data integrations, and digital processes. <\/p>\n\n\n\n

Choosing the right quality assurance software is no longer a competitive advantage; it has become a basic operational requirement.  <\/p>\n\n\n\n

According to Gartner, the <\/strong>adoption of AI-powered testing tools<\/strong> <\/strong>It is expected to jump from about 20% of companies in early 2025 to 70% by 2028, as automation takes over previously manual tasks related to test generation, maintenance, and prioritization. <\/p>\n\n\n\n

McKinsey reached a similar conclusion when analyzing call centers: processes of quality assurance automated by generative AI<\/strong> <\/strong>achieved an accuracy of over 90% in the evaluation, compared to 70% to 80% obtained through manual evaluation. <\/p>\n\n\n\n

4. The Relationship Between Quality and Risk Management<\/strong> <\/h3>\n\n\n\n

This is the most frequently overlooked step\u2014and the one that generates the most business value. An unaddressed quality deviation is, by definition, an unmitigated risk. Addressing the two separately means duplicating monitoring efforts and losing visibility into the root causes of the problems. <\/p>\n\n\n\n

Mature companies link their quality assurance findings directly to corporate risk matrix<\/strong><\/a>, treating each recurring nonconformity as a risk event to be formally monitored. <\/p>\n\n\n\n

5. Executive governance and quality culture<\/strong> <\/h3>\n\n\n\n

No quality assurance process can succeed without the support of senior leadership. The Harvard Business Review documented, in a survey of more than 800 professionals from various industries, that about 60% of the respondents said they worked in environments without a consolidated quality culture<\/strong><\/a>. <\/p>\n\n\n\n

This data reinforces a central principle of strategic execution: quality indicators only influence decisions when they reach the leadership table with the same discipline as any other corporate KPI. <\/p>\n\n\n\n

The Cost of Not Structuring Quality Assurance<\/strong> <\/h2>\n\n\n\n

The numbers behind the absence of a formal quality assurance program rarely appear in isolation; they manifest as budget overruns, rework, and projects that fail to deliver the promised value. <\/p>\n\n\n\n

The PMI (Project Management Institute) shows, in its Pulse of the Profession 2025 report, that professionals with high maturity in Business intelligence solutions have failure rates up to 27% lower<\/strong><\/a> than their peers, in addition to better performance in meeting goals \u2014 direct evidence that structured prevention outperforms reactive correction. <\/p>\n\n\n\n

In the field of digital transformation, McKinsey has found that, although 89% of large global companies already have digital transformation and AI initiatives underway, on average they capture only 31% in expected revenue and 25% in projected cost savings<\/strong>.<\/strong> <\/p>\n\n\n\n

The difference between organizations that extract value and those that do not is rarely in the chosen technology, but in the discipline of execution, of which quality assurance is a structural part. <\/p>\n\n\n\n

Some of the most common hidden costs when quality assurance is not treated as a system: <\/p>\n\n\n\n