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Perspectives

Why Traditional Quality Assurance is Giving Way to QA-as-a-Service

2017-08-31


Under pressure to support digital business at scale, QA must embrace an on-demand approach to quality assurance, one that requires tight orchestration of people, process and technology.

Quality assurance — the crucial branch of software development that monitors engineering processes such as feature requirements, design, coding, hardware configuration, release management, and continual updates to ensure user satisfaction — is being upended as the world increasingly becomes more digital. Although software has always been digital, the way it’s made and assured is decidedly different today than it was just years ago.  

To better understand QA’s changing dynamics, we commissioned the Everest Group to survey 100 quality assurance leaders to better understand their QA attitudes and plans in today’s digital world. Our study found that:

  • 86% of large enterprises are expected to increase their QA budgets over time.

  • 77% of large enterprises are exploring investments in QA automation.

  • 84% cite the lack of digital or industry-specific QA talent as a challenge.

  • Only 2% mentioned cost reduction as the most important priority.

Why? Simply put, QA leaders are under pressure to support their organization's digital agenda and add business value beyond merely reducing costs. And as digital business reformation increasingly relies on platform technology as operational glue, QA practices must accordingly follow. 

New World Order

Digitization, technology proliferation, DevOps, and automation are fundamental forces that are reshaping the enterprise QA function. To successfully navigate these disruptive forces, the QA function must evolve its organizational, talent, metrics and consumption models.

Historically, the traditional enterprise QA function was characterized by scaled delivery models and a tightly bound technology stacks. While this was effective in the past, today’s QA value is more closely tied to speed-to-market and an ability to rapidly embrace new technologies such as robotic process automation and artificial intelligence (in the form of natural language processing through machine learning) as well as architectures such as microservices. 

Figure 1

As a result, the QA function has needed to evolve from one focused primarily on reducing the cost of moving software from testing into production to one that is increasingly critical to the acceleration of digital at scale across the enterprise. Supporting the digital QA agenda will therefore require significant investments to keep pace with rapid development cycles and the disruption of business as usual. By adopting quality as-a-service strategies, enterprises will be able to support more agile ways of embracing and deploying new technologies and ensuring returns from long-term QA investments.

Areas of Focus

With this as their marching orders, QA leaders are shifting their efforts to focus on the following four initiatives, according to our study: 

Technology.

The new QA model must be able to orchestrate an ecosystem of tools and technologies at speed.

People.

The talent model is built on the composite knowledge of digital technology, automation assets, and vertical business processes, and can be sourced from either internal or external expertise.

Process.

The new QA model is responsible for assuring outcomes against a digital business process.

As-a-service delivery.

The new QA model can be consumed in units that are more closely linked to business metrics than traditional measures such as headcount or lines of code.

To support these objectives, QA teams are evolving from a custodian of typical IT metrics such as code quality and uptime to that of focusing and supporting rapid adoption of new technologies and application improvements. 

Interestingly, traditional values such as operating model optimization, cost reduction, and globalization of talent force are now lower priorities, indicating that the QA industry is maturing to deliver revenue-enabling value themes. This is in stark contrast to the traditional cost arbitrage-based QA models that were built to contain expenses.

Moving Forward

Thanks to open source and SaaS models, modern QA is thankfully within reach. But putting these concepts to effective use in an enterprise context remains a challenge. What’s more, rapid technology adoption brings its own set of challenges. For instance, automation forces QA teams to increase their contextual understanding of business processes. Moreover, IT organization suffer from a shortage of QA as-a-service skills, according to those surveyed. 

To support the digital mandate, the QA function will need to orchestrate an ecosystem of technology, talent, and business process expertise in a rapid, agnostic and flexible structure. In order to deliver business value and incremental process improvements, enterprise QA must quickly innovate to keep up with ongoing technology disruption and ever-changing business models. This, in turn, requires enterprise QA to orchestrate across firewalled and open ecosystems spanning traditional tools’ vendors and a host of non-traditional industry stakeholders. By embracing a wider, faster, and on-demand QA ecosystem, however, enterprises will ultimately achieve shorter time-to-market and higher user satisfaction.

To learn more, please read “Quality Orchestration: QA in the Digital Era,”  visit our Quality Assurance Practice, or contact us

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Why Traditional Quality Assurance is Giving Way to QA-as-a-Service