The report Sogeti World Quality Report 2021-22 reveals notable advances in terms of key trends both in QA, that is, in software quality, and also in the field of testing, which reveal the change in perception of both in all areas, and their passage from a secondary position in companies to a first level. About all this, as well as the weight of new technologies such as Artificial Intelligence and machine learning in the quality of the software, we have spoken with Jose Luis Antón, Head of Sogeti Spain.
[MCPRO] Software quality (QA) has gone in a fairly short time from having a relative visibility and importance in companies to occupying a first level position, especially in the face of their digital transformation. What has motivated this field and what consequences and advantages has it brought?
[Jose Luis Antón] Organizations have made a significant shift on the importance of ensuring software quality and are increasingly aware of its importance. In addition, the implementation of Quality Engineering activities With a comprehensive vision of quality is key to improving the customer experience, improving security, application performance, etc. It is, in short, accompany digitization with quality guarantees.
Precisely, our latest World Quality Report 2021-2022 provides strong figures on the importance of quality engineering in organizations as a priority business strategy to move towards digitization, ensuring a quality experience for customers and customer users without fissures. .
[MCPRO] What role do Artificial Intelligence and Machine Learning have in ensuring the quality of the software?
[Jose Luis Antón] As it progressed, according to this latest study that we have published from Sogeti together with Capgemini and Micro Focus, the World Quality Report 2021-22 (WQR 21-22) there is a growing desire among organizations to put Artificial Intelligence (AI) and Machine Learning (ML) techniques to good use as a mechanism for transparency, anticipation, aid in decision-making and automation in the Quality Engineering activities.
The report reveals that almost half of the respondents (48%) consider that they have data about the tests that could be used by AI and ML solutions, while 42% affirm that organizations trust the intelligence provided by these solutions and 46% that their organization is willing to act on the information provided by AI / ML based assistance. Just as AI in other areas can be seen as something futuristic, the World Quality Report encourages to stop talking about AI and start applying it.
In fact, test automation and management tools are incorporating capabilities based on AI and ML, and at Sogeti, for example, we also have a significant focus on solutions to make smart decisions in the field of software quality. Despite this, we are aware that artificial intelligence in quality engineering has not yet reached an optimal degree of application.
The report also finds that test design and strategy competencies are increasingly needed, combined with AI and analytical capabilities, indicating that organizations are beginning to envision key profile changes to bring out the maximum use of data and AI in quality assurance, as well as to face the challenges posed by their use.
[MCPRO] What effects has the popularization of the use of Agile and DevOps methodologies in software quality testing had on QA and testing?
[Jose Luis Antón] The adoption of Agile and DevOps approaches with continuous quality activities is a growing and continuous trend in companies, even with different levels of maturity and rates of progress. In this sense, the World Quality Report reports improvements in the productivity-quality-cost triangle. For this, according to data from the same report, it is necessary in Agile / DevOps to focus on quality by promoting shift-left (testing throughout the process and as soon as possible), the automation of tests, the integration of quality activities in CI / CD pipelines in the form of Quality Gates, and above all provide continuous feedback on quality through automated dashboards.
Linked to these needs, there is also a clear need for adequate profiles to promote this advance towards Agile / DevOps with a vision of continuous quality. That is why at Sogeti we are committed to the evolution of professionals, the dissemination and transfer of knowledge. Quality Engineering is the answer to implement continuous quality vision in Agile / DevOps environments.
We have various initiatives underway to precisely promote the evolution of professional profiles in this direction: our TechCamp Sogeti Spain, a complete training and practical program for new talents passionate about technology; through what was the first postgraduate degree in Quality Assurance in Spain; several hackathons that we have carried out combining our points in common with young talents who are passionate about technology and eSports, introducing another of Sogeti’s values into the equation, such as Fun; ; or our SogetiLabs, to promote innovation and new solutions adapted to DevOps environments.
[MCPRO] What are the main obstacles faced by the departments that are in charge of everything related to the quality assurance of software in companies?
[Jose Luis Antón] Expectations with the introduction of QA activities in organizations are increasingly pragmatic and realistic: quality as a whole and in its different perspectives is valued more than ever in the context of post-pandemic digitization, but at the same time it is needed seek the balance between investment in quality and the risks of non-quality.
On the other hand, another challenge arising from the World Quality Report is the evolution of professionals and the profile of QA teams as key enablers of continuous quality to achieve more efficient software delivery processes. This implies changes in professional profiles and new combinations of skills to take into account, especially in relation to automation and the integration of quality activities in the continuous delivery process. Finally, the report also observes the challenge of providing transparency and visibility of testing activities as sources of feedback for projects, which require the automation of quality dashboards in organizations.
[MCPRO] How has the pandemic affected the quality of the software and its testing? How have the changes in the way of working caused by having to adopt, in many cases, teleworking and cloud and collaboration tools influenced all these processes?
[Jose Luis Antón] The post-pandemic scenario is accelerating digitization and also the need for agility and quality of systems and applications in all sectors. As IT modernizes and environments move to the cloud, companies are increasingly aware of the relevance and value of quality in all its dimensions. As a result, the implementation and improvement of the effectiveness and efficiency of testing and other quality engineering activities must go hand in hand with this acceleration.
Telecommuting has also highlighted the importance of decentralized work, which in turn enables testing and QA activities from multiple locations. We have implemented teleworking long before the COVID restrictions and fostering collaboration models with clients that allow us to make the most of diverse capacities even from different locations, seeking proximity, but also some flexibility.
We do it by betting on structured delivery methodologies and processes supported by advanced collaborative work environments. This is precisely another point that is given superlative importance in the WQR, 60% of those surveyed reflect the need to evolve collaborative work environments and forms of communication.
[MCPRO] What do you think the future of QA will look like in the corporate world, and how important can software quality assurance be in moving toward smarter business?
[Jose Luis Antón] Intelligence must also focus on its quality from various points of view and implement activities and actions to guarantee this quality. That is why at Sogeti we talk about quality engineering, as an essential activity in software. In this context, QA teams will also be an enabler and a source of growth in the Smart Industry.
WQR 21-22 notes that organizations are willing to pursue higher digital transformation quotas, and the main drivers of smart industry include improving efficiency (47%), increasing quality (46%), improvement of agility and flexibility (44%), and improvement of the customer experience (43%) as key axes. 42% of those surveyed in the report also noted plans to upgrade their current test labs with capabilities in 5G, Internet of Things (IoT), AI and autonomous systems in order to facilitate this task. Organizations should focus on investing in products and services that deliver the most value in the shortest time, as well as in people.
