Exploring Opportunities in Software Testing Services

Software testing services constitute a substantial and expanding segment of the information technology (IT) services industry. These services have a long history of being employed by various businesses to ensure the quality and reliability of their software applications and have continued to adapt with emerging capabilities. 

However, what does this mean for the current state of software testing services and the investment prospects for those seeking to capitalise on its next phase of growth?

Despite the well-established presence of software testing services, L.E.K. Consulting believes that the current landscape for such services presents ample opportunities for tapping into a new era of expansion, particularly given the surge in automation and AI’s increasing impact. In this Executive Insights, we delve into the primary trends and priorities steering the growth of software testing services and explore the implications for investors and businesses as they evaluate their strategies in this evolving market.

Software testing services represent a large, growing and resilient market

The software testing services market represents a substantial opportunity and has continued to thrive with promising growth potential. As digital transformation gains momentum across various sectors, there remains a persistent and substantial demand for quality assurance (QA) and testing services.

This upward trajectory is driven by several key factors, including: 

1. Growing spend on software implementation contributing significantly to the sustained demand for testing services (see Figure 1)
2. Greater software complexity necessitating thorough testing, fuelling the need for testing services
3. Evolving regulatory standards and compliance mandates compelling organisations to invest in rigorous testing to ensure adherence
4. Continued reliance on outsourcing to access specialised testing expertise and resources
5. The shortage of skilled testing professionals further solidifying the importance of outsourcing for fulfilling testing needs

Notably, the spend on testing remains resilient due to its critical role in ensuring the effective functioning of software systems. Most clients recognise that the costs associated with errors stemming from inadequate testing — such as potential business losses, security breaches and damage to brand reputation — far outweigh any savings achieved by skimping on testing efforts (see Figure 2). This recognition underscores the continuing importance of strong testing methodologies within the software industry.

Shift to Agile has increased testing frequency, not workload

The majority of software testing services (by value) are delivered in an Agile setup, with the remaining being delivered in a waterfall or hybrid setup. Agile models require consistent and frequent testing due to shorter release cycles. Yet the total testing workload remains comparable to traditional waterfall methods; it’s just distributed over the project’s duration in Agile.

Additionally, while Agile requires close collaboration between development and testing, it is not a barrier to outsourcing. The need for independent evaluation, specialised expertise and affordability can still prompt the selection of an independent service provider, thus implying a limited-to-marginally positive impact on the size of the market, given the shift in skillset (driving hourly rates).

Automation is replacing legacy manual test execution while increasing demand for specialist expertise

The increased complexity of software and the emphasis on more rapid release cycles have led to an increase in the use of automated testing and QA tools to keep pace. 

Automation is largely replacing legacy manual test execution of highly repeatable functional tests (especially unit tests and regression tests); however, more complex nonfunctional tests require a human layer of expertise and as such have not yet been widely automated (particularly security and UX testing). 

The true value of automation lies in its ability to increase the number and extent of tests that can be run in shorter time periods, aligning the testing and QA function more closely with Agile development. So while automation leads to increased productivity, these productivity gains are reinvested to expand the scope and depth of testing in terms of (a) greater volume of test coverage (more tests can be run in a shorter amount of time); (b) greater breadth of testing coverage (e.g. testing a web application across different browser versions, screen sizes); (c) greater depth by handling more complex scenarios (e.g. complex regression testing scenarios, performance testing) resulting in higher testing quality and a stable volume of testing workload.

The rise of automation has also shifted labour demand: there’s a reduced need for low-skill test execution roles and a heightened demand for specialists in test design, automation frameworks and analysis.

Overall, automation is a positive driver of the market; it is increasing reliance on outsourcing and leading to higher hourly rates.

Companies that make the investment to leverage automation in testing and QA (see examples of automation tools in Figure 4) are able to improve test coverage of code bases, reduce test cycle time and better detect defects before software is pushed live to production environments. Over 40% of organisations highlight it as one of the most important objectives to ensure test quality (see Figure 3).
 

AI is not expected to disrupt the market, but it is rather a further evolution of automation trends

Traditional AI (non-generative) is already being used to drive automation in text execution, test analysis and reporting. However, emerging generative AI (Gen AI) tools can be used to generate synthetic test data, create test cases, write automation scripts and further enhance the quality of reporting and analysis. These tools can also optimise test execution, particularly in scenarios like regression testing, where they can determine which test cases to prioritise through data-backed risk assessment (as opposed to intuition-based) and considering time/resource constraints, enhancing testing efficiency and effectiveness.

As with automation, productivity enhancements from AI are expected to be re-invested towards improving the quality of testing. 

Additionally, the emergence of AI (see Figure 5) will introduce new testing prospects, such as evaluating code generated using AI and testing AI-based systems. As code development becomes more reliant on AI, code can become more susceptible to issues such as AI hallucination, where AI generates incorrect but plausible code, which increases the need for robust testing. In addition, as AI use cases develop across industries, testing AI-based systems is expected to emerge as a new testing domain, requiring different testing skills (focused on data science).

With the growing influence of AI (see Figure 5), there will still be a requirement for highly skilled testers to oversee testing strategies and effectively deploy AI tools. Moreover, customers will continue to outsource because establishing in-house AI capabilities for testing is challenging due to a shortage of skilled talent.

This presents new opportunities for software testing service providers that are able to demonstrate AI competency and deliver additional value to their customers. To capitalise on this opportunity, software testing service providers should: 

• Proactively adopt tools to align with the advancements of Gen AI specifically by integrating AI in testing scripts as well as developing proprietary technologies (e.g. machine learning algorithms). The advancements in AI are likely to be facilitated by the existing top vendors of testing automation solutions
• Focus on acquiring the right talent with the skillsets and capabilities to perform testing with Gen AI tools 
• Prioritise the use of AI to minimise defects and improve the overall quality of software development, ensuring that customer outcomes are elevated through AI (rather than merely concentrating on cost efficiencies)

Productivity gains from automation/AI offer service providers the chance to enhance margins

The broader IT service industry operates using service-based models, which allow providers to bank productivity gains and improve gross margins. Software testing service providers should focus on developing their ability to provide additional pricing models (beyond T&M (time and materials)), and those with strong expertise in automation have the opportunity to retain productivity gains by transitioning customers to fixed-price/more opaque pricing models.

However, it should be noted that the purchasing context is important in determining the pricing model. For example, certain industries may favour service-based models over other industries due to differences in procurement practices. Similarly, certain types of testing (e.g. regression testing) may be more suited to a service-based pricing model (e.g. points-based system based on complexity). However, in many situations (e.g. staff augmentation in Agile), T&M will be the preferred model. 

A shift to a service-based model can also enable shifting delivery to near-shore/off-shore service models, allowing software testing service providers to further optimise costs and improve margins.

How L.E.K. can help 

At L.E.K. Consulting, we specialise in navigating dynamic markets. Drawing from our in-depth insights into software testing and broader IT services, we can illuminate the core trends and growth drivers, especially in the realms of automation and AI. Our expertise can help investors and businesses identify and capitalise on emergent opportunities, ensuring they are strategically positioned for the upcoming expansion phase. 

For more information, contact strategy@lek.com. 

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