Leave test automation to those who define the requirements
In this blog article, you will learn about the major benefits of product owners automating the tests themselves
1. The well-known communication gap
In many companies, the implementation of requirements in tests still involves several people. Product owners formulate features, development translates these into technical concepts and the testers create automated tests. The result: interpretations, misunderstandings and a high communication effort. Specialist departments often do not recognise themselves in the tests and testers complain about a lack of clarity. This communication gap costs time, money and quality.
Why is information lost when requirements become tests?
Every translation step harbours losses. Requirements that initially appear clear lose precision due to reformulations, technical abstraction or incomplete documentation. The intention of the specialist department is distorted by technical interpretations. In addition, the testers often lack the in-depth understanding of the process to correctly assess the business-critical risks.
Why are requesters most familiar with the test conditions?
Anyone who sets requirements knows the relevant processes, special cases and accepted tolerances from day-to-day business. Specialist users know what ‘correct’ means because they live it every day. This knowledge is more valuable than any technical specification. If these same people can also formulate test cases, tests become more realistic, more comprehensive and more practical.
2. The technical hurdle
Traditional test automation requires programming knowledge or technical understanding. Specialist departments are therefore reliant on IT teams to translate their requirements into code. Tools are usually not designed for laypeople, but for developers. Added to this is the fear of responsibility and the uncertainty of ‘breaking something’.
How modern technology enables non-technical people to write tests
AI-supported low-code or no-code tools have the potential to change the distribution of roles. With intuitive interfaces, ready-made building blocks and natural language, specialist users can now create tests themselves. This makes test automation more accessible than ever.
Example: New automated tests for a new feature
A new feature has been implemented.
- Classical automation The tester creates new tests and implements the test steps. To do this, he extends the existing page structure and creates individual methods to operate the elements. These methods are then used in the tests.
- AI-supported approach The TOE creates descriptions for the test executions in natural language. The AI-supported test tool takes over the technical implementation and execution.
A before-and-after comparison shows that instead of lengthy and time-consuming test implementation, tests are created in just a few hours and executed immediately.
When specialist departments test themselves, a more direct, realistic image of the requirements is created. Test errors are reduced because there are no more interpretation errors. Feedback on the quality of new software is received more quickly. This accelerates the development cycle and sustainably increases product quality.
How do I introduce the approach in my company?
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identify recurring test scenarios with a high communication effort.
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introduce a suitable low-code test tool.
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train specialist users specifically in test case creation.
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start with pilot projects in a selected specialist area.
5 Establish roles for test coaches who support but do not take over.
- measure progress based on feedback cycles, error rates and effort.
Conclusion
When specialist departments automate testing themselves, the responsibility for quality shifts to where it originates: at the beginning of the process. The democratisation of test automation leads to better products, more agility and faster market launches. Those who shape this cultural change not only save time, but also gain a real competitive advantage.
Investing in easy-to-use test tools pays off quickly: Less coordination, reduced error costs, shorter time-to-market. In many cases, the investment pays for itself after just a few months. Companies not only gain efficiency, but also transparency regarding quality and risks.