Forrester: Automated Testing Still Challenges Organizations

July 22, 2022

A global study, conducted by Forrester surveyed test operations decision-makers to understand the state of test strategies and technologies.

The research report, titled Conquer Testing Complexities with Automation and Artificial Intelligence (AI), identified that automation is gaining inroads, with 75% of organizations using a combination of automated and manual testing. However, only 11% have a fully automated strategy. With growing complexity, the number of tests is increasing (77%) and without automation, product development slows.

According to Jeff Harris, vice president, Portfolio and Global Marketing at Keysight Technologies, "We learned in the study that companies feel pressure to do more test automation, especially when asked about the future. Manual or partially automated strategies simply can't keep up with the needs of organizations today, and without AI-powered automation, they will struggle to conquer testing complexities. Additionally, we expect the COVID pandemic to accelerate adoption of remote development, automated test sequencing. We also expect a much higher use of digital twins as development teams strive to continue working together but from different locations. At Keysight, we’re building this automation of intelligence across the workflow into our entire software product portfolio to address these needs and drive test and validation automation forward."

The primary technical challenges resulting from testing complexities are long cycles, accurately capturing bugs and issues, and then fixing them. These problems directly impact business results and the product development process.

Respondents ranked the outcomes as:

51% - Security breach risk

48% - Increased expenses

42% - Slower time to market

36% - Defective product

34% - Loss of revenue

Given the emphasis placed on the risk of data security breaches and slow delivery times in automated testing, Bloor Research suggests the integration of production data masking or test data synthesis as part of system testing design. In his article IRI Voracity and Test Design Automation, analyst Daniel Howard cites examples of seamless invocations of these fast-executing jobs in popular DevOps pipelines to substantially ameliorate or remove the test data bottlenecks involving sensitive data which increase product development costs.

However, enterprises recognize that manual and partially automated testing strategies cannot keep pace with the increasing complexity of products. As a result, 45% will consider using a fully automated approach in the next three years, a 409% growth. Over half (52%) stated they would look at AI for integrating complex test suites, a 325% growth.

By shifting to intelligent automated testing strategies, organizations expect benefits. Operational improvements include increased productivity (59%), ability to simulate product function or performance (54%) and bug fix automation or simulation to save time on fix-retest cycles (53%). The anticipated business impact spans higher quality product that increases customer satisfaction (59%), the ability to reduce time to market (50%) and more agile product development cycles (50%).

As described in the survey, the most anticipated technology or operations improvements from automation and AI are increased productivity, ability to simulate product function/performance and bug fix automation/simulation.

A weak link in your testing lifecycle will often lead to bottlenecks.

Source: Bloor Research

In this study, Forrester conducted an online survey of 406 test operations decision-makers at organizations in North America, EMEA and APAC to evaluate current testing capabilities and to hear their thoughts on investing in automation (including AI). Questions provided to the participants asked about their organizations' current testing environments, future investments, challenges and expected outcomes from testing automation.