Next-Generation SAP Testing with Cloud ALM : Evidence from Four Company Cases

Gombkötő, Judit and Kozma, Tímea and Szalay, Zsigmond Gábor (2026) Next-Generation SAP Testing with Cloud ALM : Evidence from Four Company Cases. In: Interdisciplinary Approaches to addressing the Opportunities and Challenges posed by Digitalization and Artificial Intelligence publication in progress. Budapesti Gazdaságtudományi Egyetem (BGE), Budapest, pp. 26-39. ISBN 9786156886309

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Abstract

Enterprise resource planning implementation projects remain high-risk undertakings, and failures frequently arise from insufficient test depth, weak defect management, and limited readiness assessment. Nowadays, the cloud environment is the platform where Enterprise Resource Planning systems have transitioned. The importance of structured test processes is a primary focus in Enterprise Resource Planning projects, as they simulate the future system. This study compares four cloud-based implementations (two with Excel for testing and two with cloud-based application lifecycle management). The study analyses how testing tools affect testing quality, defect management, and post-go-live stability. The comparison was based on quantitative project data, including test case logs, defect records, testing duration, cycle counts, and hypercare incidents. Descriptive statistics and non-parametric comparative methods were used for analysing the data. The research results show that projects with integrated lifecycle management tool support conducted deeper test cycles and detected more defects before go-live, and, as a result, systems were more stable after deployment. Excel-based testing was adequate only for smaller, less complex rollouts and led to higher defect density post-golive due to limited traceability and fragmented workflows. The study highlights the strategic relevance of testing depth and demonstrates the benefits of integrated lifecycle management tools for implementation quality. These results contribute to Enterprise Resource Planning research by providing empirical evidence that test management tools influence project outcomes and long-term system stability.

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