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Solving the Automation Puzzle: A Framework for Technology Selection in Process Automation Initiatives
Thomas Muehlbauer, Leonie Kitzeder, Maximilian Faaß, Johanna Riedl, Marcus Fischer
In many developed countries, productivity growth has stagnated, exacerbated by demographic shifts and workforce reductions, creating critical gaps in industrial and service processes. While artificial intelligence offers potential solutions, it cannot fully address these challenges. Organizations must adopt broader automation strategies to maintain competitiveness. Despite advancements, the proportion of automated processes remains low, largely due to initiative complexity and the diversity of technologies. This paper proposes an integrated framework to guide organizations in selecting appropriate automation technologies. Following the Design Science Research methodology, we develop a solution-oriented artifact and iteratively evaluate it through business scenarios. Our contributions include a comprehensive review and categorization of automation technologies, the development of a practical framework, and insights from real-world applications. The findings aim to help practitioners overcome common barriers and provide a foundation for future research in process automation.
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