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Unlocking success: a decision support system for agile assessment in intelligent automation projects

Author

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  • Sreenivasa Sekhar Josyula
  • M. Suresh
  • R. Raghu Raman

Abstract

Intelligent automation is an emerging volume of software development work in today's industry as an instrument for driving digital transformation, innovation, and cost efficiencies. Applying agile software development (ASD) practices in this area is being increasingly explored with appropriate tailoring of agile practices, tools, and procedures. The question then arises of the level of agility in these programs and how it can be measured consistently. This research aims to develop a decision system to support (DSS) practitioners and academicians in their pursuit of this category of software applications by identifying agility criteria and enablers. Fuzzy logic is often used in decision support systems where inputs are vague as it helps convert uncertain feedback into linguistic variables as a reliable measurement and mathematical method. This research contributes by synthesising the concepts of decision support, agility, and fuzzy logic in the context of Intelligent Automation. Such a DSS application is developed and provided for access to the research fraternity. The authors discussed the implications of this research, the limitations of the research methodology, and opportunities for future research in this domain.

Suggested Citation

  • Sreenivasa Sekhar Josyula & M. Suresh & R. Raghu Raman, 2025. "Unlocking success: a decision support system for agile assessment in intelligent automation projects," International Journal of Process Management and Benchmarking, Inderscience Enterprises Ltd, vol. 19(4), pages 484-512.
    • Handle: RePEc:ids:ijpmbe:v:19:y:2025:i:4:p:484-512
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