Strategic Considerations for Hyperautomation
Abstract
This chapter dives into how Business Process Management (BPM) is changing the game, especially when paired with cutting-edge hyperautomation technologies like Robotic Process Automation (RPA) and Artificial Intelligence (AI). BPM is making waves in crucial sectors such as manufacturing, financial services, and healthcare, helping to boost operational efficiency, cut down on errors, and streamline cycle times. When you stack it up against traditional management methods, BPM shows some impressive results—think 40–60% improvements in process efficiency, 70–90% fewer errors, and 30–50% savings on costs. The perks of BPM encompass operational, strategic, and financial aspects, leading to smoother processes, greater agility, better decision-making, and a solid return on investment. Yet, organizations encounter some bumps in the road when it comes to adopting BPM, facing both technical hurdles (like system integration, data management, and security) and organizational challenges (such as resistance to change and skill gaps). To truly succeed, companies need a strong architectural design, effective leadership, user buyin, and a commitment to continuous improvement. Analyzing the impact shows that BPM can significantly boost business competitiveness, automate tasks, and make better use of resources. These reported efficiency gains (e.g., 40–60% in process improvements and 30–50% cost reductions) should be interpreted in the context of comparative benchmarks and empirical studies. For instance, van der Aalst [1] emphasizes these outcomes in organizations that adopted process mining alongside BPM, as opposed to control groups relying on manual methods. Similarly, industry reports often measure baseline performance pre- and post-automation over 6–12 month intervals. Clarifying such methodological details ensures the reported benefits are rooted in validated empirical comparisons. As more industries jump on the hyperautomation bandwagon, BPM stands out as a crucial framework for achieving sustainable digital transformation [2-4].
Fields of Study & Subjects
Robotic Process Automation Applications
Business Process Modeling and Analysis
Impact of AI and Big Data on Business and Society
Publication details
- Journal / source
- BENTHAM SCIENCE PUBLISHERS eBooks
- Pages
- 31–59
- Publication date
- 7 January 2026
- Document type
- Book chapter