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Leveraging Data Analytics for Informed Decision-Making in Process Management
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Author(s): Siva Subramanian R. (SRM Institute of Science and Technology, India), Thanammal Indu V. (Amrita Vishwa Vidyapeetham, India), Ignatious K. Pious (Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, India), Anni Princy B. (Panimalar Engineering College, India), K. Sudha (RMD Engineering College, India), Anto Gracious L. A. (R.M.K. College of Engineering and Technology, India)and P. Divya (IFET College of Engineering, India)
Copyright: 2026
Pages: 26
Source title:
Navigating Digital Transformation Through Business Process Management
Source Author(s)/Editor(s): Javier Martínez-Falcó (University of Alicante, Spain), Eduardo Sánchez-García (University of Alicante, Spain)and Bartolomé Marco-Lajara (University of Alicante, Spain)
DOI: 10.4018/979-8-3373-3336-6.ch008
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Abstract
This survey chapter aims at discussing the application of data analytics in process management in order to improve operational performance, decision making and innovation. This chapter also describes the analytical techniques including descriptive, predictive, and prescriptive analytics and illustrates their use in manufacturing, healthcare, finance, and logistics industries. The chapter also discusses new trends, which are in the development of process management, including artificial intelligence, edge analytics, and digital twins. However, there are some barriers to the implementation of the framework such as data quality, skill, privacy, and organizational readiness. The chapter concludes by emphasizing the importance of leveraging data analytics strategically and responsibly to ensure long-term success in a data-driven business environment.
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