05394nam a22005295i 4500 978-3-031-61343-2 DE-He213 20251030112334.0 cr nn 008mamaa 240626s2024 sz | s |||| 0|eng d 9783031613432 978-3-031-61343-2 10.1007/978-3-031-61343-2 doi HF5548.125-.6 KJQ bicssc COM005030 bisacsh KJQ thema Process Intelligence in Action [electronic resource] : Taking Process Mining to the Next Level / edited by Lars Reinkemeyer. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. XXIV, 248 p. 107 illus., 67 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Part I: From Process Mining to Process Intelligence -- 1. Evolution -- 2. How to get started -- 3. Driving user adoption -- 4. Success Factors for Digital Transformation -- 5. Value as the name of the Game -- 6. Operating Models and Centers of Excellence -- 7. Process Intelligence as Transformation Enabler -- 8. Challenges, Pitfalls and Failures -- 9. Key Learnings -- Part II: Best Practice Use Cases -- 10. ABB: Driving a Sustainability Transformation with Process Intelligence -- 11. BMW: Process Intelligence for Everybody – Organizational Setup & Scaling -- 12. Bosch: Business & IT Transformation facilitated by Process Intelligence -- 13. Ingka: Inspiring a Community for Open Exchange -- 14. Kimberly-Clark: Process Intelligence as Catalyst for Supply Chain and Global Business Services Transformation -- 15. Merck, Sharp & Dohme: Digital Transformation in Shared Services and Beyond -- 16. PepsiCo: From Discovery to Dollars - Turning Process Insights into Value -- 17. Reckitt’s Digital Transformation: Unleashing the Power of Process Intelligence at Scale -- 18. Saint Gobain: The Power of Executive Sponsorship -- 19. Siemens: Acting resiliently through hybrid Process Intelligence in the Supply Chain Metaverse -- 20. thyssenkrupp Rasselstein: Connected Supply Chain across thyssenkrupp -- 21. Uniper: Empowering Business Transformation through Process Orchestration -- Part III Future of Process Intelligence -- Academic Perspective: How Object-Centric Process Mining Helps to Unleash Predictive and Generative AI -- 23. Business Perspective: The Future of Intelligent Business Process Execution. This book provides operational guidance on how to bring process mining to the next level, with process intelligence enabling companies to improve process efficiency and realize value. Written by practitioners, it combines the editor’s 10-year experience in this field gained at Celonis and Siemens, with 12 best practice use cases from international companies representing multiple industries and domains. Part I sets the stage describing the evolution from process mining to process intelligence. The chapters guide the reader step by step, from getting started to driving adoption at scale. Success factors critical for digital transformations and a detailed path to value realization are presented. Best practices on operating models and Centers of Excellence (CoEs) are shared as accelerators for successful digital transformations. Part II presents 12 use cases written by transformation- and CoE leaders who have achieved significant impact and value with process intelligence in their respective organization. All use cases have been written independent from any particular software, with a focus on evangelizing the topic and showcasing how companies like ABB, BMW, Bosch, Merck, PepsiCo, Saint Gobin, Siemens, and others leverage the capability to drive value. Part III provides an outlook on the future of process intelligence from an academic and an operational perspective, with a special focus on the disruptive impact of GenAI with future scenarios, challenges and recommendations. The book is written by practitioners for practitioners. Readers may have responsibilities as senior executives, transformation leaders, process managers and experts, consultants, change evangelists, etc. The book provides operational, hands-on tips on how to accelerate process transformation in organizations by detailing best practices as well as possible pitfalls. Business Data processing. 59544 Business information services. Artificial intelligence. 58441 Business Informatics. 65949 Business Information Systems. 66184 Artificial Intelligence. 58441 Reinkemeyer, Lars. editor. edt http://id.loc.gov/vocabulary/relators/edt 79382 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031613425 Printed edition: 9783031613449 Printed edition: 9783031613456 https://doi.org/10.1007/978-3-031-61343-2 ZDB-2-SCS ZDB-2-SXCS 61049 61049