We are entering the era of digital transformation where human and artificial intelligence (AI) work hand in hand to achieve data driven performance. Today, more than ever, businesses are expected to possess the talent, tools, processes, and capabilities to enable their organizations to implement and utilize continuous analysis of past business performance and events to gain forward-looking insight to drive business decisions and actions. AI-Enabled Analytics in Business is your Roadmap to meet this essential business capability. To ensure we can plan for the future vs react to the future when…mehr
We are entering the era of digital transformation where human and artificial intelligence (AI) work hand in hand to achieve data driven performance. Today, more than ever, businesses are expected to possess the talent, tools, processes, and capabilities to enable their organizations to implement and utilize continuous analysis of past business performance and events to gain forward-looking insight to drive business decisions and actions. AI-Enabled Analytics in Business is your Roadmap to meet this essential business capability. To ensure we can plan for the future vs react to the future when it arrives, we need to develop and deploy a toolbox of tools, techniques, and effective processes to reveal forward-looking unbiased insights that help us understand significant patterns, relationships, and trends. This book promotes clarity to enable you to make better decisions from insights about the future. * Learn how advanced analytics ensures that your people have the right information at the right time to gain critical insights and performance opportunities * Empower better, smarter decision making by implementing AI-enabled analytics decision support tools * Uncover patterns and insights in data, and discover facts about your business that will unlock greater performance * Gain inspiration from practical examples and use cases showing how to move your business toward AI-Enabled decision making AI-Enabled Analytics in Business is a must-have practical resource for directors, officers, and executives across various functional disciplines who seek increased business performance and valuation.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
LAWRENCE S. MAISEL is President of DecisionVu, a management consultancy specializing in Performance Management, Data Analytics, and Operations Improvements. He is an experienced executive with proven leadership to drive efficiency and control through planning and analysis, AI-enabled analytics, and operating process redesign. Maisel is a CPA, MBA, and CGMA and received AICPA's Thought Leader award for creating its Center for Excellence in Financial Management. He authored Predictive Business Analytics, co-created with Drs. Kaplan and Norton, the Balanced Scorecard Approach, and co-authored with Drs. Kaplan and Cooper Implementing Activity-Based Cost Management. He is a former Senior KPMG Partner and an Adjunct Professor, Columbia University's Graduate School of Business. ROBERT J. ZWERLING is a high-tech entrepreneur founding and growing software companies across telecom, manufacturing, distribution, high data availability, analytics, and AI. He is a noted speaker, thought leader, and author on AI and analytics, and has co-authored with Jesper H. Sorensen dozens of papers and the groundbreaking book, Implementing an Analytics Culture for Data Driven Decisions. Zwerling holds two degrees in engineering and is a registered Professional Engineer. He is Managing Director at Aurora Predictions, providing AI-enabled analytics with an intuitive/no-code interface to automatically reveal insights that moves the business's needle. He is co-founder of the Finance Analytics Institute, which teaches how to implement analytics through papers, surveys, benchmarks, and the Analytics Academy. JESPER H. SORENSEN is a Finance Executive with a proven track record of advancing the analytics agenda. He is currently a Vice President of Finance at Oracle, leading a large global finance team for a multi-billion-dollar business. Prior to Oracle he held leading positions with DuPont and IBM. He holds several advisory positions including advisory board member for Aurora Predictions. He co-authored with Robert J. Zwerling many articles and papers on analytics and the book Implementing an Analytics Culture for Data Driven Decisions. Sorensen is also the co-founder of the Finance Analytics Institute. He holds a Master in Economics and Management from the University of Aarhus, Denmark, and is certified in Risk Management and Strategic Decision Making from Stanford University
Inhaltsangabe
Acknowledgments ix Introduction XI Part I Fundamentals 1 Chapter 1 A Primer on AI-Enabled Analytics for Business 3 Chapter 2 Why AI-Enabled Analytics Is Essential for Business 17 Chapter 3 Myths and Misconceptions About Analytics 27 Chapter 4 Applications of AI-Enabled Analytics 39 Part II Roadmap 57 Chapter 5 Roadmap for How to Implement AI-Enabled Analytics in Business 59 Chapter 6 Executive Responsibilities to Implement Analytics 87 Chapter 7 Implementing Analytics 97 Chapter 8 The Role of Analytics in Strategic Decisions 109 Part III Use Cases 121 Chapter 9 Cases of Analytics Failures from Deviation to the Roadmap 123 Chapter 10 Use Case: Grabbing Defeat from the Jaws of Victory 133 Chapter 11 Use Case: Incremental Improvements to Gain Insights 143 Chapter 12 Use Case: Analytics Are for Everyone 151 Epilogue 157 Appendix - Analytics Champion Framework 159 About the Authors 209 About the Website 215 Index 217
Acknowledgments ix Introduction XI Part I Fundamentals 1 Chapter 1 A Primer on AI-Enabled Analytics for Business 3 Chapter 2 Why AI-Enabled Analytics Is Essential for Business 17 Chapter 3 Myths and Misconceptions About Analytics 27 Chapter 4 Applications of AI-Enabled Analytics 39 Part II Roadmap 57 Chapter 5 Roadmap for How to Implement AI-Enabled Analytics in Business 59 Chapter 6 Executive Responsibilities to Implement Analytics 87 Chapter 7 Implementing Analytics 97 Chapter 8 The Role of Analytics in Strategic Decisions 109 Part III Use Cases 121 Chapter 9 Cases of Analytics Failures from Deviation to the Roadmap 123 Chapter 10 Use Case: Grabbing Defeat from the Jaws of Victory 133 Chapter 11 Use Case: Incremental Improvements to Gain Insights 143 Chapter 12 Use Case: Analytics Are for Everyone 151 Epilogue 157 Appendix - Analytics Champion Framework 159 About the Authors 209 About the Website 215 Index 217
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