Solving the Dynamic Complexity Dilemma: Predictive and Prescriptive Business Management: Answering the Need for a New Paradigm - Hardcover

Abu El Ata, Nabil; Perks, Maurice J.

Hardcover

ISBN 10: 364254309X ISBN 13: 9783642543098

Publisher: Springer, 2014

Synopsis

Solving the Dynamic Complexity Dilemma examines the growing business problem of dynamic complexity and presents a path to a practical solution. To achieve better predictability, organizations must be able to expose new, dangerous patterns of behavior in time to take corrective actions and know which actions will yield the optimal results. This book promotes new methods of risk management that use data collection, analytics, machine learning and automation processes to help organizations more accurately predict the future and take strategic actions to improve performance outcomes. The presented means of achieving this goal are based upon the authors' practical experiences, backed by scientific principles, and results achieved through consulting engagements with over 350 global organizations.

About this title

About the Author

Dr. Nabil Abu el Ata is the founder of Accretive Technologies and has invested over 20 years maturing the science and practical application behind the company's solution offering with over 15 patents. In the late 1970s Dr. Abu el Ata's mathematical discoveries provided accurate coordinates for space exploration. By solving a problem that was previously defined as unsolvable, Dr. Abu el Ata set the foundation for a new era of risk management, termed Optimal Business Control (OBC), which today enables companies to more accurately predict the future and take strategic actions to improve business outcomes. Dr. Abu el Ata's accomplishments include doctorate (Ph.D. and D.Sc. from Paris-Sorbonne) and B.S. in Mathematics and M.S. in Physical Sciences (Royal Observatory, Sussex-Cambridge Universities).  He is a former Doctorate Fellow of the European Space Organization; former Data Processing Director and Advisor for the French Atomic Energy Authority; former CTO of First Data; an External Professor for a number of universities in France, the UK, and the US; and Laureate of Computer World Honors 2008.


Dr. Maurice J. Perks is a visiting professor of IT Integration at the University of York. He joined IBM in 1968 as a Systems Engineer. During his tenure as an IBM employee (1968-2010) he attained the level of IBM Fellow and specialized in the design of IT systems for large organizations. Dr. Perks is noted for his methodological approach, which helps to understand and assess the complex­ity of systems, and his ability to apply that knowledge to design and modify complex sys­tems. He is currently working to promote under­standing of modern IT systems complexity, and is bringing new ways of combining the triangle of business knowledge, IT knowledge and mathematics to this challenge. He is a great believer in the increased use of modeling and simulation to help tame the growing challenges that business and IT change pose.

From the Back Cover

Dynamic complexity results from hidden, un­known factors--or more precisely, interactions between factors--that can unexpectedly im­pact the perfor­mance of systems. When the influences of dynamic complexity are not meas­ured and understood, new never-seen-before behaviors can come as unwelcomed surprises, which disrupt the performance of systems. Left alone, processes that were once prized for their effi­ciency unexpectedly begin to degrade--costs increase, while volumes and quality decline. Evidence of problems may come too late for effective resolution as technology advance­ments induce rapid change and compress the time available to react to that change. The results of dynamic complexity are always negative and unmanaged dynamic complexity can bring business or global systems to the point of sudden chaos. The 2009 H1N1 pandemic, 2008 Credit Crunch and 2011 Fukushima Daiichi nuclear disaster are global examples of the dangers of undiagnosed dynamic complexity.

With increasing frequency executive leaders today are discovering that their business and IT system performance levels are not meeting expectations. In most cases these performance deficiencies are caused by dynamic complexity, which lies hidden like a cancer until the symptoms reveal themselves--often when it is too late to avoid negative impacts on business outcomes. This book examines the growing business problem of dynamic complexity and presents a path to a practical solution. To achieve better predictability, organizations must be able to expose new, dangerous patterns of behavior in time to take corrective actions and know which actions will yield the optimal results. The book authors promote new methods of risk management that use data collection, analytics, machine learning and automation processes to help organizations more accurately predict the future and take strategic actions to improve performance outcomes. The presented means of achieving this goal are based upon the authors' practical experiences, backed by scientific principles, and results achieved through consulting engagements with over 350 global organizations.

Edition details

• Publisher: Springer
• Publication date: 2014
• Language: English
• ISBN 10: 364254309X
• ISBN 13: 9783642543098
• Binding: Hardcover
• Number of pages: 307