Maximizing Management Performance and Quality with Service Analytics: 9781466684966: Business & Management Books

Publication Status: E-Book and Print Version Available for Purchase

ISBN13: 9781466684966

EISBN13: 9781466684973

DOI: 10.4018/978-1-4666-8496-6

Description:

Service analytics studies the collection of business analytics models and tools for the improvement of IT service management processes. By analyzing related quality, cost, and productivity metrics, as well as customer interactions and social factors, organizations can effectively exploit these resources to reveal valuable insights in support of business goals, maximizing performance, quality of service, and customer satisfaction.

Maximizing Management Performance and Quality with Service Analytics offers a selection of service analytics solutions for process modeling and optimization proven to drive excellence in IT service management. This book is for practitioners engaged in IT service management who are interested in delivering high-quality and cost-competitive IT services, as well as academic and industrial researchers in the fields of information technology and computer science who are advancing data analysis, modeling, and optimization methods to new emerging fields.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

Complex Service Delivery Systems
Configuration Analytics
IT Incident Management Services
Optimization of Process Management
Optimizing Cloud Storage Management Services
Predictive Analytics for Business Processes
Service Development Strategy in a Global Environment
Ticket Data Clustering
Visual Analytics to Diagnose Productivity and Quality Issues

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Yixin Diao is a Research Staff Member at the IBM Thomas J. Watson Research Center in Yorktown Heights, New York. He received his Ph.D. degree in Electrical Engineering from Ohio State University in 2000. He has published more than eighty papers in systems and services management and is the co-author of the book "Feedback Control of Computing Systems" (Wiley 2004). He received IBM Outstanding Innovation Award in 2005, was named to IBM Master Inventor in 2007, and received IBM Outstanding Technical Achievement Award in 2013. He is the recipient of the 2002 Best Paper Award at IEEE/IFIP Network Operations and Management Symposium; the 2002-2005 Theory Paper Prize from the International Federation of Automatic Control; the 2008 Best Paper Award at IEEE International Conference on Services Computing; and the Second Prize of the 2012 Innovation in Analytics Award from Institute for Operations Research and the Management Sciences. He served as Program Co-chair for the 6th International Conference on Network and Service Management in 2010 and the 13th IFIP/IEEE International Symposium on Integrated Network Management in 2013. He is an Associate Editor of IEEE Transactions on Network and Service Management, and Journal of Network and Systems Management.

Daniela Rosu is a Research Staff Member in the Service Delivery Management and Analytics Department of the IBM T. J. Watson Research Center. Her current research interests include process modeling and optimization of IT Service Management processes. In the past, Dr. Rosu worked in multiple areas including productivity tools for IT Service Operations, business goal-driven resource management in complex IT environments, operating systems support for high-performance Web servers, distributed Web caching infrastructures, and real-time operating systems. Dr. Rosu received a Ph.D. degree in Computer Science from the Georgia Institute of Technology in 1999, with a dissertation in the area of adaptive resource management in complex real-time systems. She also holds an M.S. degree in Computer Science from Georgia Institute of Technology (1995), and a MS. in Theoretical Computer Science from the Faculty of Mathematics, University of Bucharest, Romania (1987).

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