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<font size="2" face="sans-serif"> CALL FOR BOOK CHAPTERS
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<font size="2" face="sans-serif"> Maximizing Management Performance and Quality with Service Analytics
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<font size="2" face="sans-serif"> To be published by IGI Global</font><br>
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<font size="2" face="sans-serif"> (Proposal Submission Date: 30 March 2014)</font><br>
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<font size="2" face="sans-serif"><b>Introduction
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<font size="2" face="sans-serif">IT service management comprises a large variety of management processes and technologies that enable service providers to manage IT infrastructures and applications from the perspective of their customers and of their own business. Aligned with the best industry practices (e.g., Information Technology Infrastructure Library (ITIL)), IT service providers track customer requests, IT system performance, and service operation details, producing large volumes of process data. This wealth of data can be effectively exploited to reveal valuable insights in support of business goals to maximize performance, quality of service, and customer satisfaction. Towards this end, a wide variety of analytic methods and tools are employed to analyze the process data within and across dimensions such as service processes, workload types, customer domains, and delivery geographies. Generally, the analytic solution requires the integration of tools and methods from domains such as data mining, operations research, control theory, and natural language processing. Extensions of state of the art methods are required to address the domain-specific content features and quality of results.</font><br>
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<font size="2" face="sans-serif"><b>Objective of the Book
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<font size="2" face="sans-serif">Maximizing performance and quality in IT services demands effective modeling of all aspects of IT services, ranging from service engagement to steady-state delivery. Service Analytics identifies the collection of business analytics tools that address the IT service management processes, quality and productivity metrics, customer interactions, and social factors. This book intends to offer a selection of Service Analytics solutions for process modeling and optimization that have been practically proven to drive excellence in IT service management. Specifically, this book aims to address several categories of analytics problems, such as (1) workload characterization to understand workload and effort arrival patterns, (2) predictive analysis to project observed insights on IT process performance and quality into the future, and (3) process optimization to improve service management effectiveness.</font><br>
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<font size="2" face="sans-serif">The book aims to address a comprehensive set of IT service management challenges related to incident management, change management, risk management, skills management, etc. We expect the book to excel both from the view of advancing the data analysis technologies and from the view of tacking the complexity of IT service providers' business. </font><br>
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<font size="2" face="sans-serif"><b>Target Audience
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<font size="2" face="sans-serif">The book is primarily targeted for two types of audience: (1) practitioners engaged in IT service management who are extremely interested in delivering high-quality and cost-competitive IT services, and (2) 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. We expect this book to serve as both a practical reference and an advanced scientific source for those interested in the latest progress of this new research area of service analytics for IT service management.</font><br>
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<font size="2" face="sans-serif"><b>Recommended Topics</b></font><br>
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<font size="2" face="sans-serif">• Data centric management of IT services</font><br>
<font size="2" face="sans-serif">• Predictive analytics for risk management in IT service engagement</font><br>
<font size="2" face="sans-serif">• Predicting and managing cost for service outsourcing contracts</font><br>
<font size="2" face="sans-serif">• Analyzing service operational data for management tasks</font><br>
<font size="2" face="sans-serif">• Analyzing social data for management</font><br>
<font size="2" face="sans-serif">• Optimization of service request management</font><br>
<font size="2" face="sans-serif">• Workload management in cloud services</font><br>
<font size="2" face="sans-serif">• Managing service risk in change management</font><br>
<font size="2" face="sans-serif">• Managing monitoring policies for event management</font><br>
<font size="2" face="sans-serif">• Analytics for prevention of server failures</font><br>
<font size="2" face="sans-serif">• Analytics for large-scale automation efforts in service management</font><br>
<font size="2" face="sans-serif">• Balancing security risk and service effort in compliance assurance</font><br>
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<font size="2" face="sans-serif"><b>Submission Procedure
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<font size="2" face="sans-serif">Authors are invited to submit a brief chapter proposal (approximately 500 to 1,000 words) clearly explaining the mission and content of the proposed chapter. Brief overview of author’s previous work on the topic and intended extension for this chapter should be included with related references. All proposals should be submitted through IGI Global at </font><font size="2" face="sans-serif"><a href="http://www.igi-global.com/publish/call-for-papers/call-details/1268">http://www.igi-global.com/publish/call-for-papers/call-details/1268</a></font><font size="2" face="sans-serif">. Authors of accepted proposals will be notified about the status of their proposals and sent guidelines for full chapter submission. All submitted chapters will be reviewed on a double-blind review basis. Contributors may also be requested to serve as reviewers for this book project. Only original contributions written in English that have not been published or submitted for publication elsewhere will be accepted for publication.</font><br>
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<font size="2" face="sans-serif"><b>Publisher </b></font><br>
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<font size="2" face="sans-serif">This book is scheduled to be published by IGI Global, a leading international academic publisher offering premier and peer-reviewed content to international researchers, librarians, and universities under five imprints - Information Science Reference, Business Science Reference, Medical Information Science Reference, Engineering Science Reference, and IGI Publishing. For additional information regarding the publisher, please visit </font><font size="2" face="sans-serif"><a href="http://www.igi-global.com">http://www.igi-global.com</a></font><font size="2" face="sans-serif">. This publication is anticipated to be released in 2015.</font><br>
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<font size="2" face="sans-serif"><b>Important Dates
</b></font><br>
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<font size="2" face="sans-serif">Proposal Submission: March 30, 2014</font><br>
<font size="2" face="sans-serif">Notification of Acceptance: April 15, 2014</font><br>
<font size="2" face="sans-serif">Full Chapter Submission: June 15, 2014
</font><br>
<font size="2" face="sans-serif">Review Results Returned: July 30, 2014
</font><br>
<font size="2" face="sans-serif">Revised Chapter Submission: August 30, 2014
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<font size="2" face="sans-serif">Final Acceptance Notification: September 30, 2014</font><br>
<font size="2" face="sans-serif">Final Chapter Submission: October 15, 2014</font><br>
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<font size="2" face="sans-serif"><b>Book Editors</b></font><br>
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<font size="2" face="sans-serif">Yixin Diao (IBM T.J. Watson Research Center, USA)</font><br>
<font size="2" face="sans-serif">Daniela Rosu (IBM T.J. Watson Research Center, USA)</font><br>
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