[BBLISA-announce] Call for Book Chapters: Maximizing Management Performance and Quality with Service Analytics

[Yixin Diao]

------------------------------------------------------------------------------------------------

                                 CALL FOR BOOK CHAPTERS

    Maximizing Management Performance and Quality with Service Analytics

                               To be published by IGI Global

                      (Proposal Submission Date: 30 March 2014)

------------------------------------------------------------------------------------------------

Introduction

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.

Objective of the Book

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.

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.

Target Audience

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.

Recommended Topics

•	Data centric management of IT services
•	Predictive analytics for risk management in IT service engagement
•	Predicting and managing cost for service outsourcing contracts
•	Analyzing service operational data for management tasks
•	Analyzing social data for management
•	Optimization of service request management
•	Workload management in cloud services
•	Managing service risk in change management
•	Managing monitoring policies for event management
•	Analytics for prevention of server failures
•	Analytics for large-scale automation efforts in service management
•	Balancing security risk and service effort in compliance assurance

Submission Procedure

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
http://www.igi-global.com/publish/call-for-papers/call-details/1268.
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.

Publisher

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 http://www.igi-global.com. This publication is anticipated to be
released in 2015.

Important Dates

Proposal Submission: 		March 30, 2014
Notification of Acceptance: 		April 15, 2014
Full Chapter Submission: 		June 15, 2014
Review Results Returned: 		July 30, 2014
Revised Chapter Submission: 	August 30, 2014
Final Acceptance Notification: 	September 30, 2014
Final Chapter Submission:		October 15, 2014

Book Editors

Yixin Diao (IBM T.J. Watson Research Center, USA)
Daniela Rosu (IBM T.J. Watson Research Center, USA)
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://www.bblisa.org/pipermail/bblisa-announce/attachments/20140313/3d2bb11f/attachment.html>