Maximizing Management Performance and Quality with Service Analytics, 1st Edition

  • Daniela Rosu
  • Yixin Diao
  • Published By: Business Science Reference
  • ISBN-10: 1466684976
  • ISBN-13: 9781466684973
  • DDC: 658.4
  • Grade Level Range: College Freshman - College Senior
  • 464 Pages | eBook
  • Original Copyright 2015 | Published/Released April 2016
  • This publication's content originally published in print form: 2015

  • Price:  Sign in for price

About

Overview

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.

Table of Contents

Front Cover.
Title Page.
Copyright Page.
Advances in Logistics, Operations, and Management Science (ALOMS) Book Series.
Titles in This Series.
Table of Contents.
Detailed Table of Contents.
Foreword.
Preface.
Resource Management: Optimal Management of Human Resources and Skills for Balanced Costs and SLA Attainment.
1: Capacity Planning and Management of IT Incident Management Services based on Queuing Models.
2: Modeling and Optimization of Complex Service Delivery Systems.
3: Organizational Models for Service Delivery.
4: Optimization of Service Development Strategy in a Global Environment.
5: Improving Application Management Services through Ticket Data Clustering.
6: Service Delivery Resource Management using a Socially Enhanced Resource Model.
Operations Management: Optimizations of Service Operations - Incident, Problem, and Change Management.
7: Tuning up IT Services using Monitoring Configuration Analytics.
8: Using Visual Analytics to Diagnose Productivity and Quality Issues on IT Service Pools.
9: Optimization Model for IT Change Management.
10: Using Machine Learning and Probabilistic Frameworks to Enhance Incident and Problem Management: Automated Ticket Classification and Structuring.
Process Management: Optimization of Process Management using Innovative, IT Services-Specific Models.
11: A Mashup-Based Approach to Optimize Human Performance in IT Service Management.
12: A Service-Oriented Algebra for Optimizing the Management of Service Requests.
13: Predictive Analytics for Business Processes in Service Management.
14: Optimizing Cloud Storage Management Services.
Compilation of References.
About the Contributors.
Index.
Front Cover.
Title Page.
Copyright Page.
Advances in Logistics, Operations, and Management Science (ALOMS) Book Series.
Titles in This Series.
Table of Contents.
Detailed Table of Contents.
Foreword.
Preface.
Resource Management: Optimal Management of Human Resources and Skills for Balanced Costs and SLA Attainment.
1: Capacity Planning and Management of IT Incident Management Services based on Queuing Models.
2: Modeling and Optimization of Complex Service Delivery Systems.
3: Organizational Models for Service Delivery.
4: Optimization of Service Development Strategy in a Global Environment.
5: Improving Application Management Services through Ticket Data Clustering.
6: Service Delivery Resource Management using a Socially Enhanced Resource Model.
Operations Management: Optimizations of Service Operations - Incident, Problem, and Change Management.
7: Tuning up IT Services using Monitoring Configuration Analytics.
8: Using Visual Analytics to Diagnose Productivity and Quality Issues on IT Service Pools.
9: Optimization Model for IT Change Management.
10: Using Machine Learning and Probabilistic Frameworks to Enhance Incident and Problem Management: Automated Ticket Classification and Structuring.
Process Management: Optimization of Process Management using Innovative, IT Services-Specific Models.
11: A Mashup-Based Approach to Optimize Human Performance in IT Service Management.
12: A Service-Oriented Algebra for Optimizing the Management of Service Requests.
13: Predictive Analytics for Business Processes in Service Management.
14: Optimizing Cloud Storage Management Services.
Compilation of References.
About the Contributors.
Index.