DECISION SUPPORT MODELS IN SUPPORTING WORKFORCE FORECASTING

Sanjay Shukla

ISBN 10: 3844315128 / ISBN 13: 9783844315127

Published by LAP LAMBERT Academic Publishing Mär 2011, 2011

About this Item

Neuware -For any organization, the effective workforce planning is essential to stay competitive and continue to subsist. Workforce planning is an organized process for identifying the number of employees, their mix and the types of skill sets required to accomplish an organization''s strategic goals and objectives. This book focuses on demand analysis (i.e. forecasting the future workforce demand) in workforce planning. Workforce demand forecasting techniques can be classified into two broad categories viz. qualitative and quantitative. Generally, quantitative techniques are used to forecast workforce size and mix, whereas, qualitative techniques forecast competency requirements. This research explores demand analysis in many folds. First, state-of-the-art of workforce analysis techniques are presented and synthesized into a scenario specific forecasting technique(s) selection tree. Afterwards, the Clonal C-fuzzy Decision Tree (C2FDT), a decision support model, is proposed to forecast future workforce demand. C2FDT inherits its properties from fuzzy c-mean clustering and clonal algorithm.Books on Demand GmbH, Überseering 33, 22297 Hamburg 84 pp. Englisch.

Seller Inventory # 9783844315127

Bibliographic Details

• Title: DECISION SUPPORT MODELS IN SUPPORTING WORKFORCE FORECASTING
• Publisher: LAP LAMBERT Academic Publishing Mär 2011
• Publication Date: 2011
• Language: English
• ISBN 10: 3844315128
• ISBN 13: 9783844315127
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

For any organization, the effective workforce planning is essential to stay competitive and continue to subsist. Workforce planning is an organized process for identifying the number of employees, their mix and the types of skill sets required to accomplish an organization's strategic goals and objectives. This book focuses on demand analysis (i.e. forecasting the future workforce demand) in workforce planning. Workforce demand forecasting techniques can be classified into two broad categories viz. qualitative and quantitative. Generally, quantitative techniques are used to forecast workforce size and mix, whereas, qualitative techniques forecast competency requirements. This research explores demand analysis in many folds. First, state-of-the-art of workforce analysis techniques are presented and synthesized into a scenario specific forecasting technique(s) selection tree. Afterwards, the Clonal C-fuzzy Decision Tree (C2FDT), a decision support model, is proposed to forecast future workforce demand. C2FDT inherits its properties from fuzzy c-mean clustering and clonal algorithm.

About the Author

Sanjay Kumar Shukla is working with Evalueserve, India as a Senior Analyst in Data Analytics. He received his M.S. degree in Advanced Manufacturing and Enterprise Engineering from the University of Texas at San Antonio,San Antonio, USA. His research interest include Statistical Modeling of manufacturing and service systems, Artificial Intelligence.