DECISION SUPPORT MODELS IN SUPPORTING WORKFORCE FORECASTING
DECISION SUPPORT MODELS IN SUPPORTING WORKFORCE FORECASTING
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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 ...
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.
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