It Research Proposal – How Data Mining & Decision Tree Can Improve Personnel Selection and Human Capital

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Current Trends and Issues in IT-ITEC 6544

IT Research Proposal – How Data Mining & Decision tree can improve personnel selection and human capital

Professor. Prashant Gali

Presented by:

Kishor Kundaram

Abstract

In a technologically advance world human capital is still considered to be important and has its own competitive edge. This plays an important factor when there is a high turnover rate for employees. Traditional HR practices needs personnel selection approach to hire the right talent. This research will aim to fill the gap by constructing a framework for data mining based on decision tree. Thus, data mining techniques can useful in improving selection and improve human capital.

Brief Introduction

For any company, human capital is important factor, this can give the company an added advantage. if right people are hired the desired talent is acquired which can be beneficial for the company. There has been various research done on resumes, interviews, personality tests, etc. in HR to help them make better personnel selection of employees. Today work environment not only focuses on the primary job functions but they also focus on cross functional tasks and the static job responsibilities will not be sufficient. With new technological advancements in information technology, technologists have developed better decision support systems which help in better selection of talent to hire which have improved the outcomes of HR management

Background

The study focuses to develop a framework for personnel selection of employees which is developing a datamining framework. With the help of this framework we can determine the input quality of the employee. For this research proposal, I have chosen a semiconductor company to support their hiring decision for engineers and managers with different job functions.  The industry has different characteristics which are unique like manufacturing process, life cycle of the product, yield problems, etc. These companies have problems with regards to high turnover rate and difficulty hiring the right talent. They are unsure which employee will have the best productivity and performance and who will be staying for longer time working for the company which is quite important.

Methodology

For this research proposal, we will focus on the following methodologies to for better personnel selection of employees to hire the right talent which would be beneficial for the companies.

1: - Data mining: Data mining is defined as extraction of useful pattern or rules from a large database and analysing that data. This methodology has been developed for exploring purposes and discovering meaningful patterns. Data mining is categorized into

• Association: It is known as discovery of association that occur in a dataset.
• Clustering: Process of cutting down the data in groups to maximize the intra-class similarity and minimizing the inter-class similarity.
• Classification: Known as a function that is used to identify the class of an object based on its attributes.
• Prediction: A function that predicts future trends.
• This kind of approach has been applied to many industries such as marketing, finance, banking, health care, etc. But the application in HR management is quite unusual and rare.

2: - Decision Tree – Decision tree is a kind of data mining approach which is used for classification and prediction. This approach has its advantages such as easy understanding and interpretation for the decision makers and to justify their decision. Decision tree can also help us in analysing data different data without having to require assumptions about the distribution. As the name says decision tree, it is presented in a tree structure with leaves and stems. It is helpful in analysing various levels of factors. Each leaf can reveal the results of classification and the stem indicates the condition of the attributes.