Predictive HR Analytics, Text Mining & Organizational Network Analysis with Excel

Mong Shen Ng

ISBN 10: 107722690X / ISBN 13: 9781077226906

Published by Independently Published, 2019

About this Item

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Bibliographic Details

• Title: Predictive HR Analytics, Text Mining & Organizational Network Analysis with Excel
• Publisher: Independently Published
• Publication Date: 2019
• Language: English
• ISBN 10: 107722690X
• ISBN 13: 9781077226906
• Binding: Paperback / softback
• Condition: New

About this title

Synopsis

Predictive HR Analytics, Text Mining & Organizational Network Analysis (ONA) are hot topics and powerful techniques to improve organization effectiveness. Best Buy is able to predict that a 0.1% increase in employee engagement results in an increase of $100,000 in the store’s annual income! VoloMetrix found that a salesperson’s network size within their company is a more important leading indicator of sales, than the time salespeople spend with customers! You don't need to spend months learning R programming & you don't need to buy expensive SPSS statistical software. This is the only book that teaches you how to use Microsoft Excel for Predictive HR Analytics, Text Mining & Organizational Network Analysis (ONA) with step-by-step print-screen instructions:
1) Predictive HR Analytics: Use Excel’s Statistical Analysis tools (Decision trees, Correlation, Multiple & Logistic Regression) to run Predictive HR Analytics. You will learn how to predict Ethnic & Gender Diversity’s impact on EBIT, predict training’s impact on sales revenue, predict employee resignation, predict impact of staff engagement on sales, predict workplace accident, etc.
2) Organizational Network Analysis (ONA): Run ONA using Excel's network analysis tool. Learn how to convert an employee’s organizational network into a score & then predict if they will be a high-potential (HiPo). You will also learn how to predict employee performance and resignation with ONA graph metrics. E.g. an employee is predicted to be a HiPo with performance rating of “9”, if his “Social Network Score” is “16”, “Social Network Diversity Index” is “3” & “Competency Score” is “8”.
3) Text Mining, Sentiment Analysis & Word Clouds: Mine text from social network posts, employee engagement surveys & Glassdoor comments, then run Sentiment Analysis using Excel & visualize the insights with “Word Clouds”. Learn how to predict a company’s average employee attrition rate based on its sentiment. E.g. a company’s average employee attrition rate is predicted to be 8%, if unemployment rate is 3%, GDP growth is 2%, Glassdoor public sentiment rating is “5”, and engagement score is “7”.