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

By: Publication details: Columbia: Independently published, 2020Description: 500ISBN:
  • 9781077226906
Subject(s): DDC classification:
  • 658.301 SHE
Summary: 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".
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Reference Book Reference Book Alliance School of Business 658.301 SHE (Browse shelf(Opens below)) Not for loan A27524
Book Book Alliance School of Business 658.301 SHE (Browse shelf(Opens below)) Checked out 08/01/2025 A27526
Book Book Alliance School of Business 658.301 SHE (Browse shelf(Opens below)) Available A27525
Total holds: 0

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".

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