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

The model

A causal model in which HR design levers and contextual conditions (compensation, training, diversity practices, network position, demographics, sentiment) influence psychological and behavioral states (engagement, job satisfaction, flight risk) that in turn drive organizational outcome metrics (attrition, performance, sales, EBIT, safety incidents). The analytics process itself (ARHAT framework + storytelling) is the meta-lever that surfaces these relationships.

A candidate measure

Predictive HR Analytics, Text Mining & Organizational Network Analysis_ with Excel — derived measurement candidates

The story

The reader An HR or people analytics professional who wants to deliver data-driven recommendations that improve business performance and establish credibility with executives.

Chapter by chapter

1. ch01Chapter 1

   This chapter introduces the fundamentals of predictive HR analytics, emphasizing its significant impact on organizational effectiveness through practical tools like Excel.

2. ch02Chapter 2

   This chapter delineates different types of machine learning — supervised, unsupervised, and reinforcement learning — and explores their practical applications, challenges, and analytical maturity, particularly within the realm of HR analytics.

3. ch03Chapter 3

   This chapter articulates the critical nature of implementing a structured predictive analytics framework in HR to address varied organizational challenges effectively.

4. ch04Chapter 4

   This chapter emphasizes the importance of clear, engaging visual communication in presentations, offering strategies to enhance viewer understanding and retention.

5. ch05Chapter 5

   This chapter explores the principles and applications of statistical analysis, highlighting the importance of visualizing data relationships to make informed decisions.

6. ch06Chapter 6

   This chapter delves into the practical application of regression analysis in Excel, providing detailed guidance on using the software for both multiple linear regression and logistic regression to derive insights from data.

7. ch07Chapter 7

   This chapter explores the profound impact of sentiment analysis on employer branding, employee selection, and retention, arguing that understanding and analyzing employee sentiment can lead to significant improvements in workforce engagement and company performance.

   • A one-star increase in Glassdoor ratings leads to a statistically significant increase in the likelihood of employee retention.
   • Companies with poor employer brands often overpay salaries by 10% due to weaker attractiveness to potential hires.
   • Engaged employees are significantly less likely to resign, with studies showing an 87% drop in resignation rates among highly engaged staff.
   • Concrete steps in sentiment analysis can lead to actionable changes that improve employee satisfaction and retention metrics.

8. ch08Chapter 8

   This chapter explores the Employee Net Promoter Score (eNPS) as a pivotal metric for measuring employee engagement and morale, alongside the transformative impact of flexible work arrangements on organizational productivity.

9. ch09Chapter 9

   This chapter explores how Organizational Network Analysis (ONA) can be leveraged to improve employee retention, optimize team performance, and enhance decision-making processes within organizations.

   • Organizational Network Analysis (ONA) provides deeper insights into employee connections than traditional metrics.
   • Employees who are well-connected exhibit greater loyalty and are less likely to leave the organization.
   • Strong, quality connections within an organization are more valuable than sheer quantity, as excessive networking can hinder performance.
   • Understanding informal relational dynamics is critical for effective onboarding, retention, and performance improvement strategies.

10. ch10Chapter 10

    This chapter provides a detailed guide on utilizing logistic regression and multiple regression analysis to predict employee behaviors, specifically their likelihood to resign and impact on sales, using Excel as the primary tool for calculation.

11. ch11Chapter 11

    Chapter 11 details the analytical processes required to assess employee diversity through data and its correlation with performance, focusing on techniques such as the Simpson’s Diversity Index and regression analysis in Excel.

    • Raw diversity metrics are insufficient; organizations must transition to quantitative diversity indices for a nuanced understanding.
    • The Social Network Diversity Index, derived from the Simpson's Diversity Index, provides a more comprehensive view of diversity in workplace contexts.
    • High R Square values from regression analyses indicate strong correlations between diversity indices and employee performance ratings.
    • Statistical significance in findings (e.g., P-values under 0.05) is essential for relying on analytics in decision-making.

12. ch12Chapter 12

    This chapter explores the application of predictive analytics in human resources, detailing how organizations can leverage data to predict employee turnover and enhance performance metrics.

13. ch13Chapter 13

    This chapter examines the intricate relationships between personality traits, employee performance, and organizational profitability, emphasizing how strategic hiring and internal networking can mitigate turnover and bolster productivity.

14. ch14Chapter 14

    The chapter examines the critical role of compensation and benefits in employee satisfaction and retention, illustrating how organizations can enhance performance and reduce turnover by strategically investing in their workforce.

    • 80% of American workers prefer benefits over higher salaries, emphasizing the importance of a comprehensive benefits package in recruitment and retention.
    • Walmart’s pay increase led to a significant recovery in sales and customer service metrics, demonstrating the tangible benefits of investing in employees.
    • Research shows that a connection with team members is often more crucial to job satisfaction than direct supervision or salary.
    • The strategic use of Market-Ratio and Compa-Ratio Analytics can help organizations maintain fairness in compensation and drive retention.

15. ch15Chapter 15

    This chapter demonstrates how to perform multiple linear regression analysis in Excel to evaluate the impact of training programs on customer service ratings, offering a step-by-step guide for working professionals.

16. ch16Chapter 16

    This chapter delves into a comprehensive guide on creating various types of charts in Excel, emphasizing their applications in data analysis, visualization, and effective presentation.