HR AnalysisApril 4, 2014

MBP

Professor Judson

Glenice Booker-Butler, Mark Dominik, Tammi Dorion & Fred Paul

Team Shenanigans

Glenice Booker-Butler

Mark DominikTammi DorionFred Paul

Table of Contents

1. Executive Summary

2. Problem Statement

3. Purpose Statement & Research Question

4. Business Case

5. Variables Analyzed

6. Methods

7. Demographics

8. Hypothesis

9. Analysis & Results

10.Conclusions

Executive Summary The analysis of key demographic information

is important to the new executive team in order to understand if any policies need immediate review. This study will provide the following:

General overview of company demographics Significance between key factors Statistical analysis for determination of

potential bias Descriptions of analysis methods utilized Ethical considerations

Problem Statement

Problem: The new executive team wants to better understand the critical issues related to demographics and processes such as compensation and job grade.

Purpose & Research Question

Statement of Purpose:

The purpose of this presentation is to outline key HR statistical data for the new executive team to understand if the various demographics affect salary.

Research Question:

Which demographic(s) within the company most affects the salary of the employees?

Business Case

Close in-depth look into demographics

Benefits of analysis

Forward looking…

Variables Analyzed

Gender Cultural Identity Age Grade Effectiveness Years of Education Years of Experience Company Experience ESL

Methods

Demographics Scatter Plot Correlations Regression Analysis Voice of the data – ethical

considerations

AA = 36%$79,512.17

H = 37%$76,016.11

E = 27%$80,612.93

F = 53%$73,939.53

M = 47%$83,673.19

ESL N = 47%$82,330.30

ESL Y = 53%$75,130.32

Basic Hypothesis: There is no relationship between the independent variables (1-8) and the dependent variable salary.

Independent Variables

1. Gender

2. Cultural Identity

3. Age

4. Effectiveness

5. Years of Education

6. Years of Experience

7. Company Experience

8. ESL

Dependent Variable Salary

Hypothesis

Variables Related to Salary

Correlations – Pearson’s

Correlations – Kendall Tau’s

Multi Regression Independent Variables Age Grade Effectiveness Years of Education Years of Experience Company Experience Satisfaction with company Gender Cultural Identity ESL

Multiple Regression – All Variables

Gender and ESL are the only statistically significant variables.

R-Square – All Variables

22.9% of the variation within salary.

R-Square – ESL & Gender

14.7% of the variation within salary.

R-Square - Gender

10.2% of the variation within salary.

Salary & Job Grade Analysis

Job “grade” is not statistically significant, nor is it predictive of an individual’s salary.

Job grade is directly correlated with “Age”.

Conclusions

ESL and gender are the demographics that are statistically significant related to salary.

No strong predictive model for salary.

Grade of individuals is based on age of employees.

Overall determination of why differences exist would need to be investigated further.