HRM Data Analytics Assignment

With the ever increasing array of software solutions being implemented and rolled out across organisations, and in particular within human resources, the challenge has become one of how to deal with and understand the vastness of the data that has been captured and the information that can be leveraged from this data. In this regard, the use of data analytical techniques has allowed organisations to manage and understand their data and more specifically has allowed organisations to distil this data into meaningful information as a way to support their decision making processes.
This project should consider the concepts covered and tools used within the module Analytics for HRM and the student should produce a technical report that summarises and analyses a fictitious data set within the context of HRM. The data set comprises the records of approximately 1800 employees and records data on: gender, age, length of service, educational attainment, salary, and sick leave taken; to mention a few.
The report should contain results that describe variables of interest through appropriate graphical techniques as well as their usual numerical measures of centre and dispersion. The report should attempt to identify relationships between variables as well as identifying similarities and differences across specific groups of interest. More importantly, the report should be framed within the context of literature that deals with subset of the variables provided.
For example, the report could focus on gender inequality as manifested through the salary differences of females compared to males and possibly considering level of education as a variable that explains the presence or absence in differences. The report could consider the relationship between overtime completed and the levels of sick leave taken by employees, and possibly exploring if these relationships are present across age categories and length of service accrued by employees. As mentioned previously, the analysis should be framed within the context of literature and the results and their analysis either supporting or contradicting the views expressed within the literature.
The technical report should include a title immediately followed by the authors name and also include the following section headings: Abstract; Key Words; Introduction; Methodology; Results and Analysis; Conclusion and Bibliography. With the exception of the abstract, all main body narrative within the report should be typeset using a Calibri font of size 12 and be formatted with space-and-a-half line spacing, all narrative should be justified.

The Abstract should be typeset using a Calibri font of size 10 with single line spacing justified. Tables, figures and equations should be captioned as such and include a brief synopsis typeset using Calibri font size 11. Each table and figure should be introduced so that the reader can easily understand their structure and purpose; this typically can be done in the results section. All tables, figures, and equations should be page centred. Tables should be inserted as images, png format preferable; all figures having absolute height dimensions of 5.35cm. Each section, with the exception of the introduction, should contain a brief introduction of what will be presented in the section and finish with what will be presented in the immediately following section. The only section headings to be those indicating: Abstract; Key Words; Introduction; Methodology; Results and Analysis; Conclusion; and Bibliography; no sub-section headings. All section headings should be typeset using a bold Calibri font size 12. The report title should be typeset using a bold Calibri font size 14. Marks will be allocated for conformity to this structure.

Abstract:

The increase in the level of sick leave taken within the public sector is a phenomena that has been extensively reviewed and reported within the literature. In addition, the effect that availability of overtime has on increased sick leave taken has also been noted. This paper explores, from a statistical perspective, this relationship and more importantly examines if there exist differences in levels of sick leave taken based on gender as well as exploring the accessibility of overtime for female employees. The paper presents a number of graphical representations of these relationships and also a numerical characterisation of the same. Our results show a positive association between levels of sick leave taken and the amount of overtime completed by an employee. In particular, our results would indicate the presence of a negative association within this organisation; with increased participation in overtime reducing the level of sick leave taken by employees. Our results also show significant differences when a gender based analysis is undertaken.

Introduction:

The increase in the level of sick leave taken within the public sector is a phenomena that has been extensively reviewed and reported within the literature [Camp et.al.] In addition the effect that availability of overtime has on increasing the number of days sick taken by employees has been
The literature review...

Methodology:

In this section we present an overview of the approach taken to the statistical analysis that follows....

Results and Analysis:

In this section we present the results of our analysis of two portfolios. We first present a number of graphical descriptive representations of the data under consideration, in particular the gender distributions of employees, their length of service, highest level of qualifications across the workforce, and finally the levels of sick leave taken by different categories of employee. In addition, we present an overview of how gender in particular and age have influenced remuneration levels. Finally we present the results of a regression analysis between sick leave taken and the number of hours overtime completed by employees.
Figure 1 and 2 below provide an overview of the gender makeup of the organisation. In each case the horizontal axis depicts the gender with the vertical axis representing the number of employees, or percentage of employees of a specific gender. Of note is the larger number of male employees compared to female, in particular approximately 60% males and 40?males. This gender difference is as would be expected considering the industry is heavily focused in manufacturing. With respect to the age profile of the workforce, Figure 3 depicts the distribution of employees based on their age. Of note is the relative positive skew that the distribution exhibits, indicating a relatively young workforce.

Table 1 depicts the age profile of the workforce in greater detail, showing the frequency, percentage and cumulative percentage of employees based on age. The age distribution of the workforce would indicate that 20 to 30 year olds make up the largest age group, representing more than 3 time the number of employees compared to 50 to 60 year olds, or employees older than 60 years.

...ditto

Table 1: Breakdown of Employees based on their Age

A scatter plot of the relationship between the amount of overtime that employee has completed and their levels of absenteeism is depicted in Figure 4. The horizontal axis representing the number of hours of overtime completed and the vertical axis representing the number of days sick leave taken. Of note is the negative slope of a best fit regression line, indicating a negative association between both. This would seem to contradict the literature which seem to suggest that increased participation in overtime has a detrimental affect with regard to sick leave taken. In particular the literature would suggest that employees who avail of overtime are more likely to be sick.

This is association is further verified the Pearson correlation coefficient, a correlation coefficient of -0.399 was observed, as detailed in Table 2. This correlation would indicate the presence of a moderate association between sick leave taken and overtime completed.

A further examination of the levels of sick leave taken by employees, grouped by gender, is presented in Figure 5 and 6. Of note is the greater number of females who have taken no sick leave compared to their male counterparts, as shown by the histogram bar centred on zero.

Also of note is the modal level of sick leave taken by males and females, as depicted in Figure 5 and 6 by the highest histogram bar, with males taken 6 days compared to females of 3 days.

A more detailed breakdown of is presented in Table 3. These results showing that on average males take 8.44 sick days compared to 3.94 for females. In addition, Table 3 shows that the completion of overtime seems to be the same for males and females, averaging 1.25 hours for males and 1.54 hours for females.

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