Instructions and guidance

Report based on the following scenario. The academic standards of grammar, spelling and referencing should be thoroughly observed.

This scenario is based on data collected from a hospital in the UK. A total of 285 employees were asked to fill in a questionnaire relating to their attitudes towards various aspects of their job and perceptions about their organisation. This data collected from employees was then matched to records that the hospital has on each individual employees performance appraisal ratings, sick days taken, job tenure and the gender of the employee.

You are a data analyst for an HR consultancy that has been contracted to help the hospital management to understand the potential reasons that can explain

(a) which employee attitudes are best predictors of sick absence and

(b) which employee attitudes are best predictors of employee performance. Your insights are aimed in helping the organisation review its current policies and practices with an aim to reduce sick absence and improve employee performance.

Drawing on this data source, you have been asked to prepare a report of 3,000 words addressing the following themes:

A short summary of the business problem that the analysis is designed to address.You are advised to draw on the theoretical and empirical literature that explores the links between employee attitudes, sickness absence and employee performance. (no more than 400 words)

An explanation of the data and how you are planning to use it, including statistical description of the measures you will use in your regression analysis. The use of descriptive statistics tables and visualisations (where and if appropriate) is recommended. (no more than 200 words, tables and visualisations do not contribute to the word limit)

Regression analysis: investigating relationships between the various employee attitude variables available to you in the dataset and the two outcomes of interest to the organisation, namely sickness absence and employee performance. Your discussion should start with the rationale for examining these variables (i.e. defining the dependent and independent variables), followed by a justification of the type of statistical analysis you have chosen to use and finally a discussion of the results. (no more than 1,100 words)

Analysis of what the results mean for the organisation; What actionable insight does the you have undertaken analysis produce? If the analysis does not produce any actionable insights, explain why. (no more than 800 words)

Suggestions for how to improve the analysis (e.g., through additional data collection or different methods). (no more than 300 words)

A short summary of overall value of the analytics project to this organisation. If you think the value is low, summarise the additional steps that could be taken to enhance value (no more than 200 words)

Outline of the variables that are included in the dataset including a description of how they are defined in the HR literature and how they are coded in the dataset:

Perceived Organisational Support (POS): is the degree to which employees believe their organisation values their contributions, cares about their well-being and fulfils socio-emotional needs.

Distributive Justice Perceptions (DistJust): this is fostered when rewards and outcomes are perceived to be consistent with implicit norms for allocation, such as equity or equality.

Procedural Justice Perceptions (ProcJust): this is fostered through voice during a decision-making process or influence over the outcome or by adherence to fair process criteria such as consistency, lack of bias, correctability, representation, accuracy and ethicality.

Job Satisfaction: this is defined as a pleasurable or positive emotional stating resulting from the appraisal of ones job or job experiences.

Value Fit: (or else person-organisation fit) refers to the compatibility between employee and their organisation. It can lead to increased levels of trust and a shared sense of corporate community.

Job Strain: this refers to a psychological response to a demanding work context and can be a consequence of having the perception of having little control over ones work, while facing high demands.

The variables in the Employee Performance Dataset are coded as follows:

ID (employee ID).

Gender (1 = female, 2 = male).

JobTenure (years with the organization as at December 2023)

POS2023 (perceived organizational support on a scale of 1= strongly disagree to 5= strongly agree as at December 2023).

DistJust2023 (distributive justice questions on a scale of 1= strongly disagree to 5=strongly agree as at December 2023).

ProcJust2023 (procedural justice questions on a scale of 1= strongly disagree to 5=strongly agree as at December 2023).

JOBSAT2023 (job satisfaction questions on a of 1= strongly disagree to 5=strongly agree as at December 2023).

ValueFit2023(person organization fit questions on a scale of 1= strongly disagree to 5=strongly agree as at December 2023).

JobStrain2023 (job strain questions on a scale of 1= strongly disagree to 5=strongly agree as at December 2023).

PerformanceRating2023 (performance rating given in December 2023 on a scale of 1 to 5, with 5 being the highest performance rating i.e. excellent performance).

SickDays2014 (total number of sick days taken in 2014)

Assessment rubric with weighted criteria

exceeds expectations very well by achieving equivalent of 70+,

exceeds expectations well by achieving equivalent of 60-69,

meets expectations by achieving equivalent of 50-59;

does not meet expectations at equivalent of 49 or less (PG)

Assessment rubric with weighted criteria

Report structure 10%

Main analysis 30%

Discussion of findings 40%

Critical reflection and recommendations 20%