Multiplex_HR_Data_Analyst_Case_Study

Raphael Gall

This is a Data Analysis Presentation Exercise. 14th November 2017

Employee Attrition

This is a Data Analysis Presentation Exercise.

Carried out by Raphael Gall for the HR Data Analyst role at Multiplex in London, UK.

Task Overview

Research question

Research question: What can we learn about employee attrition at Multiplex in Q2 2017?

Why are employees leaving?

Who is leaving, what are their characteristics?

When, and after how long are employees leaving?

Executive summary

  1. Problem: The overall trend in attrition is that talent is leaving the company voluntarily. If this is a long-term trend, it is worrying for the overall competitiveness and thus health of the company.

  2. Trends and insights: Talent is generally on the upper end of performance and potential, job profile (job title, department, location) and timing (season, employment duration) play a role in attrition

  3. Predicitve analytics: We can predict which employees are likely to leave by building an attrition model and applying it to all employees. We can make this task more feasible by prioritising the most important employees. I suggest an easy measure to identify the most important employees.

  4. Recommendations: HR can optimise attrition by estimating all employees chance to leave by approaching talent proactively. We can predict which employees are likely to leave. A custom-built attrition model helps HR to employees at risk of attrition. prioritise these according to their performance, potential, profile, and timing.

Methodology + dataset

Preparation

  1. Consolidate data into single spread sheet in Excel.
  2. Clean the data (data types, typos, formatting, etc).
  3. Create a reference table for the new value variable employees.
  4. Calculate additional categorical and quantitative variables (e.g. unique identifier~ index, employment length, value scorecards).

Analysis

  1. The calculations of tables and and pivot charts and the early analysis are conducted in MS Excel.
  2. The visualisation is conducted in Excel and R.
  3. The presentation is in the reproducible R markdown format (PPT, PDF and HTML).

dataset

Who?
Terminated employees at Multiplex.

How many?
37 employees (N=37).

When?
April – June 2017, Q2.

Where?
Multiple locations across the UK.

Which profiles?
Various roles and job families.

1) Talent is leaving the company voluntarily.

  1. The overall trend in attrition is that talent is leaving the company voluntarily. If this is a long-term trend, it is worrying for the overall competitiveness and thus health of the company.

Why are employees leaving Multiplex?

Insight 1: Employees generally resign voluntarily.

1) Talent is leaving the company voluntarily (continued).

Why does this matter for the business?

Insight 2: A relatively high proportion of talent is leaving.

3) HR can optimise attrition and mitigate the risk by approaching talent proactively.

Sub-conclusion: We have learned which factors play a role in attrition. We can predict which employees are likely to leave in the future.

A simple Model to predict attrition has the following input: - Performance - Potential - Job position - job family - employment duration

Problem: Approaching all employees is not practical, as the total population is too big with 3-4 thousand. How do we identify the most important employees?

Performance and potential measure different aspects of a person.

Solution: We look at the top 1/3 of people first.

How? We create a single measure that is a combination of both performance and potential. It ranks employees into 9 levels, from 9 (‘star’) to 5 (‘normal’) to 1 (‘avoid’).

Concept schema 1 and 2:

Recommendation: A custom-build attrition model helps HR to identify employees at risk and prioritise these according to their value, profile, and the right time.

How to optimise attrition

Identify whom to contact with the Simple Attrition model (SAM)

  1. Value

  2. Job roles and titles to look. Job roles “beginning with senior” are of high value. Construction Manager with 3 counts, and 2 senior Planner with 2 counts. All with high value.
  1. Senior Quantity Surveyor
  2. Senior Planner iii.Senior Facade Manager
  3. Construction Manager
  1. Employment duration (employment duration and job roles interact, see observation 11).

When to approach:

Discussion