Attrition Predictor Analysis

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Allison Horton
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1 Delivering Public Service for the Future Attrition Predictor Analysis Overview

2 Attrition Predictor What to Do, What to Say (WTD, WTS) Background The Attrition Predictor enables proactive attrition management by identifying factors that influence employee engagement. Predicting attrition helps an organization to plan specific interventions required to manage and plan for changes in the workforce. The Attrition Predictor uses logistic regression to segment and profile a workforce, along with time to event analysis to predict attrition rates and volume by segments over multiple time horizons, which provides actionable insights into drivers of attrition. Attrition is predicted based on the historic data available. Key Business Outcomes driven: (KPI) Identify different factors affecting attrition in an organization Analyze survey results to predict attrition Understand which employees are most likely to leave an organization Helps reduce the hiring cost Copyright 2017 Accenture All rights reserved. 2

4 Executive Overview

6 Employee Historic Attrition Tab: This tab gives the detailed information about the employee attrition based on various factors affecting it. Below are the details about each chart: 1. Employee Attrition donut chart: The donut chart shows the percentage and count of Employees who are likely to leave in red, and unlikely to leave in green. It can be used as a filter to slice data in other charts. 2. Retrienment in Public: The pie chart here shows the distribution of employees based on their overall experience. Vesting is the process by which employers make contributions to an employee's qualified retirement plan account or pension plan. 3. Monthly Trend Stack Bar: The stack bar shows the monthly trend of attrition out of total employees. The green part of the bar shows the total count of employee and the red shows the count of employee attrition. Using employee level data, the app can predict the count of attrition based on the past data trend. 4. Survey Response by Department and Classification Code & Survey Response by Department and by Occupational level: The Org structure have Departments and multiple Job roles overall. Each department have multiple job roles within and Each Job roles have different occupation level in it. The stack bar graph shows the count of employee at each job role by department and table below shows the count of employee in each occupation level in each department. Click on the red wedge of the employee attrition pie chart to know about the percentage of attrition in each job role by department in the stack bar and in each occupation level in the heat map. This gives an idea of which job role or which occupation level has the highest employee dissatisfaction and potential risk of attrition by department. 5. Survey response by Gender and Survey Response by Age: The chart below shows attrition percentage by gender, which will enable Departments to review any unusual or unexpected attrition by gender. The trend chart shows attrition by age. 6. Trend by different factors affecting attrition: The below trend graphs shows four factors affecting attrition and line shows the average monthly income.

8 Survey Analysis tab: This tab is based on the three employee surveys conducted by the federal government. The Attrition Predictor is based on a subset of the broader Government of Canada survey, and focused only on 18 Questions. The non-mandatory survey was conducted within 64 departments and 144 classification codes overall. The tab below shows the overall response by employee divided into positive, negative, neutral, NA and don t know based on the answers received. The responses can be further be sliced by each question, department, and classification code and at job levels. Below are the details about each chart: 1. Data Summary table: This is a small summary table that shows the overall count of survey questions, count of department and count of classification codes participated in the survey. The data in the table changes based on what is selected from the drop down filters. 2. Overall Employee Response: The pie chart below shows the percentage of total responses based on response received from the employee to the 18 in-scope survey questions. Click on each wedge to see the response by question, department and job roles. 3. Response prediction of Q61: Question 61 is the important question in that it predicts the attrition of Employees over the two years following the survey. Based on the average response received for the 17 other questions, the organization will know how many people intend to leave or stay for the next two years. 4. Overall Response by question: The stack bar shows the positive, negative and neutral response to each question by Employee overall. The more negative the response is for any question, the more people are dissatisfied. Select the department or occupation level to know the response for each question. (continued on next slide.) P.T.O

9 Survey Analysis tab (conti): 4. Overall Response by question: The stack bar shows the positive, negative and neutral response to each question by Employee overall. The more negative the response is for any question, the more people are dissatisfied. Select the department or occupation level to know the response for each question. KPI: High, Medium and Low flags for Q61. At overall and at department and occupation level. We can group the % response score in buckets to show attrition risk. Example: Response bucket variable: 38-40%, % and above 60% and attrition flag variable: low, medium and high. If Response % is between 38-40% then flag is low, if % then medium flag and above 60% response then high flag. (Note: this case is just for when you click on the red section of Q61.) Now when you click on each stack of Q61. Click on green, Survey Response by chart (bottom lhs) will show all green bars by department and by CC. As the employee in this section has responded positive to Q61 so attrition chances will be low. That means Attrition flag = Low. Click on purple, the below Survey Response by chart will show all purple by department and by CC. As the employee in this section has responded not sure to Q61 so attrition chances will be not sure. That means Attrition flag = Medium. Now when you click on red, the below Survey Response by chart will show all red by department and by CC. All the employees have responded Yes to Q61, means all department under this section will have attrition for sure. Now to see the impact of attrition within this High section, we divide the response % into 3 buckets. Response bucket as 38-40%, %, above 60%. Now Organization needs to pay immediate attentions to departments who get the response % above 60 as compared to departments which get response % between 38-40% and %. This High or Red section specially will have 3 more division unlike the above 2 (Low, Medium and High) based on the Response bucket created. P.T.O

10 Survey Analysis tab (conti): 5. Survey Response Trend: The trend lines below show the response for different years. It is possible to observe a response trend by selecting a particular question/questions or department. 6. Survey Response by Classification Code + Job Level +Department: The stack bar shows the response sentiment (+ve,-ve, neutral) by 2 views For each job level by Classification code within a department. For each Department within each Classification code. 7. The Heat Map of Departments and Classification Codes: The heat map shows the total percentage response overall by Classification code in different Departments, which makes it possible to identify the classification codes or job level with the most issues overall in most of the departments.

11 Overall Employee Satisfaction tab: This tab shows the overall employee response sentiment by Department, Job level and occupation levels within the job levels for each question. The data can be segmented by selecting any particular department, survey question, etc.

Attrition Prediction tab: This tab shows which of the in-scope survey questions have the greatest impact on attrition based on correlation with survey question 61.. 1.

13 Attrition Prediction tab: This tab shows which of the in-scope survey questions have the greatest impact on attrition based on correlation with survey question Factors affecting attrition: Each survey question is related to a particular theme / important area. The below chart highlights which survey questions have the highest impact for both the years (2011 and 2014) together. The charts identify the factors affecting, or which survey question, has the highest impact for individual years. 2. Relation between Q61 and Attrition: The below chart shows the correlation of responses between Q61 and other survey questions. For Example: Q61: Do you intend to leave your current position in the next 2 years? Survey Question: Q60: I would prefer to remain with my department or agency, even if a comparable job was available elsewhere in the federal public service. As can be seen below in the two charts as number of employees saying positively for survey question Q61, the number of employees saying they are going to leave current position will decrease by a magnitude of 33%. 3. Actuals vs Predicted by Department: Once the statistical model trained to capture previous year survey results and subsequent attrition trend it is possible to predict future attrition for upcoming time periods.

Aug 1 9:38 AM. 1. Be able to determine the appropriate display for categorical variables.

Aug 1 9:38 AM. 1. Be able to determine the appropriate display for categorical variables. Chapter 3 Displaying and Describing Categorical Data Objectives: Students will: 1. Be able to determine the appropriate display for categorical variables. 2. Be able to summarize the distribution of a