The Exit Interview Data Analysis Process in 7 Steps

Exit interview data analysis is the key to making the most of your exit interview process. The data behind why employees leave can help you better grasp what’s affecting your organization’s turnover and what you can do about it. 

Contents
What is an exit interview? 
Why conduct an exit interview?
The exit interview data analysis process

What is an exit interview? 

An exit interview is a one-on-one conversation with a departing employee to seek feedback about their experience with the organization. A neutral third party should conduct the interview, so it’s typically an HR representative. They present a set of specific, uniform questions to every employee who is separating from employment. 

This final stage of an employee’s journey provides closure and allows them to be heard in a setting where they can express themselves candidly. Their opinions and suggestions provide insight into the circumstances surrounding their departure and how the organization is viewed through the employee’s eyes. It’s a way to learn what may have gone wrong and whether something can be done to prevent similar occurrences in the future.

This information can help you identify the root causes of turnover and other problem areas. Then you can address them to improve the work environment and employee satisfaction.

Why conduct an exit interview?

The benefits of exit interviews make them a standard procedure for employers of all sizes. An exit interview is a valuable tool for many reasons, including:

• Gaining a better understanding of why people leave.
• Offering employees the opportunity to have a voice.
• Collecting data that can improve organizational effectiveness and boost employee retention.
• Being able to hold managers accountable when needed.
• Discovering whether any illegal or unethical practices are taking place.
• Providing former employees with a positive final impression of the organization to champion your employer brand.

The importance of offboarding

Just as onboarding starts new hires with pertinent information and walks them through essential procedures, offboarding is necessary to appropriately wrap up the employee life cycle appropriately. Offboarding covers all the required tasks, paperwork, and legal requirements while also ending the employment relationship on good terms.

Departing employees get their last impression of the company during offboarding. They can leave as either a resentful adversary or an advocate who speaks highly of the organization. No matter what led to their exit, offboarding can send them on their way with respect and professionalism. 

Exit interviews are a crucial part of offboarding and should be conducted when employees leave under all circumstances, i.e., resignation, employment or contract termination, lay-off, or retirement. They allow employees to be heard and clear up misunderstandings. Exit interviews also provide HR with information that it wouldn’t otherwise obtain about why employees leave.  

The exit interview data analysis process

To make the most of exit interviews, you need to analyze the data that’s gathered from them. This is how you translate feedback from employees into useful information. Then you can draw from it to make changes and improvements. 

Here is an overview of the 7 steps involved in conducting a data analysis with your exit interview data:

1. Define the problem

The first step in the process of analyzing exit interview data is to know what you’re trying to accomplish. You’ll need to collaborate with management and other stakeholders to understand what the business need is. What problem do you want the data to help you solve? 

Outline the objective by formulating a problem statement, for instance:

• Top employees aren’t being retained.
• People are consistently quitting a specific position or department.
• Younger workers leave once they reach a certain point of employment.

Then you turn the problem statement into a question that you want the data to answer. An example could be, “How do we retain top talent?” Then take it a step further to make it as specific as possible, “How do we retain top talent in team leader positions?” 

Next, you can determine the desired outcome that will benefit the company. It might be, “Retaining top talent in team leader positions will maintain productivity and provide a pool of potential candidates for higher level management.”

2. Determine what exit interview data will be collected

Once you know what you’re looking for, you need to decide which data you’ll need and how to collect it. The two types of data to consider are qualitative and quantitative. Let’s take a look at these.

Qualitative data:

Qualitative data express subjective and interpretive qualities that can’t be measured numerically but can be observed, recorded, and categorized. This type of data approximates and characterizes something.

This data type is collected from formats such as surveys, questionnaires, and interviews with open-ended questions. It defines a trait and expresses it without numbers.

Examples of qualitative data from exit interviews could be: 

• The work environment is inclusive but demanding.
• The organizational culture promotes collaboration and innovation.

Quantitative data: 

Quantitative data are expressed in numbers and can be verified and validated, allowing you to determine how much, how many, and how often. This type of data can be gathered during exit interviews by offering a numerical ranking for responses.

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As an example, the exit interview quantitative data could be:

• 65% of departing employees rate the company 3 out of 5 overall as an employer.
• 25% of departing employees rank their managers below 4 out of 5 for impartiality.

3. Collect the exit interview data 

Now that you have a data strategy, you’ll need to design the exit interview process to collect the necessary information. Here is an overview of what this entails:

Establish functions:

In addition to solving a specific business problem, exit interviews serve other purposes, which include the following: 

• Formally finalizing the employment relationship.
• Seeing a snapshot of the employee experience and overall perception of company culture.
• Identifying both what’s working and where the problem areas are. 
• Learning whether the former employee will promote the organization in the future.

Develop effective exit interview survey/questions:

Asking the right type of questions will provide better results. Using an exit interview template can help you maintain uniformity. Be sure that the questions are:

• Worded in a non-judgmental way to encourage honest answers.
• Standardized to obtain consistent data.
• Posed with adequate time to respond.
• Able to prompt some open-ended replies to acquire more detail.

It’s helpful to focus the questions on evaluating certain job components. We have created a comprehensive list of the types of questions to ask. 

Here is a summary of the five categories and a sample question for each one:

1. The employee: “Explain the circumstances that prompted you to look for another job.”
2. The job: “Did the job match your expectations from when you were first hired?
3. The company culture: “How would you define our company culture?”
4. The work environment: “What did you like best about coming to work?”
5. The resources/technology: “Did you have the tools you needed to do your best in the role?”

Conduct the exit interview:

Along with the right questions, there are some administrative logistics for conducting a successful exit interview. Here are a few tips:

• Schedule the interview as close to the person’s departure as possible. If they have one foot out the door, they’ll feel more comfortable being open and sincere.
• Use automated systems to streamline data collection and analysis.
• Be mindful that certain questions may evoke an emotional response, especially when an employee is let go. 
• Assure confidentiality about what they share and show appreciation for their input.

4. Clean the exit interview data 

Before you start analyzing the exit interview data, you must ensure it’s reliable. When data is compiled from multiple sources, duplication and mislabeling can occur. “Clean” data will be complete, consistent, and accurate. “Dirty” data reflect errors and inconsistencies. Putting effort into erroneous data will waste your time and impede the results. 

Data cleaning or scrubbing is recognizing and correcting faults in the raw data. You can perform the following data cleaning tasks to preserve the data quality: 

• Extract irrelevant data points that don’t contribute to the analysis.
• Identify duplicates and remove outliers and significant errors.
• Unify the data by organizing the layout and fixing typos. 
• Look for any missing values and fill in the blanks.

We have developed an in-depth guide on what Excel tools and functions can assist you in cleaning your data in Excel.

Some of these include: 

• How to remove duplicates
• Sorting data
• Converting data (Using the VALUE and TEXT functions).

5. Analyze the data  

Now it’s time to analyze the exit interview data and glean some insight. Individually exit interviews may not be a rich source of data, but collectively they will reveal certain trends and patterns. 

You’ll need to determine what tools to use in analyzing the data. Your talent management or HR software probably has some type of offboarding component, but it may not be detailed enough. Various technology solutions specifically exist for exit interview data, but Excel is also a powerful and readily available tool.

Our in-depth guide on Excel tools and functions also presents several tools you can use to help you analyze your data. These include: 

• Using Slicers and Filters
• PivotTables

Your approach to data analysis will depend on what you need the data to tell you. Our article on types of HR analytics can give you more comprehensive information, but data analytics generally fall under one of the following four categories:

1. Descriptive analysis: Summarizes data and describes what has taken place. (Example: The number of employees that have left the organization in one year.)
2. Diagnostic analytics: Identifies why something has happened.  (Example: Finding the most commonly disclosed reason that people resign.)
3. Predictive analysis: Formulates future trends by making models from historical data. (Example: Forecasting employee turnover for the following year.)
4. Prescriptive analysis: Applies past and present data to make recommendations for future decisions. (Example: Identifying areas of employee engagement that need action to prevent turnover.)

There are multiple metrics you can track that will reveal trends in your exit interview data, including the following:

• Employee turnover rate: The number of employees who have left compared to the average number of employees. You may want to break this down into voluntary and involuntary turnover.
• Retention rate: The number of employees who are employed after subtracting those who have departed over a set period.
• Retention rate per manager: The number of resignations per department/manager as a percentage of all resignations.
• Retention rate of top/low performers: The number of top or low performers who stay with the company for a defined period compared to the total number of employees at the start of that time.
• Exit interview completion rate – The number of completed exit interviews compared to the number offered.

6. Share insights with stakeholders

Interpreting your findings and making conclusions is the culmination of data analysis. You’ll need to produce a report and present it to stakeholders. It should explain the exit interview process, which data you collected, and some ideas for what needs to be addressed. You should also be prepared to make suggestions for how to take action.

For optimal impact, the report should contain data visualization techniques. Presenting the data in an illustrative form provides stakeholders with a more tangible way to grasp the information. Diagrams, graphs, pie charts, colors, shapes, etc., all put the numbers into a picture that non-technical people can see and comprehend better. 

It’s also important to tailor the information you present according to your audience’s needs. Focusing on what certain stakeholders are most interested in will give your findings and insights more credibility.  

7. Determine actions to be taken

Once you’ve gathered and analyzed the useful exit interview data, it’s time to transfer the insights into solutions. You should be able to identify the matters that require attention and make data-driven decisions to set your next steps.

You can leverage exit study data to change policies and practices that will improve your employee turnover and retention rates. When you know the main reasons employees are leaving, you can examine how different aspects of the employee experience contribute to this.

Here are several business practices you may want to examine for potential weaknesses:

• Recruiting/hiring strategies
• Job training/staff development
• Onboarding
• Targeted manager coaching/training
• Mentor program implementation
• Work-life balance issues
• Compensation and benefits package

To conclude

Exit interviews give employees the proper send-off and provide beneficial information. The data from these straightforward evaluations of the company’s culture and work environment can expose underlying issues that may be contributing to low employee satisfaction. Armed with this evidence, HR can offer strategic solutions that make a difference in curbing unwanted attrition and retaining top talent.