Do you still conduct exit interviews holding a pen and paper? If so, it may be time for a change. There are several powerful technologies you could use to elevate those one-on-one meetings. Whether you opt for artificial intelligence or the latest software, you can gather deeper insights into departing employees.

The Importance of Conducting Exit Interviews

Exit interviews give you a glimpse into staff’s professional lives and personal opinions, revealing insights you may have never acquired otherwise. They help you restrategize to mitigate turnover and improve your retention rates. By all accounts, they are a fundamental part of offboarding.

However, despite being a long-standing staple in most industries, exit interviews remain largely ineffective. Research suggests they have not typically elicited valuable feedback from departing workers. Instead, they mainly serve to leave a good impression, reducing individuals’ willingness to complain about their soon-to-be-former employer.

Why is this? Tessa West — a professor of psychology at New York University — states most are not genuine in their exit interviews. West clarifies that a “strong norm against clear, honest and critical” responses exists in “most organizations.” According to her, “the default isn’t honest feedback.” Even if you believe the workers at your company are candid, other issues may exist.

Sitting down with human resources (HR) can make people nervous, regardless of their time with the firm. Even with one foot out of the door, they may be hesitant to share their honest opinions with you. When asked generic questions about their experiences, people tend to give half-truths for fear of burning bridges, especially if a higher-up they had friction with is present.

Incorporating Technology Into Exit Interviews

How can you convince employees to participate in your exit interviews? Take advantage of the digital age — your organization’s team members are likely familiar and comfortable with surveys, apps, and chatbots, which can give you the upper hand.

Survey Software

Your response rate is among the most effective criteria for measuring exit interview success. If most employees participate, your business likely has a diplomatic, accessible process. In contrast, a low response rate suggests people are intimidated or historically find the interview unproductive.

You can leverage software to encourage participation — it can automatically send an exit survey via email at a predetermined time. Sometimes, questionnaires are better than face-to-face meetings. Employees may feel more inclined to share their experiences and go into more detail if they have time to process their thoughts.

Digital Asset Management

Digital asset management is defined as a software solution for storing, organizing, and sharing digital files, processes and platforms across your entire organization. Done right, it can lead to massive efficiency gains and generate actionable insights. These systems provide one secure, centralized location for storing all interview data, making it easy for HR professionals to grab and sort interview data for deeper and more meaningful insights.

Most platforms also come equipped with reporting features, which can help better visualize data, as well as collaborative tools to allow HR professionals to easily share the insights gathered with relevant stakeholders.

Big Data

If you have not already collected and analyzed exit interview responses, you should. With big data, you can build a rich feedback repository, which makes measuring cause and effect easier. This way, you can determine whether your refined strategies resolve commonly raised concerns and complaints.

Automation Technologies

Have you ever struggled to find time to conduct an exit interview? When work piles up, meeting with a departing staff member can be challenging. With automation, you will not experience this problem again. Various software can automatically schedule meetings, summarize responses or generate interview questions.

AI’s Role in Interviewing Departing Employees

In regards to technology, AI is in a league of its own. You will gain unique automation and analytics opportunities if your enterprise deploys a pretrained machine learning, deep learning or large language model (LLM).

Predictive Analytics

The cost of replacing a departing individual with a new candidate is high. According to the Society for Human Resource Management, you will spend around $5,000 per hire on average. If you use AI to learn from your interviewees, you may be able to avoid this costly issue.

With predictive analytics, you can turn a departing worker’s responses into predictors. Each data point will aid in determining when and why others will leave, helping you quickly reduce turnover and improve retention.

Natural Language Processing

Natural language processing (NLP) is a subset of AI that enables algorithms to interpret text and speech. It could give you a massive advantage because it can conduct a real-time sentiment analysis. This way, you can determine the interviewee’s mood and truthfulness.

Alternatively, you can use NLP to transcribe and summarize speech, simplifying insight extraction. Afterward, you can extract key points from the meeting using plain language — no typing in commands or entering code required. Automating this process could save you some much-needed time if your workloads are consistently large.

Large Language Model

With a chatbot or an LLM, you can conduct exit interviews without being present. Anonymity and confidentiality may motivate employees to provide honest responses, ensuring the feedback you collect from the exit interviews is accurate and relevant.

Machine Learning

A machine learning model is capable of analyzing vast amounts of data in mere moments. If your organization has integrated AI into cameras or work computers, you can use this technology to extract granular insights about staff behavior and mood.

Alternatively, you can make the machine learning model review workplace surveys, performance reviews and exit interview answers. During its analysis, it will likely uncover hidden trends and patterns you never knew existed. This way, you can determine the accuracy and weight of the interviewee’s feedback.

Tips for Optimizing Exit Interview Technology

While integrating technology into your exit interview process can help you uncover valuable insights, how you approach implementation affects downstream outcomes. Optimization will lead to better results.

1.    Regularly Adjust Model Weights

Training data becomes less relevant over time as your staff, procedures and metrics change, making AI output less accurate. The solution is to feed new details to your algorithm continuously, adjusting the model weights so older information carries less significance.

2.    Continuously Clean Training Data

Cleaning a dataset involves removing outliers, transforming data points and filling in missing values. Your firm — namely the information technology department — must do this regularly to keep the AI accurate and free of bias.

3.    Balance Human and AI Involvement

Although incorporating technology into your exit interviews can reduce your workload and improve insight extraction, its presence may make some uncomfortable. They may feel it makes the process more impersonal or invasive. Show them you value their time and feedback by directing the one-on-one and brief them on the inclusion of technology beforehand.

4.    Incentivize Employees to Participate

How often do you actually respond to the comments, complaints and concerns departing workers raise? A high action rate shows former and current team members the HR department values their feedback, helping convince them to participate in exit interviews when the time comes.

Most people want to feel heard. In one survey, nine in 10 employees reported they are more likely to stay with an employer that collects and acts on feedback. Use the data your technology generates to prioritize actionable responses and determine the interview’s helpfulness.

Technology Shapes the Future of Exit Interviews

Manually writing down interviewees’ responses and perpetually storing the documents in a filing cabinet is a holdover from yesterday’s workplace. The future of exit interviews involves software, big data and machine learning models. Bring your HR department into the modern age by incorporating these solutions into your exit interview process.

This post was written for HRTech247 by Eleanor Hecks. Eleanor is a business and hiring writer and researcher who is passionate about sharing physical and mental health resources with the SMB community. You can find her work as Editor in Chief of Designerly Magazine as well as a staff writer for publications such as HR.com, eLearning Industry and Training Industry.