December 3, 2020
How can you use AI to make sense of your employee feedback system ?
Despite our best efforts, employee feedback systems are mostly worthless.
Vast amounts of unstructured data are too complicated to go through. Surveys seldom capture the right words that employees want to say. Also, managers’ bias can lead them to cherry-picked data confirming their beliefs, despite only using a small portion of data to prove it.
The only true way to have a bias-free approach to employee feedback is through AI analysis. Text analytics AI can sort through vast amounts of data to find trends in your employees’ inputs.
To address how AI can improve your system, we are going through the following:
- What Are Different Forms Of Bias Which Can Affect Employee Feedback?
- How Are Surveys Inadequate For Gathering Data
- How AI Can Be Used To Improve Both Systems
Let's get started.
How Can Bias Affect The Employee Feedback System?
When humans make decisions, bias is almost always unavoidable. Influence can come from several different locations, but influence can be spread at any stage of the feedback process. Below are some different types of bias that can occur during the feedback process.
Managers want to see a good employee experience, but performance reviews for them can be incredibly stressful. Their managers would also agree, and they may be looking at strong numbers and expect the same results for the employee experience. Confirmation bias can, for instance, indicate that the manager's manager will always assume that their employee is the best and choose specific excerpts of employee feedback to support this.
Depending on who you ask, some leaders will have a different perspective on what constitutes useful data. Many leaders rely on their emotions to determine what data they like the most. As a result, selection bias tells them to select data based entirely on subjective results. This means that they are more likely to throw out data that they don't understand. With a little effort, this data could be understood by them. AI does the heavy lifting, taking this effort out of their hands.
People are more likely to take advice from relations of theirs during the decision making process. For some people, they may not be fully aware of this. Regardless, they are more likely to put stock into something that person X says over person Z because X is part of their bowling team, otherwise known as social bias. This also comes from racism, sexism, and classism. Artificial intelligence does not consider this unless it is specifically programmed to.
It is far easier for us to remember something we are familiar with. As a result, memory bias causes us to recall easier-to-remember topics. This is especially concerning during verbal feedback, where we may only remember the phrases that had an impact on us. Artificial intelligence operates based on large batches of historical data, meaning memory bias cannot not affect it.
While unstructured data gives the freedom for employees to express things in their own words, it is the readers of data that have the most problem with interpreting it.
As a result, you may be tempted to stick with simple survey data. In many ways, surveys can be a useful tool to gather quick segments of useful data. However, they can also have just as many issues.
The Problem With Using Employee Surveys
Employee surveys are the second most popular form of cheaply gathering a large amount of data. They are also the bane of corporate culture, as it is easy to fall back on surveys. However, these questions may not always reach the effectiveness we want them to be. Below are potential problems one can run into when using surveys.
The Question May Not Be Phrased In The Way An Employee Agrees With
Have you ever looked at a survey and thought that you would have phrased that question differently. Such is the case when writing these items, which may modify their answer as a result. While it is far simpler to read than large chunks of data, artificial intelligence gives you the opportunity of using the employee's own words for later use.
All Surveys Are Self-Selected
Nine times out of ten, your first response to a survey will be to throw it out. For a group of frustrated employees who haven't felt any real results, they may do the same thing.
No matter your best effort, a certain amount of employee engagement must be reached if you have a good survey. Given people's initial response to surveys, this makes them a difficult option.
Employees May Not Be Encouraged To Provide Honest Answers
If you have ever worked an "I just need a paycheck" sort of job, you know that your answer will be the bare minimum to get upper management off your back. If you are working to find issues with the employee experience, they may be feeling the same thing. Surveys do not always elicit positive answers.
While surveys are fine in many situations, their ability to gather useful data is often questionable. Often, surveys do not encourage people to participate in their workforce. If you give them the freedom to speak in their own words, they may be more encouraged. But sorting through that large chunk of unstructured data can be a headache. To address this, you need to consider AI.
How You Can Use AI To Improve The Employee Experience
These days you are expected to make tough decisions in an environment that demands an instant response. However, the dangers of being reactive in any business setting result in impulse-based decision-making, causing major issues.
Instead, Artificial Intelligence can be used to address the pain points of surveys while taking advantage of the freedom that comes with unstructured writing. This is done in a process known as opinion mining. Below, we will give you a few ways that AI can be used for your employee experience.
AI Can Look For Trends In Historical Data
Imagine being able to sort through several years worth of employee feedback data in a matter of minutes. With advanced AI features, you can locate performance reviews and employee satisfaction results with relative simplicity. Good AI can look for the most common words or phrases used, allowing you to use them to notice consistent issues.
AI Gives You A Good Way To Find The Voice Of The Employee
For the most part, the goal of questionnaires and surveys is pretty straightforward. That being said, employees may be less responsive to these questions if they are not asked from the employee's perspective. When looking for common words or phrases, AI can find which questions result in getting to the real meat of the problem, allowing you to create further discovery questions down the road.
AI Combines The Best Aspects Of Surveys And Freeform Questions
Surveys are best at finding individual pieces of data, but the answer bubbles don't really give a good picture of what the employee is really feeling. Freeform questions are great at digging into people's emotions, but employees tend to go off on their own tangent eventually. With an advanced AI scanning through your documents, they look for commonly used words and phrases to turn your freeform content into structured data.
Employee Engagement Will Increase
Employees who are asked freeform questions will need to really think about the details of their answers. It allows them to consider the biggest pain points for them, giving them time to address these issues. Freeform questions are far more engaging than surveys. Also, more engagement results in higher employee retention.
Employee feedback is a monstrous undertaking for HR. You can often feel like it is an overwhelming process that takes too much of your day. You can also feel like your constant surveying can lead nowhere, as it has done in the past.
By using modern technology, AI is paving the way forward to turn deep and passionate employee feedback into actionable results. While a wall of text may be overwhelming to us, it isn't overwhelming to a program that finds consistencies across unstructured data.
For questions about how AI can help you, feel free to book a demo. We would love to help you out.