AI for employee engagement [webinar]
AI is a true game-changer for employee engagement surveys, enabling even the largest of organisations to really listen to their people: in-depth, in real-time, and at scale.
In this webinar, we sit down with our Enterprise Account Executive and Product Manager to discuss our feature Listening AI, and how AI and NLP can enhance employee surveys and make it easier to build workplaces where people thrive.
AI is changing employee engagement surveys
Shino: My name is Shino Diabate, and I work at Eletive as an Enterprise Account Executive, hence I help the larger organisations with their people strategy. Tell us a little about yourself Patrik, who are you? Patrik: Firstly, welcome to everybody online joining us for this webinar where we're going to talk about Listening AI. My name is Patrik Thuring, and I'm a Product Manager at Eletive, which means that I work a lot with product development and innovation. Let's present the topic for the day - Listening AI, our latest feature. Shino: It's exciting. The new generation of employee listening technology.
AI for employee surveys and feedback
Shino: So, what is Eletive? A Global People Success platform. We help people build feedback culture and improve feedback culture. Today we have over 9 million surveys done in our database. A huge number. We also have a unique focus on self-leadership.
"Most companies have historically been good at measuring sales, finance, marketing, production, etc. Companies also have forgotten to measure the most important thing - the employees. Historically, people have been relying on gut feeling, and we attempt to change that."
Patrik: So, how are we going to change it? We have a unique approach. Traditionally and some modern solutions, do have certain solutions that put pressure on boards, HR, and managers, and they don't really involve the employees. Shino: With Eletive, we want to do that. That's the Eletive way - we involve the employees because that's where all the power comes from.
Patrik: You can say that we are developing self-leadership, not only on the individual level but also on the manager and team level, and, on the top management and organisational level. Meaning, all the different levels within an organisation. That is one of the core values of Eletive: improving general engagement.
Related reading: The drivers of employee engagement – and how to measure them
An employee experience with feedback at its core
Shino: Organisations and their management teams always have three questions in their head: what should we keep doing? Stop doing, do better. We also can see that the companies that work with these questions more consciously, also do better. But in the center of this is feedback. So how do we know what we should keep doing, stop going, or do better?
"Employee feedback is at the center. So that's why we're talking about the feedback culture."
Patrik: I can ask you, Shino, what should I keep doing that you have observed the last couple of weeks or a time period, and then you can give me input. But that's only you. I want to ask many more people to get a whole range of feedback. And that's Listening AI at its core. Listening at scale.
The challenges with employee feedback and pulse surveys
Shino: What's the challenge then, Patrik?
Patrik: At Eletive, we believe it's important to encourage feedback. We want to encourage input from the employees, the manager, the whole organisation.
Usually, organisations work a lot with quantified inputs, like 1-5 questions, yes or no, stuff that you can summarize and aggregate very easily. But that will only get you so far when it comes to actionable insights. Often, you need to know more. This is why you need to add open-ended questions and comments in to your employee surveys.
But there's a challenge there. Because if you have free-text answers, you can't really aggregate them that easily. And the challenge is then that information may get stuck in silos, or it gets lost. And when it gets lost or stuck in silos, people tend to lose engagement because people don't feel like the manager or the organisation really listens to them, their opinions, and what they have to say. This is what we have addressed with Listening AI.
The other challenge is that if you are a medium-sized or a larger company, especially if you are a larger company, you have a huge amount of input, of free-text inputs. It is difficult to make sense of that input if you just go through all the comments one by one. And that's a tedious task.
And that brings us to the next challenge. It is hard to get an overview. It's hard to get an overview if you're a manager or if you are an HR manager, or in top management. To get the facts on the table. What should we improve in our organisation? Is it communication? Is it our strategy? Stuff like that. The last challenge is that it is tedious to go through all these answers, all the free-text answers that you really can't aggregate in an easy way. It can be very time-consuming.
The solution: AI technology for HR and employee listening
Patrik: We have developed a sophisticated AI technology that allows you as a manager, or in top management, or anywhere in your organisation, to really listen to your organisation and to extract all the most significant and prominent topics that people speak about.
Related reading: Listening Ai - Employee Listening at scale
We do this in-depth because when you derive actionable insights from open-ended questions and comments, you will really dig deep into what people think of your company and what they want to continue doing, stop doing and do better. The feedback culture. And it is important for us that this is done as close to in real-time as possible.
"That's one of the beautiful things about this feature, that you can address your whole organisation and get actionable insights at scale."
Shino: One important use case is in change management. All of us live in constant change. Hence, change management is crucial today in businesses and organisations. You can use this tool to track how the change is perceived within the organisation and follow different sentiments within the company.
Related reading: Pulse surveys in change management
Patrik: Yes, this shows you which actions you took that made sense and gave results and what actions you should avoid moving forward. Insights based on facts and feedback. Now, we'd like to bring you along a journey, an example of how you can use Listening AI in your organisation.
Let's say you have sent out a survey with free text answers like open-ended questions and comments. You receive all that input. This is the first level of Listening AI, the bird's view. So, Listening AI extracts from all the comments, from all the free text answers that you have received, it really extracts the most prominent, most significant topics that people write about.
Shino: So, these are the most significant topics here.
Patrik: Yes, the bigger the bubble, the more significant the topic. In this example, people have written mostly about "workload" because that's the biggest bubble. And the colour red indicates that it is more negative in emotion, while green means more positive in emotion.
Shino: So the topic "workload" is quite negatively charged in this view, in this organisation.
Patrik: Yes, if you are a manager or in top management, you should really address "workload" as a topic to improve people's success and overall employee wellbeing.
Shino: Yes, that makes sense. For example, if you manage a bigger organisation, if you have too much workload for a long period of time, it's of course very negative for the organisation.
Patrik: Yes. Sick leave, people will maybe leave the company, bad PR, stuff like that. But mostly it's about how people feel and how they can perform in the workplace.
Shino: Ok. Can we dig deeper into the data to understand more?
Patrik: Yes. This is the first level, the bird's eye view. Let's dig into "workload" to get more insights before we can create an action plan, and decide what we should do to address this issue.
The next step can be to look at different segments of the organisation. Segments allow you to group people in all the various ways that you want. You can group them into departments or countries or based on gender or age or anything you want. And Listening AI is connected to this, of course. In this example, we can see that the topic "workload" is most prominent in the segments "Females", "Denmark" and "UK". These are also the segments that speak the most negatively in general and on the topic of "workload".
Shino: All these topics: "workload", "breakfast", "pension plan", "manager", "boss", are the most negative topics right now in these groups.
Patrik: Yes. So here you can create an action plan to address "females", "Denmark", and "UK", perhaps, for "workload", "breakfast", as an example. But if you want to dig even deeper into insights, you will go to next level of Listening AI.
So, here you see, up in the left corner that the topic is "workload". This is what we're looking at, right? But here we see all the adjectives connected to workload. Adjectives. Because adjectives are used to describe topics.
In this example, Listening AI has identified that an unstructured workload or confusing workload is the most negative people write about. The scale is the same here. So negatively to positively here on the x-axis, and the y-axis is the emotional content. The further up you go here, the stronger the emotion is. You should address the adjectives up here and do something about them. Shino: This view makes it even easier to, for example, understand what's happening during a change in the company.
Patrik: Yes, now we can derive "unstructured workload", "confusing workload", it could be that we have an unclear strategy, maybe, or that company goals or values are confusing or unclear, stuff like that.
But if you want to learn even more, you can click on one of these adjectives. For example, here, "unstructured", we will go to the last level, the deepest level of Listening AI.
Here we show the source of the feedback, the source comments from your employees connected to the topic "workload" and the adjective "unstructured". So here you can read all those comments connected to that topic and adjective, for deeper actionable insights. You can also see a comment distribution in "positive", "neutral", and "negative" and the overall score of the "workload" topic. So that is a sentiment score plus.
Global employee surveys in multiple languages
Patrik: We have language support for 39 languages in our product and the listening AI takes care of them all. We translate everything to English and then we do the NLP analysis, the artificial intelligence analysis, which makes it possible for the user to toggle between the original language and the English translation. If you are a global organisation and you have inputs from all over the world, you as an HR manager or anyone else can easily, just by one click of a button, get all the comments translated into English.
Shino: So if I'm a part of a huge organisation and I'm based in Sweden and my Spanish colleagues write something, then I can instantly translate this and understand what the nature of the problem could be.
Related reading: A guide to global employee engagement surveys in multiple languages
Patrik: Yes. So you can use this information when creating objectives, actions, one-on-ones, all the different follow-ups and actions, based on fact, based on what your people are writing about.
Shino: This is really powerful. I can imagine there will be some questions around this from the audience. What you have shown us now, Patrick is that it's a really good idea to understand the organisation, especially the needs of your organisation. And yes, I can only concur.
Patrik: People feel good if they're listened to. If someone pays attention. Pays attention to their thoughts, their ideas, and their advice. That will empower people, people will feel safe, and engagement will increase.
Shino: Safe, you say? Let's talk more about that, what do you mean?
Patrik: I think people are more comfortable when other people listen to their ideas, take them seriously, and include them. It's super important as an employee to feel included within your organisation.
Turning insights into action
Shino: So, to sum things up – what we're looking at here on the left side, that's the challenge. Valuable feedback gets lost or is stuck in silos. On the right side, you find the solution. A unified platform with a structured full-cycle framework.
So, let me shortly just explain what I mean. On the top , you see the box "listen". This is, of course, one of the first steps. You must listen to start to understand. That's the next step, to understand. You're taking the inputs and measurements and surveys like that. What does the management think, what do the employees think? When you have that insight, you can start to act. The action is really important. After that, you can drive performance in the most efficient way.
Patrik: This way you can act in a data-driven way, you will perform, and then you remeasure. And then you will, with Listening AI, extract new insights, and then you will act upon them, and then you perform even bettter. This is the "flywheel of people success".
Shino: It's an agile way of developing self-leadership and a People Success culture at scale in your organisation.
Q & A
Audience: This looks like the perfect HR person that can listen to us all the time. How do you recommend implementing Listening AI with the existing survey strategy?
There are a lot of employee survey strategies out there, so it depends. But when you turn on Listening AI in our product, Listening AI will analyze all your historical comments as well so you can go back in time and gain new insights. And when you perform new surveys, they will be included there as well, of course.
Audience: How does Listening AI work on a global scale with comments and answers in different languages?
The Listening AI analysis is made in English, but the comments are automatically translated so that it works for all the languages that we support, 39 languages. This means you can toggle back to your original language for all the comments, to see the original source.