How to Use and Analyse Text from Employee Surveys
We increasingly expect a similar experience at work as that we enjoy as consumers. This coupled with advances in technology and the growth of people analytics has seen a surge of growth and innovation in the field of employee experience and surveys. With growth comes noise. How often should I survey my workforce? Is it time to ditch the annual survey? What about survey fatigue? How do I combine surveys with other data and analytics?
These are just some of the areas David Green covers with his guest Sarah Johnson, Vice President of Enterprise Surveys and Workforce Analytics at Perceptyx, in this episode of the Digital HR Leaders podcast. Sarah is an IO psychologist who has been in the survey research space for 35 years and combines her wealth of experience with an exciting vision for the future.
This episode is a must listen for anyone interested in employee experience the role of people analytics and the insights and outcomes that can be generated through the intelligent use of surveys.
In this extract taken from their conversation, David and Sarah discuss why text is the ‘final frontier’ for surveys and the opportunity this brings for analytics in the HR space. You can listen to the full episode here.
According to an article published by Bernard Marr, 90% of the world’s data was generated in the last two years alone. Much of this data is unstructured data, which remains largely untapped by the majority of organisations especially when it comes to HR and people data.
Given the opportunities offered by ‘text analytics’, it is not surprising that people analytics teams and HR leaders are looking for ways to utilise this data to support their work.
What is text analytics?
According to Andrew Marritt, CEO of OrganizationView and an expert in the field “text analytics is the application of algorithms to process text information”. When people talk about an explosion of data the growth is mostly in unstructured data - text, images, audio, video - not classical ‘numbers’ in databases. For many organisations probably the most common type of unstructured data is text.”
Text analytics or sentiment analysis technology is often powered by natural language processing or machine learning and ultimately it enables us to analyse and interpret huge amounts of data to understand themes, engagement, identify patterns of success and more.
It has been extremely challenging to make systematic use of text feedback because it’s so difficult to analyse and quantify. Historically, survey comments would be transcribed, hand coded into topics and then analysed. However, the growth of technology in this area and the introduction of text analytics has revolutionised this process, allowing the analysis to take place far quicker than ever before and provide greater understanding on employee sentiment by changing qualitative, unstructured data to quantitive structured date.
Some the most promising areas that text analytics can really drive impact within HR are:
Understanding the voice of the employee & engagement surveys
Analysing the voice of the employee provides insight on the needs, wishes and sentiment of the employee towards the organisation
Recruitment
Text analytics in this area supports recruiters with the tedious task of sifting through hundreds of CV’s to identify the talent best suited to a role based on the needs of the organisation
Exit interviews
The analysis derived from the results of these types of interviews provide valuable information that can help improve future retention, optimise the employee experience and determine ways to drive real cultural change within an organisation.
For more information on how text analytics and AI is driving real change across HR take a look at our our online course Introduction to AI in HR and the Future of Work, in which Ian Bailie and Soumyasanto Sen provide a great foundation to really understanding how technology is optimising the way we improve the employee experience of HR.
How is text analysis impacting HR?
Where we see the true benefit of text analysis is the insight it provides, as Sarah Johnson explains, the real challenge you experience from just reading comments without that layer of analysis applied, is that you lack the necessary level of insight or framework for you to truly understand the sentiment behind the comment.
“Whenever I meet with a leadership team, they're very interested in the survey data, the results, the analysis. But there are so many CEOs who will say to me, Sarah, I read every single comment. I sat down with a book of 10,000, 20,000 however many comments there were and I read every single one of them. And I think to myself, okay, that's nice. It shows you're interested. But I don't know what you took away from that. You can't read comments like a novel and come away with any sort of understanding because there's no organising framework for that information. Comments really are the final frontier because we have the ability to pull tremendous insights out of them. But the challenge is you are faced with literally millions of words in multiple different languages. And how do you make sense out of it? And to just read the comments is not going to give you a tenth of the insight you could pull out of it.”
As Sarah discusses sentiment analysis is incredibly useful and provides some great insight that can be leveraged by organisations. However the real value lies in the ability to analyse unstructured data and identify patterns and themes within the comments that form organically.
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“So, as we think of comments going forward, we are looking for not just sentiment analysis because it's kind of interesting that a comment is positive or negative. But it's really more interesting what is in the comment? What is the employee identifying as the way forward? So, we are starting to look at programming around unstructured comment analysis using NLP to search all of these patterns within the text data and start to form the themes organically from the comments that people read.”
Being able to take the analysis beyond just theming but actually begin to derive insight you wouldn’t have otherwise found is one of the many ways that text analytics can support HR in creating an experience at work that mirrors the consumer experience. Sarah explains
“Now one of the things that I think our tools are exceptionally good at is not just finding the themes in the comment but linking the comments to how employees responded to survey questions. So for example back to our example of high-potential younger employees who are leaving the organisation very quickly. Well if I know that let's say 10% of them may leave the company in the next year. I can use the Perceptyx tools to filter to just that group of employees, that 10% and now I can go back and read just their comments and I can do keyword searches and theming around what did they say that will help me understand why they want to leave the organisation. So it's the ability to drill into the comments through multiple different ways. How they respond to questions the demographics, all of that, that's going to provide us additional insights, but there's so much more work that needs to be done to help us pull all of that context and all of that insight out of those comments.”
Text analytics allows you to really drill down into the data, by applying demographic filters you’re able to begin telling a far richer story, as they provide insights that you wouldn’t usually be able to obtain from just a survey alone.
“When you can combine the demographic filters with how they responded to specific survey questions, and then what they said, I think it really starts to tell a much richer picture. A richer story about their experience within the organisation and then leads a management team or leadership team more closely to what do I need to do about it? What are the specific issues they're experiencing?”
There is a huge opportunity for analytics in the HR space, and the more HR organisations can understand how to use their survey strategically, the closer we get to “understanding what is going on within your organisation? What are the strategic objectives of the business? What are the leadership issues that they're trying to solve? What do we need to know about executives in our company? If we can get as specific as we can about those questions and about those issues, then I think we can do richer and richer work that really guides senior leaders and guide decision making within organisations and change the path of the organisation.”
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