The Role of Natural Language Processing in Employee Sentiment Analysis
As human beings, our everyday decisions are impacted by the way we interpret and act upon our emotions. These emotions, opinions, attitudes, and beliefs are the sentiment that drives our behaviours. And as HR Leaders and professionals, understanding the sentiment of our employees is key to ensuring a successful and dynamic workplace.
In their Guide to Using Group Voice Channels, The Chartered Institute of Personnel Development (CIPD) shares how employees who feel that their voice is heard are likelier to feel empowered, productive and committed to their organisation.
This is where the power of employee listening comes into play. Of course, there are multiple ways that you can listen to your employees, but employee sentiment analysis offers a unique benefit towards driving data-driven decisions.
Employee sentiment analysis can help organisations understand their employees' attitudes and subsequently employee engagement and feelings towards the organisation, its products and services, and their job role through analysing feedback from surveys, interviews, focus groups and more. It consists of various techniques, including natural language processing (NLP) and machine learning algorithms used to automatically interpret large amounts of unstructured data.
What is Natural Language Processing?
Natural Language Processing (NLP) offers a significant advantage regarding employee sentiment analysis.
In People Analytics, NLP offers a powerful way to analyse large amounts of unstructured text data automatically. It has been proven successful in identifying the skills of an organisation for adequate workforce planning, and it can also be used to provide deeper insights into the sentiment of employees.
Essentially, natural language generation is a subset of Artificial Intelligence (AI) that enables machines to understand human language by using techniques such as text analytics.
As Andrew Marritt, CEO of OrganizationView and Course Lead on Applying Text Analytics To HR Data at the myHRfuture Academy, highlights:
"Text analytics is the application of algorithms to process text information. Once this is achieved, all sorts of statistical or machine learning analysis can be applied to derive meaningful insights from text data."
Uncovering Deeper Insights from Text Data for Actionable HR Decisions
Some of this text data will come from large amounts of unstructured text such as employee feedback surveys, employee exit interviews, and more. And while a common method of analysing this relevant data is to detect and identify themes or common topics (e.g.' communication' or 'compensation'), as Andrew highlights in another discussion with David Green, this simple way of categorising…
"… is rarely good enough to be useful. We believe that the data needs categorising down to a level where the label of the theme itself is a good answer to the question. So, communication could be 'more transparent communication' or 'more frequent leadership communication', 'better inter-departmental communication', 'less electronic communication' or even 'less communication at the weekend".
In essence, it's about finding themes beyond the surface level and then drilling into those themes to explore underlying sentiments from employees, which can help HR and business leaders build actionable insights to implement changes.
To put this into perspective, Sarah Johnson, Vice President of Enterprise Surveys and Workforce Analytics at Perceptyx, shares that:
"When you can combine the demographic filters with how [employees] 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?"
Ultimately, the value of NLP techniques in creating a data-driven HR function is immense. It can help identify patterns or topics from large amounts of text data, and when the AI is understood and used to its full potential, it can help to uncover deeper insights that can inform and empower HR Leaders to create a better workplace environment for their employees.
The Importance of Understanding NLP Techniques and Technology in HR Decision-Making
Though, as much as employee sentiment analysis and NLP techniques have proven to play a critical role in the future of people analytics and driving data-driven decisions in HR - it's equally important to recognise that Natural Language Processing has limitations. It's not perfect, and false positives can occur when the AI isn't trained correctly.
Employee sentiment analysis is complex, as it's hard to gauge human emotions from text data accurately. NLP techniques can help understand the context of language, but it needs to be more omniscient and may rely on inaccurate assumptions when it's trying to identify emotion in written language.
This raises the importance of understanding the technology before deploying it and having a solid employee listening strategy that helps HR Leaders leverage it efficiently.
Unlocking the Potential of NLP Techniques for Data-Driven HR
NLP techniques can be revolutionary when understanding employee sentiment and creating data-driven decisions in HR, but like all AI technologies, it has its limitations. That said, these challenges are a reason to open to NLP. If understood correctly, this technology holds immense potential for people analytics and driving workplace improvement through a deeper understanding of employee data.
By leveraging NLP as part of a larger employee listening strategy - it's possible to identify broad-level themes, uncover underlying sentiments, and carve out actionable insights that can help companies improve their workforce practices.
If you are unsure how to use employee sentiment analysis and natural learning processing correctly or need to understand how it can help you create more data-driven HR decisions, sign up for Andrew's short course on Applying Text Analytics To HR Data on myHRfuture.
If you would like further guidance on how to use NLP in your HR function we encourage you to visit our Insight222 site for a free consultation and discover the possibilities of transforming your organisation with people analytics and AI. We'll help your HR team leverage NLP techniques to uncover powerful insights and become the data-driven business you aspire to be.
Talk to us today and start learning how Natural Language Processing can benefit your organisation!
Looking to stay ahead of the curve and future-proof your career in HR? Our online learning course, Applying Text Analytics to HR Data, will teach you the key concepts and techniques needed to effectively analyse text-based HR data in your organisation.
Led by world-renowned expert Andrew Marritt, this course covers everything from the basics of text analytics to practical examples and common uses in HR and beyond. By the end of the course, you'll have gained valuable knowledge and skills, including word embeddings and key techniques to get started with text analytics in HR.
Enroll today and take the first step towards becoming a text analytics pro!