HR & People Analytics: First 3 reasons to embrace Natural Language Processing in Human Resources

Did you know that 80% of business-relevant information is made up of text? This type of unstructured content is growing much faster than structured data. Think about the millions of words written every day on social networks, company forums, blogs, resumes, or comments in surveys.

There is a great opportunity for those who can leverage that type of data. For example, analyzing exit surveys and acting upon the results, will enable you to shorten recruiting time. It will streamline the hiring process or reduce absenteeism. You could also reduce the risk of possible litigation.

But, there is a problem. The information available is massive. When human beings have to read and extract insights from text-based sources, it is tedious and expensive. If you’ve ever done qualitative research, you know how time-consuming it is. Sometimes, it is even just impossible.

This is where Natural Language Processing comes in! NLP is defined as the ability of machines to understand and interpret human language the way we human beings do.

NLP is a sub-discipline of Artificial Intelligence. Artificial intelligence has been around since the 1950s. It has become increasingly popular over the past few years. Personally, I can hardly hide my enthusiasm about Artificial Intelligence. I share this excitement with an increasing number of people analytics practitioners. We see that AI is transforming HR departments from top to bottom.

Reason number one: We, humans, are rather talkative!

We love sharing our thoughts on social media. Several company forums are overflowing with comments. Thousands of suggestions reach us in surveys.

I have already mentioned it in the beginning: It is commonly accepted that 80% of business-relevant information is unstructured. It is made up of text, mainly. This unstructured content is growing much faster than structured data.

Natural Language has a huge potential as a source of valuable insights. But, until recently, it was rarely analyzed or used in decision-making. This was because the process is too time-consuming. Sometimes, it is even impossible to read and analyze thousands of lines of text. Natural Language Processing technologies automatically process and analyzes textual content. They provide valuable insights and transform this "raw" data into structured, and valuable information.

Reason number two: Chatbots are cool

I’ll assume most of you have heard about Amazon Echo, Google Assistant, Apple Siri, or Windows Cortana. These are all chatbots. A chatbot is a computer program designed to simulate a conversation with human users through Artificial Intelligence.

Chatbots are proving to be extremely popular in the HR world too. According to a recent Forrester survey, roughly "85% of customer interactions within an enterprise will be with software robots in five years' time". And "87% of CEOs are looking to expand their Artificial Intelligence workforce" using AI bots.

Most organizations are making an effort to improve labor efficiencies, reduce costs, and deliver better employee experiences. They are quickly introducing AI, machine learning, and natural language processing in their strategy. In recent years, chatbots are beginning to be part of the digital transformation agenda. This is having an impact on important HR areas, such as recruiting, onboarding, training, career path development, and benefits.

Reason Number three. More and more Open-ended questions

If you've ever been in a medium-sized or large company, it's very likely that you often had to fill out surveys. Most of them came from HR Departments.

These surveys are made up of open- and closed questions, which differ significantly and impact the way we interpret their answers.

Closed questions supply the participants with a specific line of possibilities. They ask them to choose one of the available answers.

An example of a closed question is a question for the Employee Net Promoter Score, which is: How likely is it you recommend this company as a place to work?

You then have a closed range of numeral choices, from zero to ten. These questions are easy to analyze, as it gives us a straight numerical answer and can thus be analyzed more easily.

In contrast to closed questions, open questions give participants the freedom to respond and comment on whatever comes to mind in a survey.

Such an open question can also be found in the Employee-Net Promoter Score.

Open questions are a company's most valuable source. The feedba