Most employee surveys use quantitative methods. They ask close-ended questions with respondents answering on a Likert-like scale, satisfied, not satisfied etc. The results are fairly easily gathered and scored/quantified. It has been thus in HR for decades. But by sticking with this process are HR professionals not missing out on the opportunity to get a richer sense of what their employees think and feel about their relationship with their job, company, it values and mission? Would they not get a richer sense of their employees’ opinions if they asked more open ended questions, allowing employees to explain how they feel and raise items or issues the survey writers or the focus groups that helped them with the research didn’t bring up?

We assume and have been told that one of the main reason HR departments don’t regularly use more qualitative methods in their employee research is because they believe it is too difficult, time consuming and expensive to analyze and “score” large volumes of open-ended questions. We believe they are missing an opportunity.   Using text analysis tools like QDA Miner and WordStat would open up new areas of analysis that would make their companies or organizations better and position the HR department as an even greater strategic asset.

For example, by using text analysis companies could be making better use of exit interviews by contrasting and comparing comments about personnel, processes and other issues across departments. Are current methods providing enough data to spot common themes and identify trends that could impact labor relations, contract negotiations, continuity planning, safety issues and customers concerns? Text analytics can also be used to analyze the vast amounts of information about a company or organization on social media. What are your employees saying on twitter or industry chat groups? The technology is being used by market research to track customer comments so why not in HR?

Text analytics can aid human resource departments in recruitment by extracting topics and themes from hundreds or thousands of resumes and cover letters helping you identify the top candidates for key positions. A similar analysis can help HR professionals craft better job postings by seeing how the best applicants describe themselves and then using that analysis to create job postings that will resonate with and attract the best candidates.

If you agree or disagree with our premise please let us know. Or if you think there are other uses for our software to help HR professionals tell us that too. Finally we want to hear from researchers who are using qualitative methods in their HR research and do you think these methods have a place in the practice of HR.

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