Vice President of Consulting at Explorance, engaging with clients on making better decisions using employee journey analytics.
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Surveying has become an effective and easy way to collect feedback, whether you are in the customer, product, employee or education business. The ease of creating surveys and sending out quick pulses has been significantly improved with survey technology. In fact, many HR leaders now routinely pulse or create event-driven surveys to collect feedback. While this has greatly enhanced the ability to gather data in the moment, one area of analysis continues to get the least attention: the comments.
Most surveys include an option to provide comments. This is a great way to provide additional context to areas that may not be probed in the questions. Analyzing comments in relation to the quantitative metric can lead to surprising results and perhaps a different approach in how you make decisions and engage with the data.
For example, many years ago I was speaking with a tech entrepreneur who was puzzled by the lack of participation in his company's 401(k) program. This company provided a great matching benefit but consistently saw a decrease in 401(k) participation. After multiple surveys and reviews of compensation, it was unearthed through comment analysis that an underlying issue was causing low participation. It had nothing to do with how the benefit was designed. This company had many younger employees and paid competitively. However, many younger employees were paying down student debt rather than participating in a 401(k). Only through this sentiment analysis was it learned that perhaps another benefit would be more meaningful. As a result, the firm began offering a student loan refinance and company match to ease some of the financial burden. It was not in the quantitative analysis; it was analyzing comments that got us there.
You have to wonder, then, how much you are missing when the focus is just on quantitative results. Comments uncover additional issues if measured for consistency in theme. And sentiment analysis technology, powered by natural language processing and machine learning, has improved greatly over the years and is found in numerous employee survey platforms.
There is a lot out in the marketplace in terms of text analysis. As technology has improved, it is important to note the difference between artificial intelligence and machine learning. Artificial intelligence (AI), where intelligence is the acquisition of knowledge, is an ability to acquire and apply knowledge. It works like a computer program that does smart work.
Text analysis for sentiment is best derived from machine learning (ML) functionality. ML is the acquisition of knowledge or skill. It is a concept of taking in and learning from data.
Sentiment analysis technology can interpret large amounts of text to uncover organizational strengths and weaknesses and detect positive and negative sentiment around a change in benefits, management practices or workplace culture. Machine learning technologies are now also being trained to categorize feedback and identify sentiment. Business leaders can leverage these to learn additional information such as cultural issues, ethical concerns, risks, what behaviors are prevalent in the organization and if these are aligned to the culture.
While many people leaders rely on external benchmarks to assess their own company performance, leaning into your own feedback, asking more questions and following up on feedback is the next frontier. Standard question banks and quantitative results don't necessarily uncover these feedback moments.
By combining both forms of analysis, HR and operations teams can make better decisions with more context. Business leaders can:
1. Review the consistency of themes in comments to uncover insights not addressed in questions.
2. Identify cultural attributes that are creating barriers.
3. Receive more specific feedback around the “why” that may not be available in drop-down or multiple-choice responses.
4. Hear from employees or customers about ways to enhance features, processes and culture.
5. Change the way they survey, consider additional questions or create additional opportunities for feedback.
As you move forward in developing a survey strategy, consider how you are analyzing your comments and incorporating them into action items. It goes a long way when comments are reviewed. After all, feedback is a gift, and by analyzing and considering all that you've gathered, you may not only find deeper insights, but also have a more engaged feedback process.
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