Harnessing the power of sentiment analysis to streamline benefits
Increasing the benefits available to your employees may sound like a smart move, but it’s crucial that businesses consider whether their benefits offerings actually meet their employees’ specific needs.
Employee benefits are complex and expensive, typically one of the top three expenses for employers. Yet, companies often make costly benefits decisions without meaningful data on what their employees actually want or need. According to SHRM’s 2018 Employee Benefits Report, more than one third of respondents increased benefits offerings in the last year, likely without the right information at hand.
Increasing the benefits available to your employees may sound like a smart move in general. After all, what person doesn’t want more everything? But it’s crucial that businesses consider whether their benefits offerings actually meet their employees’ specific needs, and deliver the impact intended. Often, adding extra benefits or new plans to existing packages leads to employee confusion and wasted organizational resources, if the new options are underutilized or perceived as duplicative.
Related: How do millennials make benefits enrollment decisions?
The good news is that new technologies, including artificial intelligence (AI) and machine learning, are primed to play a leading role in the future of benefits: advances in these areas will help HR and benefits leaders truly understand, and efficiently meet, the needs of their people.
Understanding your employees’ needs
There’s often a disconnect between employers and employees when it comes to benefits offerings. While 78 percent of employers believe their employees are satisfied with their current benefits offerings, only 52 percent of employees report being satisfied! Through machine learning, examining any organization’s historical data, employees can have real-time, automated recommendations into what plans would best meet their needs at their current life stage. And when more information is needed, AI-enabled chatbots could allow employees to ask natural-language questions directly of benefits providers, and instantly receive targeted recommendations based on the conversation.
Another example is integrating AI with company surveys to better understand the comments in open-ended questions, providing organizations with instant, rich insight into employees’ wants and needs. Open-ended surveys (vs. simple multiple choice) allow for more meaningful responses, but traditional surveys can take months to administer, analyze, and act upon. AI-enabled survey solutions, by contrast, allow HR to immediately gather actionable intelligence to make needed changes before they become problems.
The most powerful AI and sentiment analysis tools can recognize hundreds of human emotions (confusion, sarcasm) and themes (work-life balance, development), using the power of deep learning on millions of similar documents to classify and summarize open-ended comments instantly, and with greater accuracy than a person could. The analysis of open-ended data provides specific information about how employees actually feel and can dramatically improve the relationship between an organization, its managers, and its employees.
Sentiment analysis application
The HR team at Steel and Pipe Supply Companies Inc. (SPS) in Manhattan, Kansas, is one example of an organization using the power of AI and sentiment analysis to create meaningful change. SPS sought an intelligent survey solution to help engage their employees, and streamlining benefits was one of the first business problems they solved with sentiment analysis.
The team previously administered its Leadership and Engagement survey to 600 employees using a simple online survey platform, but the process was cumbersome. More than half of SPS’s employees worked on a warehouse or manufacturing floor, so surveys had to be completed on paper. Not only did this increase the chances of accidental errors, it also slowed down the process—from synthesizing the data to compiling reports and actions—to a crawl, making any actions taken after the survey significantly less timely, which eroded employee trust in management and HR.
However, after using a human capital management (HCM) platform with AI and sentiment analysis as a core capability, SPS was able to get a better sense of how its employees felt about certain benefits offerings, where there were opportunities to shift resources to better meet needs (not just “more!”), and ultimately streamline plans based on the preferences revealed by the survey—faster. By tasking AI with analyzing responses and reporting back on the tone and themes of open-ended responses, what used to require six weeks of challenging work reviewing surveys by hand, collapsed to just a few days in total, with immediate insights, and actionable results. Previously, SPS had eight varying plans available for critical-illness benefits, which were difficult to explain and implement on both front and back ends.
By giving intelligent surveys to employees using these existing benefits, SPS understood what was actually important to them, and where similar or unnecessary options could be eliminated. Survey results were incredibly clear on preferences around two primary plans, so the company was able to reduce eight plans down to two. Additionally, the cost savings on both the administrative and benefits planning allowed SPS to launch SPS Thrive, a new HR-led wellness initiative offering nutritional, physical, emotional, and financial support to employees—something also discovered on employees’ wish lists.
Humanizing AI for results
AI has great potential in the benefits space, but it should be used to assist, not replace, human analysis in helping organizations make better decisions. Understanding people starts with listening to what they have to say, and AI can help hear every voice and read between the lines to get at what matters most.
Ultimately, technology must find more natural ways of working with people in order to fulfill its potential as our quintessential partner. It needs to speak our language and accommodate all our complexities—not the other way around. Asking survey respondents to rank questions on scales of one to five is an example of humans evolving their speech to fit a computer’s language. However, providing simple, open-ended surveys and using AI and sentiment analysis to understand how employees feel about their experience brings technology to our “home court.”
The purpose of AI in the HR field should never be to replace people, but to make it easier for HR leaders and managers to make smarter decisions with ultra-personalized, real-time insight. In HR and benefits management, that means providing them with the tools to treat their people like people.