How GenAI is Transforming People Analytics Software
Generative artificial intelligence is democratizing the use of people analytics and lowering the barrier to entry, enabling CHROs to do more with fewer resources and create better analytics outcomes.
When the turnover rate among hourly workers was rising at Sunstate Equipment in Phoenix, the company wanted to know why. In the past, Sameer Raut, SHRM-SCP, Sunstate’s vice president of HRIS, would have reached out to the data science team or created an analytics report himself for answers. Instead, he simply turned to a generative AI-driven chatbot and asked it a question in plain English: “What are the top reasons for hourly employee terminations in the past 12 months?” Within seconds, Raut had a detailed answer.
Such GenAI tools are transforming people analytics software that once required a high level of data literacy for CHROs to use. The fast-evolving technology is addressing a major pain point for HR executives. A 2023 study from Aptitude Research, for example, found that 39% of HR leaders cited limited expertise as their greatest challenge with people analytics.
The recent addition of large language models (LLMs) to popular analytics and business intelligence platforms has elevated the natural language processing (NLP) capabilities of many systems to a new level. As a result, many of these analytics systems no longer require CHROs to phrase data queries in particular formats or use specific keywords to get accurate responses.
For example, a CHRO could ask a GenAI chatbot questions such as, “How does the software engineering team’s voluntary turnover compare to industry benchmarks?” and “What’s the trend of time-to-hire for business development specialists in Boston over the past two years?” The GenAI assistant would then quickly compile and retrieve that information from company datasets.
HR technology analysts say that GenAI has also enhanced people analytics tools by automating previously manual processes in a way that creates more accurate and reliable HR data. The technology accomplishes that through improved data cleansing, data augmentation, and the efficient uniting of disparate HR data into one place.
Easier Access to Key HR Data
Commonly used analytics software providers such as Visier, Microsoft Power BI, Tableau, Qlik, and Sisense have all added some version of GenAI tools to their software. These tools are designed to improve the usability of their platforms and make it easier for HR executives to extract trends and insights from data related to metrics such as workforce costs, employee attrition, and recruiting performance.
“We use our GenAI digital assistant to ask strategic questions like how our total workforce costs correlate with year-over-year headcount growth and to analyze headcount trends by department,” says Raut, referring to Visier’s GenAI tool Vee. “We also use Vee to analyze trends in terminations and track the number of open requisitions for our technicians, helping us identify potential gaps in our hiring needs.”
Previously, when he needed to access such data, Raut would have contacted his people analytics team, which could lead to delays. Or he might have undertaken the time-consuming process of building a report with multiple filters himself.
“Now with Vee, I can just type in a request and receive an answer immediately,” Raut says. “The usability of the tool also makes it easier to get people data into the hands of those outside of HR, like senior leaders or front-line managers, so they can use the data to help drive their decision-making.”
To that end, experts say that GenAI is democratizing the use of people analytics in organizations, reducing the learning curve, and bringing those tools to a broader, non-HR audience by embedding them in commonly used platforms such as Slack and Microsoft Teams. This allows the data to reach line managers, for example, who might never log on to an analytics platform.
“GenAI is lowering the barrier to entry for people analytics solutions,” says Lydia Wu, former senior director of people strategy and operations at Panasonic Energy of North America, who now works as the vice president of products for MeBeBot, a company that provides AI solutions to the HR market. “Historically, you would need a team of data scientists or researchers to generate the reports and findings you need. GenAI can enable CHROs to do more with fewer resources and create better analytics outcomes at the same time.”
Stacia Garr, co-founder and principal analyst of RedThread Research, an HR advisory and research firm in Woodside, Calif., says that while the NLP capabilities of some analytics platforms haven’t yet reached their potential, other vendors now have more advanced GenAI chatbots.
“Some of the more sophisticated vendors have been working hard on improving their ability to handle complex data queries and are further ahead on that front than others,” Garr says. “But in general, the ability to create more nuanced, high-quality sentiment analysis with NLP exists and is making HR analytics more accessible to more people.”
Jeremy Shapiro, assistant vice president of HR and workforce analytics with the global health care company Merck, says he’s been using a GenAI tool in an analytics platform for about a year and believes CHROs are only at the beginning stage of their journeys with the technology.
“Many of the tools out there now are proving helpful but aren’t necessarily essential yet,” Shapiro says. “But the trajectory of where GenAI is going is exciting. We are in Chapter 1 of a book that will be the length of a Stephen King novel.”
Raut believes another key benefit of GenAI-driven chatbots is that they enable real-time insights during meetings and brainstorming sessions. “If someone in a meeting asks for some specific HR data, rather than saying, ‘Let me get back to you tomorrow,’ you can simply ask the GenAI assistant a question and get an answer right away,” he says. “That creates more productive and timely interactions.”
Telling Better Data Stories to CEOs
GenAI tools can also provide automated suggestions and tips that help CHROs and their teams create more visually compelling presentations—at a faster pace—for reporting analytics findings to CEOs or CFOs. Some tools, for example, can customize data visualizations, such as reports or dashboards, to audience preferences and create automated summaries of key data points.
“A CHRO isn’t going to walk into a CEO’s office and say ‘Let me walk you through the science and statistical significance of our latest HR data,’ ” Wu says. “They’ll have maybe five minutes to lay out the problem and solution they found, ideally telling that data story in a graphically enticing way. Some GenAI tools can help put together persuasive data stories faster for CHROs and executive teams.”
The Data Security Question
The use of GenAI tools in analytics software doesn’t come without concerns for CHROs. Among the top fears is that using the still-embryonic technology will lead to the leaking of sensitive or proprietary company data.
“I was just at a gathering of CHROs from startup firms as well as larger companies, and they all agreed the No. 1 risk of GenAI use is accidentally exposing sensitive data to the wrong people,” Shapiro says. “You have to be assured your data will be well-protected.”
Guaranteeing that third-party analytics providers have an “entitlement management” model of data security is an important first step, Shapiro says. Such systems identify and closely control user access rights to sensitive information. Those access privileges, called “entitlements,” are typically based on employee roles and duties, as well as the company’s business needs.
Wu says it’s also important to understand how analytics providers train their LLMs. Visier, for example, avoids the risky process of training its model on customer data. Instead, it trains its LLM only on the universe of questions users ask Vee, its GenAI assistant. Those questions can sometimes be vague or context-dependent, and the LLM needs to be adept at translating them into specific data queries.
Experts say the use of GenAI-infused chatbots like Vee on analytics platforms also largely avoids well-publicized problems such as hallucinations, inaccuracies, or copyright concerns because the LLMs don’t draw from public information on the internet but rather from an organization’s domain-specific people data.
Dave Zielinski is a business journalist based in Minneapolis and the lead technology writer for SHRM’s HR Quarterly.
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