?HR leaders are more often using people analytics to solve workforce challenges, but the use of data analysis to optimize business outcomes is still at an early stage, and the shift to a data-driven culture is still in progress in many organizations, according to a new study.
SHRM Research surveyed 2,149 HR professionals and 182 HR executives who work for organizations that currently use people analytics.
The research found that HR executives appear committed to building a data-driven culture.
“HR leaders are increasingly looking to people analytics as a tool to answer key business questions, as 71 percent of HR executives whose organizations uses people analytics say that people analytics is essential to their organization’s HR strategy,” said Alex Alonso, Ph.D., SHRM-SCP, chief knowledge officer at SHRM. “If HR professionals and leaders use people analytics and AI appropriately, they can make more effective decisions, improve the employee experience and impact the bottom line.”
But according to the study, HR professionals were less likely to see signs of a data-driven culture within the organization. The survey found that just 58 percent agreed that data is used to make decisions throughout the organization, and that most employers (77 percent) are only using basic analytic techniques for limited purposes, such as using already available data to analyze what happened in the past.
SHRM Research found that 19 percent of organizations were using data to construct causal models and other sophisticated analyses to understand why patterns are occurring, and a mere 4 percent were using data to predict what will happen in the future.
“There are two practices which differentiate a transformational people analytics practice from regular people analytics work,” said Ian Cook, a people analytics expert and vice president of research and strategy for Visier, a workforce analytics firm in Vancouver, British Columbia. “The first is to view the role of the people analytics group as supporting business decisions and business direction. Without a clear link to business challenges and opportunities, the work of a people analytics team will have limited impact.”
The second practice is to measure success as the adoption and use of the people analytics team’s work, Cook said. “Many people analytics teams are tasked to simply produce dashboards or lengthy reporting decks. This information may be interesting; however, if leaders do not use it and it does not align to the key decisions they need to make about their people, then it will not drive change. When you define success based on the amount of use and reference received by the work of the people analytics team, this creates change. If success is defined solely that the report has been produced, then the impact will be limited.”
According to surveyed HR professionals, organizations are using people analytics most often to identify turnover, and for talent acquisition activities such as matching job applicants with roles and scoring screening interviews.
“Many teams begin by focusing on talent acquisition and turnover/retention projects, as these areas are highly visible, have clear outcomes to measure, and often have data available with good governance,” said Richard Rosenow, vice president of people analytics strategy at One Model, a people analytics platform in Austin, Texas. “Compensation projects are also commonly included in this mix of starting projects, such as pay equity, compensation planning and cost of workforce studies.”
Cook said many Visier clients leverage analytics to focus on diversity, equity and inclusion; internal mobility; and compensation.
Hiring HR Data Analysts
Another reason why some organizations struggle to leverage the full potential of their people analytics may be a lack of people analytics experts. Only 30 percent of organizations that use people analytics have an employee, department or division dedicated to this function. And it is
rare for small or medium-size employers to have this function, SHRM Research found.
“Access to data is one thing, but the factor which is more impactful in generating value is the interpretation and understanding that comes from the data,” Cook said. “This knowledge is not common, and hence there is a strong need to invest in people who have the relevant expertise to educate the HR team and the rest of the business in the application of people data.”
HR teams often try to hire a data scientist without having the necessary infrastructure in place, Rosenow said.
“Without well-defined processes and proper implementation of technology, data quality suffers, which makes it difficult for people analytics teams to succeed,” he said. “To achieve long-term success, it is important to start investing earlier in the value chain and to establish a clear flow of process to technology to data to analytics, addressing upstream issues rather than relying on downstream fixes.”
Rosenow noted that trying to predict and understand human behavior “is just plain hard. Unlike other functions that handle more straightforward data sets, HR has been asked to capture and comprehend humanity in a data table. There are teams that have done incredible work in people analytics despite these challenges, but it’s not easy work.
“How can we expect business leaders to drive business goals without data?” Rosenow asked. “In 2023, data is used everywhere to make business decisions, and HR is a function of the business.”
An AI Future
SHRM Research found that 9 percent of HR professionals whose organizations use people analytics use an AI-driven form. Only 19 percent of that group are very confident that their AI-driven people analytics tools eliminate bias, and another 70 percent are somewhat confident, while 11 percent are not confident their tools are unbiased.
“Organizations must invest in governance structures and quality data as foundational pieces to implement fair, ethical and responsible uses of AI-driven people analytics,” said Emily Dickens, chief of staff and head of public affairs at SHRM. “Understanding and weighing the potential risks and benefits of people analytics and AI-driven people analytics tools before investing in them is critical to ensuring better workplaces.”
Cook said AI will play an important role in the development of people analytics. “Some vendors have had these types of capabilities within their solutions for some time and will continue to add capabilities that support the overall goal of people analytics—better decisions about how people impact the business,” he said. “The greatest opportunity with generative AI is that it can make insights about people more accessible, and clearer to more people.”
But vendors and organizations will need to be educated on how the technology works best, and the risks it brings, Cook said.
Best Practices
Ragan Decker, SHRM-CP, lead researcher for SHRM and co-author of the study, said adoption of analytics and AI technologies comes with several considerations that organizations must carefully weigh. “In this report, we have identified seven best practices that address crucial topics related to the effective and responsible use of people analytics and AI-driven people analytics,” said Decker, who has a Ph.D. from the University of Connecticut and graduate certificates in quantitative research methods and occupational health psychology.
She added that building a strong analytical foundation holds particular significance, because it serves as the basis for effectively implementing the remaining six best practices and without this foundation, the other practices may not lead to the desired outcomes or results.
“A strong analytical foundation includes several key elements such as upskilling employees, establishing a solid data infrastructure, and adopting the right tools and technology,” she said. “However, our research indicates that only around half of executives believe their organization provides sufficient resources for these aspects. This suggests that many organizations may be investing in advanced tools and technologies without adequately preparing their workforce or establishing the necessary infrastructure to effectively utilize them.”
In addition to investing in the fundamentals, best practices include:
- Examining the quality of your data.
- Being prepared to explain how people analytics is used to make decisions.
- Only implementing fair, ethical and responsible uses of people analytics.
- Assessing compliance and understanding the legal risks associated with people analytics.
- Protecting employee and applicant data.
- Establishing people analytics governance.
“Strong people analytics governance needs to include stakeholders from across the business and focus on measurement standards, data lineage and the processes by which people analytics projects impact the business,” Cook said. “This practice builds understanding about people analytics work across the organization, creating the conditions for wide adoption and a more transformative overall program.”
