LeadingAge Magazine · November-December 2018 • Volume 08 • Number 06

People Analytics is on the Way to Aging Services

November 16, 2018 | by John Mitchell

The application of artificial intelligence-assisted decision making in human resource management is making inroads in the business world, and will likely do the same for our field.

Odds are, artificial intelligence (AI) is coming to a human resources department near you soon. AI, the output of big data and machine learning, is transforming hiring, retention and personnel management strategies. Bigger companies are increasingly deploying HR AI—known as people analytics.

As in other sectors, from health care to retail, AI is advancing in fits and starts. It’s not perfect, but advocates argue that AI-assisted decision-making yields better outcomes than humans going it alone. One study found that organizations that leverage HR data outperform peers 58% of the time, by margins of 200% or more.

Early adopters, such as IBM, Kraft Heinz, and SunTrust are mining tangible, wide-ranging benefits from people analytics platforms. These include hiring more suitable employees for better retention, identifying key-asset employees who may be at risk of departing the organization, measuring the effectiveness of training and reducing absenteeism.

“It’s vital for senior living organizations to find better ways to attract and retain good people. People analytics may be one viable solution,” says Julie Rupenski, president and CEO of MedBest, which does senior living executive recruiting. She also worked in operations in the aging services field for many years. “What worked to attract, acquire and retain talent a few years ago may not work today,” she says. “Decisions regarding talent are now becoming more data-driven.”

In a blog post in May, Rupenski cited Forbes data that 69% of companies in all sectors are building integrated databases necessary to launch a people analytics platform. This is up from 10-15% of organizations surveyed in recent years. Despite this rapid evolution, she observed that the aging services field has been slow to adopt people analytics.

“What worked to attract, acquire and retain talent a few years ago may not work today. Decisions regarding talent are now becoming more data-driven.”

There are barriers, not the least of which is that people don’t like change. According to Harvard Business Review, employees feel threatened by AI due to a loss of control, including feared job loss. Advocates maintain that AI applications perform mundane, repetitive tasks that humans don't like doing and in which they are prone to making errors. For example, consider a radiologist who needs to read 100 mammograms at one sitting to find the one or 2 that may indicate an early-stage, treatable tumor. AI-assisted decision-making is forecast to leave more time to do things that people are better at, such as emotional intelligence and creativity.

AI applications are not a short-lived trend. Forecasts say that spending on machine earning and AI will more than quadruple from the $12 billion in 2017 to $57.6 billion in 2021. One study found that organizations that don’t implement “intelligent automation” by 2020 risk irrelevance, that planning needs to start now and be conducted with employee empathy and education. Another analysis found that people analytics is already a priority for 46% of HR departments, with another 32% expected to make it a priority in the next 12 months.

People analytics is sometimes also called talent analytics. Such platforms can replace gut feeling, which can be subject to bias, with statistical fact. One expert, Erik van Vulpen, co-founder of Analytics in HR, acknowledges that no predictive analytics can peg human behavior (as opposed to diagnosing a tumor) with 100% accuracy. But, van Vulpen maintains that even if an HR AI platform can achieve only 40% accuracy, that performance is better than what humans can deliver on their own.

Getting the Data Right From the Start

The vital consideration in people analytics is that the big data used to formulate AI-decision making must be absolutely sound. A recent Deloitte analysis found that “analytics maturity is not possible without data accuracy, security and consistency.” An HR department must also have strong data-literacy skills to make use of people analytics.

According to Baskaran Ambalavanan, principle consultant for Hila Solutions in Irwin, CA, and a member of the Technology Expert Panel for the Society for Human Resource Management, people analytics can help answer valuable questions about employee culture in support of an organization’s business goals.

"What is the relationship between employee engagement and employee turnover?" asks Ambalavanan, citing an example: He works with companies to help formulate both the right questions that AI platforms can answer, and to create the databases to provide the answers. "Everything is cost-driven, and it [AI people analytics] can provide valuable logistic insight, including labor costs. This impacts revenues."

The vital consideration in people analytics is that the big data used to formulate AI-decision making must be absolutely sound. An HR department must also have strong data-literacy skills to make use of people analytics.

Depending upon the size of the company and to what extent people analytics are deployed, Ambalavanan says that a 10% labor savings with the right AI strategy is possible. As an example, he cites recent literature describing how Jet Blue applied a people analytics tool to decrease absenteeism by 12%. He says the demand by larger employers (with 5,000 to 6,000 employees) for people analytics has definitely been increasing in the past few years. But he adds that the adoption of AI people analytics is, first and foremost, defined by top leadership commitment, no matter the size of the organization.

Ambalavanan notes that most of the cost in using people analytics is in creating the data files on which the platform operates. He said that this could run in the high 5 figures to 6 figures for a small-to-medium size organization, although he stresses that this is a rough estimate very much dependent on what information an employer is seeking from an AI platform.

“People analytics is a good tool, but I don’t think it will completely replace people in HR,” he adds.

Any employer needs to get the implementation and roll-out of people analytics right the first time. As Rupenski notes, as organizations collect more personal and business data about their employees, there’s a risk with data security as well as “big brother” ethics issues.

But there’s an upside for employees, as well. AI insight can provide HR new insight into employee career dissatisfaction, unhappiness with poor management and low workplace morale, according to Insights for Professionals. Responding to such factors to drive organizational transformation in support of business goals is at the very core of big data and machine learning. People are the most complicated part of any organization, and their care and management are uniquely suited to analysis and prediction.

According to Josh Bersin, an HR, talent management and leadership expert who frequently writes about people analytics for Forbes, HR managers are just starting to get the hang of AI analytics. He maintains that this differs from the past, when HR managers spent too much time measuring HR and labor/development spending, rather than evaluating which HR programs were adding value.

For any aging services provider, the imperative is even more vital: to deploy people analytics in the quest for associates with both the right combination of performance and commitment to caring for others.

John Mitchell is a writer who lives in Cedaredge, CO.