Using hard data for the softer side of banking

Advances in people analytics offer new ways of helping employees thrive.

For years, financial services providers have been analyzing customer data to improve product development, marketing and fraud prevention. But more and more, they are analyzing employee data to enhance the “softer side” of their organization.

Employing people analytics to pinpoint gaps can improve recruitment, retention, culture and more. Applying a data-driven lens to human resources can also reveal how high-priority initiatives are moving the needle on diversity, equity and inclusion (DEI).

“What gets measured gets done. We can’t assess whether we’re improving if we don’t have metrics on it and track it over time,” says Molly Duvall, executive vice president, human resources, at FirstBank, a $24.4 billion-asset institution in Lakewood, Colorado.

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By slicing and dicing data by demographics, region, job function, tenure and other variables, an organization can provide more specific action plans, says Amy Johnson, associate experience officer and vice president at the $23 billion-asset Old National Bank in Evansville, Indiana.

“For example, someone who works on the front line may have a different experience from that of someone in the back office, so now we can review the data more clearly to make sure we’re homing in on gaps in employee experience that we may need to shore up,” Johnson says.

Providing hard data and analysis about employees also boosts the credibility of HR as a strategic partner to the business, says Nick Patriciu, vice president, human capital analytics and consulting at the $498.9 billion-asset Truist Bank in Charlotte, North Carolina.

“Conversations with business leaders, more often than not, begin with a review of basic workforce statistics, which in turn leads to improved questions, a more productive conversation and, ultimately, improved outcomes for the business,” Patriciu says.

Compelling new use cases for HR data

A big push within people analytics in the past several years revolves around DEI—not just reporting representation, but looking beyond the numbers to determine the reasons why there might be more attrition among some populations than others, and what interventions can make positive changes, says Gene Pease, founder and CEO of Mighty You, which makes employee goal and feedback software.

To better understand DEI within different areas of the organization, Pease says, banks are using HR data they are legally required to collect – including gender, ethnicity and the kind of work they do – to try to generate greater buy-in for resource programs and other actions that can drive measurable change.

To improve employee onboarding, Old National uses analytics to gain specific insights from the bank’s new-hire lifecycle surveys administered three times in an employee’s first 90 days, Johnson says. The bank then measures the onboarding experience by job function and by region to identify gaps at critical checkpoints.

Analytics can also gauge how well new employees mesh with a bank’s culture, says Benjamin Granger, senior scientist at Qualtrics’ XM Institute in Provo, Utah. Many banks measure this against the organization’s stated cultural values, such as accountability, excellence in service and collaboration. In other cases, banks define culture as how employees behave and how they interact with one another.

“They use data analytics to understand what may be keeping them from engaging in positive behavior towards each other and also towards customers—so the metrics within the analytics are focused on identifying the barriers to this,” Granger says.

Decisions based on the right datasets

The first step is understanding the availability and quality of data that a bank has in its human resources information system, says Rayna Edwards, principal and senior workforce strategy consultant at Mercer in Atlanta. Then the data must be sorted, compiled and structured to ensure that analyses are based on relevant and accurate information.

FirstBank enhanced its data tracking so the bank could create a more robust view of its talent pool and career paths, Duvall says. Specifically, the bank needed system fields to be set up with a longer-term outlook, so the data could be used beyond the near term. System changes can also impact how data is displayed down the road.

“For example, a company restructure might impact turnover reporting and we needed to be mindful of that,” she says. “We also have opportunity for improvement in terms of tracking skills, education and certifications of our workforce.”

Keep privacy and consistency in mind

It’s essential that employee data spans the entire organization, and is collected on a continuous basis, Cournoyer says. Consistent data gathering also accelerates data relevancy and allows corporations to work on proactive prevention initiatives.

At FirstBank, there was a need for several iterations of the data after the bank migrated its HR data from an in-house mainframe to a cloud-based system hosted by a vendor, Duvall says. This included changing the way the bank tracks information, refining it and ensuring the new cloud-based system can “talk” to other systems.

Banks must also be mindful about employee privacy, Granger says. “We have to be careful about how much information we share about employees or else we’ll lose their trust. They may shut down for fear they’ll be penalized for speaking out, or they may leave the company altogether.”

Much planning and revisiting goes into making sure people analytics can significantly improve the “softer” side of banking. If done thoughtfully and acted upon accordingly to make needed changes, banks will be rewarded with more engaged employees who will want to stay longer and grow along with the bank.

Katie Kuehner-Hebert is a contributing writer to BAI Banking Strategies.

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