Three pillars of unlocking HR data for better workforce planning

The federal government is currently facing a number of challenges in the sphere of human resources. Improving diversity, equity, inclusion and accessibility is a major goal for agencies. So is employee experience. The federal workforce is rapidly aging, experts have been predicting a “retirement tsunami” for years now, and younger generations largely aren’t clamoring to take their place. And even if agencies could start attracting millennials and Gen Z into public service, they’d have to then figure out how to transfer the massive amounts of institutional knowledge they stand to lose as Baby Boomers age into retirement. The good news is, agencies have the right tool in their toolbox to help them address these challenges. They just have to learn how to leverage it properly.

That tool is HR data.

“Where HR was simply a function, HR data was more of a mystery. The data was in a system, and employees didn’t have access to their own data, they had to work through an HR liaison to get to it,” said Eric Laychock, KPMG managing director. “But with current technologies that enable the capabilities to actually use data to make business-driven decisions, leadership can make a lot of improvements in how they manage organizations in the federal space.”

There are three major pillars to leveraging data to address agency HR challenges effectively. They are:

1. Standardization,
2. Availability and
3. Accuracy.

The problem with HR data currently is that much of it is siloed. Payroll data is in one system, time and attendance in another, training in a third, and so on. Having all of that data separated makes it much harder to draw correlations and links between various elements. It’s even worse in larger departments, which may have multiple HR departments. Standardizing this data across departments will facilitate knocking down those silos and linking the data to enable insights. It will also ensure everyone is on the same page and having meaningful conversations and outcomes when talking and reporting on HR data.

Once data is standardized, it can then be made available to the entire workforce. If employees have access to their own data, and the ability to make certain changes – or even flag inaccuracies – that has multiple positive effects. First, it removes HR as the gatekeepers of the data, streamlining processes that cause backlogs in updating the data, which is one of the biggest barriers to accuracy.

For example, if an employee gets married and requires a name change, providing a self-service option allows that update to be made much quicker. That reduces the burden on HR professionals, shrinks the backlog, and ensures the data is more accurate and up to date. In fact, allowing employees access to their own HR data is often the fastest and easiest way to improve data accuracy. It also empowers the employee, improving their experience when interacting with HR.

And employee experience is an important element to attracting younger generations into the workforce.

“With millennials coming in a surge into the workforce, they expect the same features and interaction as we have as consumers. So how we buy goods from apps on our smart phones, that’s how they expect to manage their HR processes,” Laychock said. “But I think giving the end user, the employee, access to their data, that’s no longer a perk; that’s expected, from a millennial perspective coming into the workforce.”

And that’s not all millennials are looking for. Laychock said around 50% of millennials are actively looking for employers who have DEIA initiatives. And data can help enable those.

First, agencies looking to improve DEIA – or really any HR-related aspect of their business – need to use their data to establish a baseline. Where do things currently stand? The data to accomplish this could be drawn from a number of places, including demographic data or employee feedback drawn from places like the Federal Employee Viewpoint Survey. Then agencies need to determine what their goals are.

“DEIA goals and initiatives should be linked to the priorities of the organization. It’s going to be hard to come out of the gate and say, ‘we’re going to achieve this goal or initiative’ without first understanding where you currently are in relation to it,” Laychock said. “To achieve this level of understanding, accurate data is required, which requires that data clean-up metrics have to be baked into everything you do moving forward. If you do something related to recruitment, you should be able to capture accurate data there.”

This is known as building a data maturity model, a clear path from baselines to goals, with metrics for measuring improvement along the way. The first step is assessing to understand the baselines of the three pillars of standardization, availability and accuracy. Once an agency knows where it stands, it will be able to come up with a clearer vision of where it wants to go.

“And then from there, it’s how do we use that data to drive answers to the questions, problems, and future scenarios we have?” Laychock said. “That really aligns to the strategy of the organization. Are they looking to plan for the future? Are they looking for diversity, equity, inclusion and accessibility? Depending on the strategic priority of the organization, that’s where you can start to look at certain demographics and attributes of your workforce. Finally, organizations determine how to take that data and really make those decisions around workforce planning, and planning for the future of work.”

By learning how to properly leverage their HR data, federal agencies can begin to make real progress on hiring, retention and DEIA goals, setting themselves up for the workforce of the future.

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