Harnessing analytics: How HR leaders are integrating AI, predictive tools for strategic advantage

With data and analytics continuing to rise in importance in organizational strategy, some HR leaders are still scratching their heads as to how and where they should deploy the newest tech. According to data from Zippia, 60% of HR departments are looking at investing in predictive analytics, with 47% keenly eyeing up AI.

“When we think about analytics, we start by looking at the underlying data,” says Danielle Bushen, Global Head of People Insights Data Governance at Sanofi. “How is it informing our policy design? Very often, what we see when we analyze the data is that it’s not delivering the best value inputs to our processes.

“Not only do we use analytics to inform policy design for our [people], we also use it to inform HR process design. How do we make this process as efficient and as predictable as possible?”

HR Tech Summit: Exclusive panel insight

This is where the continuous improvement aspect of analytics comes into play, something Bushen will be discussing at HRD’s upcoming HR Tech Summit Canada alongside other industry leaders.

In her panel - HR Analytics: Using data to deliver actionable intelligence – Bushen will look at how leading companies have successfully leveraged HR data to increase productivity and answer the most pressing questions from the C-suite such as how to:

• Put data to good use and deliver a coherent picture of gaps and solutions
• Use data to inform strategy in real time to respond to business needs
• Ensure that your data collection methods are producing high quality datasets

As technology continues to evolve at a rapid pace, for HR leaders the question becomes how can they best integrate new tools into already existing HR platforms with minimal fuss? For Bushen, she tells HRD that their existing systems don’t yet leverage AI extensively – they are actually based on processes that the organization might have set up years ago.

“New ways of working change the nature of the data structure itself,” she tells HRD. “Change management and diagnostics start when you look to overlay new technology. We spend a lot of time on the assessment of current state readiness and the maturity of the platforms to adopt new technology.”

For example, at Sanofi, they’re currently looking at organizational network analytics – a tool to visualize how communications, information, and decisions flow through teams across an organization. To prepare for that opportunity to leverage AI, they ensure that employees understand the ways in which their day-to-day workplace digital footprint is understood.

Transparency builds trust in AI and data

“It’s very much about exploring organizational capability - it's not about the individual. It's about understanding patterns in the workplace,” said Bushen.

“That said, this type of AI relies on accessing data that comes from processes our employees are pursuing every day in the workplace. We want to be transparent about that. And so we actually explain that business purpose. We pause and reflect on how to help people understand how their data is being used responsibly, and we make sure that we have that transparency. Because that's what builds trust in the employee relationship.”

Data governance is of upmost importance to both Sanofi and Bushen – so much so that in August of last year, Bushen took on the pioneering role of establishing a governance layer for people and culture.

“We really think about data governance in the HR context as being driven by people, enabled by technology, and supported by processes," she explains.

This approach underscores the belief that the business itself owns its data across various functions—from manufacturing and supply to R&D and clinical trials, and notably, HR. Bushen stresses that HR data isn't just housed within technological tools or transactions processed by payroll systems; it encompasses a broader responsibility.

"It's something that we have stewardship accountability for,” Bushen tells HRD. “We've focused a great deal on establishing a framework of the data that anchors that ownership with subject matter experts. They’re comfortable defining rules for their data capture methods. And that's a really important piece because people don't think about their data collection when it’s originated within a process.”

Ethical handling of employee data

Secure, ethical storage and provisioning of data to the right entities are crucial components of this strategy. Bushen adds that the importance of these foundational elements informs successful data usage, such as populating a Power BI or Tableau dashboard for leadership visibility.

"If you've done those first pieces right—around leadership, collection, quality, and storage, and ethics—then you are set up for success for consumption," explains Bushen.

Looking ahead, Bushen sees significant potential in integrating AI into HR to enhance the employee experience, particularly through a shift towards skills-based employment.

"This spans a whole bunch of areas, but the most notable one is probably skills,” she says. “In addition to that, we have a lot of grassroots work happening around our data governance framework – everything from augmenting our business data dictionary to establishing classification frameworks to update our master data, as well as the deprecation framework for legacy technology.”

Because, as Bushen points out, wardrobe management is a useful analogy for data and technology management - just as technology fashions evolve, so too must the data that is consumed by that technology.

"You need to be continually rejecting data that is now outdated, that doesn't really fit the business requirements anymore," she adds.

Want to learn invaluable insights from industry giants? Register for HRD’s upcoming HR Tech Summit Canada here.