Strategic decision-making practices in HR rely on accurate and accessible people data for talent acquisition, performance management, employee engagement, compliance, and more. Plus, having a “clean” data foundation is an imperative to take advantage of AI-driven tools. To set itself up for future success and better service and manage its over 7,000 employees around the world, U.S.-based Edgewell Personal Care embarked an 18-month-long project to improve its HR data quality within its SAP SuccessFactors solutions.
Edgewell’s portfolio of more than 25 well-known personal care brands, including Schick, Banana Boat, Wilkinson Sword, and Wet Ones, drove $2.25 billion in net sales in 2024. The company relies on a people-first culture that enables the right environment for employees to be efficient and the company at large to “win the shelf,” as Colin Emery, director of Global HR Systems at Edgewell, puts it.
In 2022, Emery was tasked with establishing a People Analytics function at Edgewell, but he quickly realized that the underlying data he needed was inaccurate. “Our system of record was no longer the system of record. We didn’t actually have one,” Emery explains. At that time, the company’s HR data accuracy was just 37% for key data fields within the Position and People Profile.
Since Edgewell was formed in 2015, Emery says, it has relied on the “infinite configurability” of SAP SuccessFactors solutions to scale, systemize, and standardize the company’s HR systems across the world. While the solutions were working as designed, the data housed in them wasn’t being maintained properly, causing a backlog of inaccuracies to flow downstream. “It was clear that the quality of our data within SAP SuccessFactors was less than perfect in some parts of the world, particularly in countries where we don’t have SAP SuccessFactors Payroll integrated,” he says.
Knowing that high data quality is crucial for effective decision-making, reporting accuracy, a painless user experience, and future innovation—but not having the budget or time to engage external resources—Emery decided to develop Edgewell’s methodology in-house to tackle the issue.
Upskilling to establish HR data champions
After identifying the priority data fields that needed to be cleaned and maintained to have the most impact on data quality, Emery turned to the people who owned and best understood the data: the HR business partners (HRBPs). To ensure the success of the data quality project, the HRBPs needed to buy in. This required a mindset shift and significant change management, he says, since not all HRBPs felt responsible for maintaining the data in the SAP SuccessFactors solutions and some needed training to understand systemized HR processes.
To help with the transition, Emery established an HR data steward program to upskill Edgewell’s HRBP community. Designated data stewards receive weekly reports and are tasked with personally resolving the data errors or informing an appropriate colleague. They are trained on the causes and consequences of the inaccuracies and how to remedy them, empowering the data stewards to become experts and educate other HRBPs. Upskilling the HRBPs helped them shift from a reactive to a more proactive mindset, which was a critical factor in the data quality project’s success, Emery says.
Case in point: the number of data inaccuracies has decreased from 2,700 to just a handful. “It’s a tiny, tiny fraction of what it was,” Emery says. “That’s based on the fact that the HRBPs are getting it right the first time, instead of making errors that need to be fixed.”
The project began in the U.S. and eventually flowed to Europe, LATAM, and APAC. Now, Edgewell’s data accuracy consistently holds at 96%–97%, Emery says.
Quality data drives quality decision-making
The success of its data quality and data steward project is clear, and now Edgewell can reap the rewards of a clean HR data foundation. This has had profound effects on the reliability of the company’s HR reporting, for which Edgewell uses stories in SAP SuccessFactors solutions. “There’s a massive advantage to using stories when we’re using live, in-the-moment SAP SuccessFactors data,” Emery says, adding that the ability to send a link that is accessible based on existing role-based permissions makes sharing the data simple and fast. Edgewell uses stories to look at data around inclusion and belonging, leadership, tenure, talent acquisition, and more, sharing the insights with company leadership, HR leaders, and HRBPs.
This data-driven culture has helped Edgewell identify areas of improvement and make strategic HR decisions. For example, in looking at the data, the People Analytics team uncovered a short-term turnover issue for specific roles and locations. Based on this insight, Edgewell’s HR function created a new candidate experience to help improve and systemize recruiting and onboarding processes. Called “Joyful Journey,” the program also doubles as a way for the company to share about itself and attract talent to the organization. “We never would have known that was the right thing to do without the data,” Emery says. “That then led us to invest time, effort, and dollars in those processes, which immediately made a positive impact on short-term turnover.”
“Over the last three years, we have been providing data and explaining its importance by cleaning up the data within the system to make it more meaningful to us,” Emery adds. “For us, it’s never going to be data for data’s sake. It has to be about what the actions that this data suggests.”
Ready for the future
Not only does Edgewell’s impressive data quality equip its leaders with actionable insights, but it creates a strong foundation for the personal care company to take advantage of HR innovations, especially considering that many, like AI, require clean data to work properly. AI copilots and agents, like Joule, are only as good as the data they run on, which is why data quality and data governance initiatives are becoming business imperatives.
In that case, Edgewell is ahead of the curve. “When I started working on People Analytics three years ago, I knew that we had to focus on [cleaning up the data] first to prepare for super automation and the AI tools that were coming,” Emery says. “It will set us up in good stead for the next iteration of tools.”
Gillian Hixson is an integrated communications specialist at SAP.
