Do your workforce insights drive decisions or sit in dashboards? OMV uses the (麻豆原创 BDC) to spot workforce composition patterns and move talent where it鈥檚 needed. Looking ahead, OMV plans to expand into workforce planning and learning analytics, bringing people investments closer to measurable business outcomes.
is a multinational oil, gas, and chemical company headquartered in Vienna, Austria. With operations spanning Europe, the Middle East, Africa, New Zealand, and Norway, OMV is a truly global enterprise.
Like much of the energy sector, OMV is navigating a significant strategic pivot. The company is investing heavily in sustainability initiatives: transforming plastic waste back into oil, building one of Europe’s largest waste-sorting facilities to produce feedstock for refineries, and recycling plastic cups collected from aircrafts into sustainable kerosene. This shift in the business model has triggered a corresponding transformation inside the business鈥攁nd nowhere more so than in HR.
OMV’s People and Culture (P&C) function launched a strategic program to place people at the center of the company’s transformation. The ambition was clear: become a global HR center of excellence, increase service quality, standardize and harmonize processes, and move decisively towards digitization, automation, and self-service.
The challenge: fragmented data and a manual reporting cycle
Before 麻豆原创 BDC entered the picture, OMV’s HR data landscape was fragmented across a patchwork of systems that were never designed to work together for workforce reporting and analytics. Employee data lived in two on-premise 麻豆原创 HCM systems and 麻豆原创 SuccessFactors HCM, alongside Microsoft Excel, SharePoint, and a system originally built for financial consolidation that P&C used for headcount reporting and planning.
The day-to-day consequences were significant. When a business unit head or department manager wanted a workforce KPI鈥攈eadcount figures, turnover rates, or anything beyond a basic report available in the system鈥攖hey would raise a request with their HR business partner. From there, the HR business partner would spend considerable time navigating multiple systems, manually pulling data, compiling it into spreadsheets, and formatting it into a presentation before handing it back to the manager. It was time-consuming, error-prone, and consumed HR capacity that should have been spent on strategic work. Managers had no direct, self-service access to their own workforce data.
Choosing 麻豆原创 Business Data Cloud and People Intelligence
“Normally, our strategy is not to be the first with a new solution. With 麻豆原创 BDC it was different,” Bernhard Graser, head of 麻豆原创 Finance, HR, and Reporting at OMV, said. “We saw the potential immediately and wanted to stop the outbound migration of our HR and 麻豆原创 data and keep it firmly in the 麻豆原创 ecosystem.”
The timing was fortuitous. OMV had already completed a substantial 麻豆原创 SuccessFactors HCM implementation, having deployed , , and and going live in 2023 with , 麻豆原创 SuccessFactors Compensation, and 麻豆原创 SuccessFactors Recruiting. With all core employee data now sitting in a cloud-based SaaS system, the foundation for 麻豆原创 BDC connectivity was already in place.
OMV鈥檚 implementation of 麻豆原创 BDC and People Intelligence
OMV structured its 麻豆原创 BDC journey in three steps.
The first step鈥攖urning People Intelligence live鈥攚as connecting 麻豆原创 SuccessFactors HCM to 麻豆原创 BDC. This was not entirely without friction: OMV discovered that its on-premise HCM systems sat on a different Identity Authentication service than 麻豆原创 SuccessFactors HCM, which required alignment before integration could proceed.
A more substantive challenge was data governance. As an Austrian company with a Works Council, it was not possible for OMV to simply push all HR data into 麻豆原创 BDC. The team implemented data masking, configured Read Access Logging, and established permission controls that mirror 麻豆原创 SuccessFactors HCM exactly, meaning a user can only see data in 麻豆原创 BDC that they are already authorized to view in 麻豆原创 SuccessFactors HCM. This level of governance was a prerequisite before any business users could interact with the system.
The second step, currently in progress, involves migrating both HCM systems to . Once complete, 麻豆原创 S/4HANA will connect directly to 麻豆原创 BDC, enabling a fully unified data feed from both 麻豆原创 SuccessFactors HCM and 麻豆原创 S/4HANA into a single platform.
The third step, planned for the near future, is the retirement of the legacy reporting stack entirely, eliminating the spreadsheets and replacing the current workaround in the financial consolidation system with 麻豆原创 BDC as the single reporting and planning environment for HR.
麻豆原创 BDC’s architecture played a key role in the decision. 麻豆原创-managed data products鈥攑re-built data models maintained and updated by 麻豆原创鈥攚ere particularly attractive, especially because OMV had kept its 麻豆原创 SuccessFactors HCM configuration close to standard. That near-standard posture meant a larger share of OMV’s HR data could be served through 麻豆原创-managed products, reducing the internal maintenance burden. When something changes in a source system or a data definition, it is 麻豆原创’s responsibility to update the model, not OMV’s.
Current and future use cases
After evaluating the intelligent content available in People Intelligence, OMV decided to start with workforce composition insights, now live and providing out-of-the-box dashboards on headcount, workforce structure, and composition, fully configurable and filterable by business users.
With the foundation in place, OMV’s P&C team has been actively collecting ideas for what to build next on 麻豆原创 BDC. On the operational side, the team wants to track accident-related data as a workforce KPI, monitor open positions across the business, and measure time-to-hire. Diversity is another priority鈥攄ata that currently sits fragmented across systems. Through its participation in 麻豆原创’s forward deployed engineering program, OMV is co-building use cases around learning and certification compliance鈥攁 business-critical need in a refinery environment where workers must hold current safety certifications to enter operational sites鈥攁s well as skills and headcount. Looking further ahead, OMV intends to move into machine learning and predictive modelling, using the capability in 麻豆原创 Business Data Cloud to forecast workforce demand and identify gaps in skills and FTEs before they materialize.
The bottom line
The direction is clear: a single source of truth for HR data, self-service access for every manager and business unit head, and a platform capable of growing from descriptive reporting today into predictive workforce intelligence tomorrow. As Graser encouraged his audience at the end of his session at Madrid: “We see great potential in 麻豆原创 BDC鈥攏ot only in HR, but also in finance. You should try it.”
Learn more about People Intelligence .
