The Data Quality Navigator brings data quality into the business. It showed us that data quality does not have to be complex. It can be a lightweight, business-owned capability that is easy to manage and directly linked to real process impact.
Markus Mützel, Head of Enterprise Data Management, Evonik AG
The impact: Enabling business-owned data governance
With BearingPoint’s Data Quality Navigator (DQN), Evonik turns data quality into a business-owned capability rather than a mainly technical task. The solution reduces manual correction effort, speeds up rule creation, and lessens reliance on technical experts through low-code workflows. It also brings governance, monitoring, and correction into one central setup, making execution simpler and more efficient.
For Evonik, the benefits extend beyond faster processes. DQN provides a stronger foundation for long-term data governance and continuous improvement by creating clearer ownership, business-relevant KPIs, and more transparent decision-making. This gives Evonik a scalable, future-ready setup that helps sustain high data quality as a driver of long-term business success.
What we did: Implementing DQN as a practical route to cleaner data
BearingPoint introduced DQN as a practical way to make data governance accessible to the business, starting with material master data. DQN combined data profiling, best-practice validation rules from similar client projects, Evonik-specific rule implementation, and efficient correction in one structured workflow.
A key focus was enabling business users to take an active role in data quality management. Evonik configured rules directly in DQN’s low-code environment, reducing dependency on ABAP development and significantly speeding up implementation.
Beyond rule creation, DQN consolidated previously fragmented activities into a single integrated workflow encompassing rule definition, monitoring, incident handling, and autocorrection. This made ownership, progress, and business impact more visible and established a consistent framework for managing data quality as an ongoing business capability rather than a technical task.
The starting point: Moving beyond fragmented, IT-driven data quality
Evonik operates across multiple business units and regions in a complex IT and project landscape. Over time, data quality activities became fragmented across different systems, reports, and responsibilities. This made it harder to maintain a clear view of priorities, allocate effort effectively, and connect data quality issues to business impact. At the same time, many tasks still depended heavily on manual work, while governance processes lacked a practical way to involve business users directly in managing data quality.
Rule creation was one of the clearest pain points. Implementing and adjusting validations required repeated coordination with technical experts, increasing both effort and turnaround time. Evonik therefore needed a simpler, more business-focused setup that improved speed, strengthened ownership, and made data quality governance easier to execute in practice.
Evonik
Evonik is a global chemical company headquartered Germany and active in more than 100 countries. Through its combination of innovative strength and leading technological expertise, the company delivers tailor-made products and solutions that help customers strengthen their competitiveness while contributing to improvements in everyday life.
Its products and technologies address some of the most important challenges of the future. Examples include lipids for next-generation medicines, biosurfactants for more sustainable detergents, additives that support plastic recycling, and membrane technologies that help enable the energy transition.
