BearingPoint Netherlands’ Data Strategy & Management cluster helps organizations take that step: from isolated experiments to structured, scalable data and AI solutions. We design and implement future-proof data management solutions that embed data into strategy, organization, and daily operations. Not as a theoretical framework, but as a practical tool for compliance, scalability, and sustainable strategic business value. We explicitly approach data management not as an IT discipline, but as an organizational tool for governance, decision-making, and accountability.
In practice, we see that data is fragmented across systems and domains, that definitions vary by team, that data quality is inconsistent, and that data ownership remains unclear. This makes it difficult to scale initiatives, and decision-making often falls back on “gut feeling.” Meanwhile, pressure is mounting due to laws and regulations (such as CSRD, the AI Act, and GDPR), which require a demonstrably reliable and audit-proof data foundation. Our approach combines data management expertise with strategic and change management capabilities and is based on proven standards and maturity models such as DAMA-DMBOK, DMM, and DCAM. These have been translated into pragmatic steps that work in your context.
Our data management offerings: from strategy to implementation
Organizations differ in ambition, maturity, and context. Yet in practice, we see that the journey from experimentation to sustainable value almost always follows the same building blocks. Within the Data Strategy & Management cluster, we have bundled these into a cohesive portfolio of offerings that reinforce one another and help organizations grow in a targeted manner. Perhaps you have already taken the first step(s) and we can help you move forward, or perhaps you are just getting started and we can give you a flying start; our consultants have extensive experience with the various offerings.
-
Data Strategy & Maturity: direction and focus that is actually actionable
When organizations want to become “data-driven,” a shared direction is often missing: what does it mean for you, which principles guide decisions, and which initiatives truly deliver value? With Data Strategy Design, we help connect vision, governance, and execution into a roadmap that clarifies priorities and investments.
Sometimes the fastest way to accelerate progress is to bring people together. In a Data Strategy Workshop, we clarify ambitions, bottlenecks, and choices and create a shared understanding that accelerates decision-making.
And if you first want to get a clear picture of where you stand: the Data Maturity Workshop maps your current maturity level (using DMM/DAMA-DMBOK, among other tools) and translates this into a concrete improvement plan focused on impact.
Typical questions that fit this context: “Where do we really stand right now?”, “What choices do we need to make to scale up?”, “How do we prioritize based on business value?” - Data-Driven Sustainability: ESG from “must” to “can drive”
Sustainability reporting and ESG data management are a wake-up call for many organizations: data often turns out to be incomplete, inconsistent, scattered, and lacking clear ownership. That’s why we start with a Sustainability Data Readiness Assessment: a reality check on governance, quality, processes, and architecture, so you know what’s needed before investing in tools. Next, we support you with ESG Data Platform Integration & Automation: integrating and automating ESG data streams with a focus on reliability, traceability, and scalability. And when you’re ready to select or refine your tools, we’ll help with ESG Data Tooling & Requirements Definition: clear functional and data requirements that align with oversight, reporting, and decision-making.
Typical questions: “Is our ESG data audit-proof?”, “How do we become CSRD-ready without temporary fixes?”, “How does ESG become part of management?” - Data & Analytics Literacy: the accelerator that is often overlooked
Even with the best architecture, value remains unrealized if people cannot read, understand, and apply data. With the Data Management Introduction Workshop, we make data management tangible for daily decision-making and work processes.
With Data Maturity Workshops (literacy-focused), teams take data skills to the next level within their own context. To ensure this is embedded structurally, there is the Data Desk: a dedicated hub for questions, support, and advice, so that data usage accelerates and knowledge doesn’t get lost.
Typical questions: “How do we ensure that data is actually used?”, “How do we increase data literacy outside of IT?”, “How do we support teams without creating dependency?” - Data Target Operating Model: from ‘governance on paper’ to practicality
Scaling up often fails not because of technology, but because of organizational issues: roles are unclear, consultation structures are missing, and ownership remains a point of contention. With the Data Target Operating Model (TOM), we design the cohesive set of roles, responsibilities, meetings, and processes that fits your organizational context.
With Operational Design & Data Archetypes, we help you determine how data functions within your organization (e.g., as a product, source, or service) and what that implies for structure and collaboration. And with Control Frameworks & Role Structures, we ensure data management through clear first-, second-, and third-line responsibilities, including control and compliance mechanisms.
Typical questions: “Who decides on data?”, “How do we organize governance without bureaucracy?”, “How do we make data roles workable?”
- Data Quality Management & Lineage: Building Lasting Trust
Trust in data is not created by a one-time cleanup, but through structural management. With the Data Quality Navigator, we make data quality transparent, measurable, and manageable as a basis for accountability and improvement.
With Data Quality PDCA Implementation, we implement a continuous improvement cycle (Plan-Do-Check-Act) that includes quality rules, monitoring, and follow-up within the organization.
Typical questions: “Why don’t users trust our data?”, “How does data quality become part of processes?”, “How do we demonstrably meet audit/compliance requirements?”
Discuss your data strategy at theData Expo
In the run-up to the Data Expo, we’d like to share our vision on what organizations need today to ensure data initiatives deliver sustainable results. Would you like to explore in advance where your organization stands and which next step will yield the greatest return? Schedule an introductory meeting or speak with us during the Data Expo. We’d be happy to help you develop your data strategy, data management, and data governance—before pilots remain just pilots.
