Productizing Business Capabilities as a Foundation for Data Mesh Governance

In previous discussions, I explored how productizing business capabilities helps streamline enterprise architecture by creating well-defined domain boundaries, clear ownership, and a shared common language across business and IT. This structure is similar to Domain-Driven Design (DDD) in software development. However, its impact goes beyond building applications—it also changes how data is managed in a Data Mesh approach.

In many organizations, centralized data governance models struggle to account for domain-specific regulatory and risk controls. Different business areas operate under unique regulatory frameworks, making a one-size-fits-all approach inefficient. Business Risk and compliance requirements should be embedded within the domain (or domain areas) rather than enforced centrally. Productizing business capabilities ensures that risk and regulatory considerations are organically integrated into domain governance, with capability owners (Product Managers) taking full responsibility for risk and compliance within their domain.

This approach allows central data governance to focus on technical aspects such as product interoperability, metadata management, and security policies, rather than enforcing domain-specific business logic from a central enterprise/IT team.

In this blog, I explore how business capability productization provides an ideal foundation for data governance in Data Mesh environments, ensuring that data remains domain-driven, well-governed, and business-aligned. (Business consistency comes with the productization itself, so it is excluded from this benefits list)

Business Capabilities as Domain Boundaries

Business capabilities define what a business does, independent of organizational structures and IT systems. When productized, (at the domain (L1) or domain area level (L2)) these capabilities are grouped into business-aligned products, each managed by a Product Manager. This naturally establishes clear domain boundaries, similar to DDD’s bounded contexts.

Within these business domains:

• A shared common language lives, reducing misunderstandings between business and technology teams.
• Compliance and risk are embedded into the product lifecycle. Product Managers act as business capability owners, which means they not only own the business logic, but all side requirements to operationalize it. Regulatory frameworks and risk controls are defined at the domain/domain area level= Product level, rather than enforced by a central compliance team.

This model also organically aligns with the Data Mesh deployments, where each domain owns and governs its own data products and lifecycle choices.

Extending Business Products to Data Products

In a Data Mesh architecture, data is treated as a product and is owned by the teams who understand it best. These are the teams operating in particular business domains. However, this requires a structured approach to domain-driven data governance.

By aligning data products as sub-products of business products, we ensure:

1. Clear Ownership: Since Product Managers already oversee regulatory, risk, and compliance aspects of business capabilities, they are best positioned to define data governance policies within their domains.
2. Domain-Driven Compliance: Rather than applying a one-size-fits-all governance model, each domain enforces domain-specific compliance rules relevant to their business area.
3. Seamless Integration with Business Operations: Data products align with the business processes they support, ensuring that data governance and regulatory requirements evolve with business needs. Compliance requirements such as risk thresholds, regulatory mandates, and data access policies are organically embedded. Central data governance teams no longer dictate business logic, allowing domain teams to enforce business context specific rules rather than applying catchall policies.

The Role of Product Managers in Data Mesh Governance

A key advantage of productizing business capabilities is the empowerment of Product Managers to take responsibility for data governance within their domains. Their responsibilities may include:

• Defining data ownership, lifecycle, and access policies for their domain.
• Ensuring that domain-specific regulatory requirements are enforced at the data level.
• Collaborating with central Data Governance teams to adhere to enterprise-wide security and privacy standards.
• Managing data-sharing agreements with other domains while maintaining data sovereignty and agreed enterprise architecture principles.

However, this does not mean Product Managers need to be highly technical or have deep expertise in data engineering. Just as they rely on legal, compliance, and risk teams for regulatory matters, they will also delegate technical decisions to engineering teams.

By making data governance a natural extension of capability ownership, enterprises can balance agility with compliance while removing unnecessary business logic from central data teams.

Conclusion

Transition to Data Mesh from traditional data management practices requires more than just decentralizing data ownership. It also demands a structured governance model that ensures data remains compliant, secure, and business-aligned. Productizing business capabilities provides a natural framework for this governance, enabling:

• Domain-driven ownership of business capabilities and data.
• Regulatory alignment at the domain level, reducing reliance on centralized compliance mandates.
• A lighter-weight, agile, enterprise-wide governance layer focused more on technical interoperability, rather than enforcing business rules from the top down.

By treating business capabilities as products and embedding data products within them, organizations can achieve a scalable and fully federated data governance which is critical for successfully implementing Data Mesh at scale.