The Challenge

A multinational consumer goods company operating in hundreds of countries manages a highly complex data and technology ecosystem spanning thousands of systems. The organization struggled with persistent “metadata pockets” and limited enterprise-wide standardization, making it difficult to connect knowledge and information across disparate business units and geographies. The company’s leadership lacked an understanding of potential return on investment (ROI), making it challenging to justify investment, resulting in semantic use cases confined to isolated internal pilots. AI adoption was similarly constrained; solutions were not designed around end-user workflows, and executives lacked a clear, prioritized path for where to invest next to deliver measurable value.

These challenges created friction across core business processes. Analysts spent significant time locating, validating, and procuring data before analysis could even begin, slowing decision-making and increasing the cost of reporting and insight generation. Critical knowledge assets were difficult to find, tacit knowledge was frequently lost during organizational or individual transitions, and AI initiatives failed to gain traction due to weak organizational context and unclear use cases. This contributed to overlapping technology investments and avoidable vendor lock-in.

The company engaged Enterprise Knowledge (EK) to help assess its current semantic maturity, identify gaps against industry best practices, and define a roadmap and supporting business case to reach its target state maturity. They also needed a practical path toward a “North Star” architecture that would enable scalable semantic solutions tied directly to tangible organizational benefits.

The Solution

EK conducted a six-week assessment using our proprietary Semantic Layer Maturity Benchmark, built on insights from over 150 client engagements, to evaluate the client’s current state, across Vision, Strategy, ROI, Knowledge Assets, Semantic Models, Tooling & Architecture, and Operating Model. EK also delivered a North Star Architecture and a Semantic Design Framework to align semantic capabilities with real business workflows and measurable outcomes.

Within that six-week period, EK completed an accelerated two-week stakeholder engagement effort to gather input from business and technical teams through interviews, documentation review, and analysis of architecture artifacts. This discovery work ensured the assessment reflected real business workflows, end-user requirements, and implementation constraints.

Based on these findings, EK defined three priority use cases to anchor the current and target states, ensuring the roadmap focused on practical next steps that could demonstrate value quickly while supporting long-term scalability.

At the end of the engagement, EK delivered a solution including: 

• A Benchmark Assessment & Gap Analysis Report on the current semantic maturity and information management practices.
• A Semantic Design Framework.
• A North Star Architecture for an integrated, future-ready data fabric and enterprise knowledge graph.
• A Scalable Implementation Roadmap, including a phased evolution plan to progress toward the North Star architecture.

The EK Difference

Using EK’s proprietary Semantic Layer Maturity Benchmark, the team conducted a targeted evaluation of the organization’s semantic capabilities and maturity, then paired findings with AI readiness insights and a structured evaluation of target content and metadata to confirm foundational assets were prepared to support AI initiatives.

A key component of the engagement was reporting findings to leadership and aligning five business leads to validate priority use cases, address cross-functional considerations, and build buy-in for implementation. This process ensured recommendations were grounded in business needs and truly valuable to our client.

A primary focus of the engagement was linking semantic initiatives to tangible metrics. By tying recommended capabilities to five key business metrics, EK demonstrated exactly how they reduce manual effort, increase asset reuse, and sharpen decision-making. EK also provided operating model recommendations to support sustained scale, including guidance on ownership, governance workflows, adoption enablement, and reducing duplication across business units while preserving necessary regional flexibility.