Resources Success Story

Unifying Enterprise Data Across a Multi-Brand Portfolio with Snowflake for Fortune Brands

Fortune Brands Innovations Logo

As Fortune Brands Innovations evolved from a collection of independent businesses into a unified operating enterprise, a fragmented data environment held it back: each brand ran its own systems, tracked its own definitions of success, and saw only its own slice of the business. Fortune Brands partnered with Atrium to build a scalable enterprise data foundation on Snowflake, connecting insights across decentralized brands while preserving the speed each team needed to move.

Background

Fortune Brands Innovations, Inc. is a Fortune 500 home and security products company headquartered in Deerfield, Illinois. Its portfolio includes some of the most recognized brands in the industry: Moen, House of Rohl, Master Lock, and SentrySafe. The company employs more than 28,000 people and operates across a broad range of product categories, distribution channels, and business functions.

Technology

Snowflake

dbt

Tableau

The Challenge


Siloed data and duplicated effort across a multi-brand enterprise

Two years ago, Fortune Brands’ data reflected its history as a collection of independent businesses: 6 to 7 teams, each with its own systems, processes, and definition of success. BI efforts were duplicated, insights stayed siloed, and simple questions, on supplier performance, materials costs, or the broader business, took weeks instead of minutes.

The cost ran deeper than inefficiency. Executive conversations could stall over whose numbers were right, and responding to shifting trade and policy conditions took weeks of work just to reach a shared starting point. Previous consulting partners had tried and fallen short, leaving behind Data Vault missteps that slowed progress.

The Solution


A scalable Enterprise Data Vault built for a unified operating company

Fortune Brands partnered with Atrium to deploy a robust Data Vault architecture on Snowflake, replacing the gaps left by previous partners with a scalable foundation for enterprise analytics. At the center of the solution was a semantic data layer that became the backbone for Fortune Brands’ operating company transition. For the first time, the company had a single source of truth across brands, functions, and domains.

Key Elements

  • Enterprise Data Vault on Snowflake to unify data across brands, functions, and domains
  • Semantic data layer establishing standardized definitions and continuous data quality validation built directly into the pipelines
  • FAIR-aligned data products designed to be Findable, Accessible, Interoperable, and Reusable across teams rather than rebuilt from scratch for each new use case
  • Full data lineage providing traceability back to source across the enterprise

Early Proving Grounds

Two of the highest-priority use cases proved the platform’s value early: supply chain visibility and product quality analytics.

Supply Chain Visibility

Supply chain control towers gave the business strengthened visibility into key operational domains across the enterprise, the kind of cross-brand view that simply hadn’t been possible before.

Product Quality Analytics

Snowflake pipelines and Tableau dashboards streamlined the research process for product issues, surfacing a $2M savings opportunity and reducing the time analysts spent on issue research from roughly 30% of their workload to less than 3%.

The Impact

Faster decisions, measurable savings, and a foundation built to scale

With a modern enterprise data foundation in place, Fortune Brands is better equipped to connect insights across brands, reduce duplicated analytics work, and operate as the unified enterprise it is becoming.

  • $2M savings opportunity identified within the quality analytics workstream through Tableau dashboards built on Snowflake pipelines
  • Product issue research reduced from 30% to less than 3% of analyst time through streamlined workflows and governed pipelines
  • Unified visibility across decentralized teams through a shared semantic layer that enables consistent enterprise insights while preserving autonomy across brands
  • Rapid response to business conditions — what previously required weeks of manual work across brands can now be done with a few queries against consistent, trusted data
  • A scalable, repeatable architecture that establishes a model for future data products, analytics use cases, and cross-functional decision-making

The shift has enabled Fortune Brands to move from reactive, brand-level reporting to coordinated, enterprise-wide decision-making with the speed and confidence that a modern data foundation makes possible.

“

The Atrium team has expertly balanced making strategic, thought-leading recommendations while also being grounded in technical realities.

Chris Tambos VP, Data & Analytics
What’s Next

From data foundation to agentic AI

With the enterprise data foundation in place, Fortune Brands is turning its attention to the next frontier. The semantic layer, now a trusted and governed single source of truth, is becoming the shared language that connects AI models to business context.

The team is building toward agentic AI: systems that don’t just surface insights, but can act on them within governed workflows. Early work includes a multi-agent AI assistant supporting the quality team, built entirely on Snowflake and designed for accuracy and scale.

The foundation is in place. What comes next is intelligence.

Ready to build a modern data foundation?

Learn how Atrium helps manufacturing and consumer products companies turn Snowflake into a platform for visibility, speed, and AI-driven growth.

Learn More

Ready for Real Results?

Reach out to our team—dedicated to the metrics that matter most. We’re here to help you adapt and grow.