How do you measure success when your organization has never done this before?
In this conversation, we explore how a newly formed division within an enterprise QSR partnered with Analytic Vizion to build their analytics foundation from scratch during a major expansion into new territories. Without historical data, established metrics, or clarity on ownership, the organization needed to quickly stand-up analytics capabilities that would support executive decision-making.
Auria Morrow shares how her team approached this challenge: aligning stakeholders, navigating ambiguity, and building a flexible data architecture that evolved with the organization’s maturity. For data and analytics leaders tasked with enabling insight in the midst of transformation, this story offers practical strategies and encouragement.
The Challenge
An enterprise QSR launched a new business division aimed at expanding its service offerings. While the broader company had mature data capabilities, this new arm had no defined metrics, limited data infrastructure, and no established reporting frameworks.
They faced a number of compounding challenges:
- No baseline data or existing KPIs to measure success against new strategic goals
- Inherited pipelines and tooling that didn’t fully align with the division’s unique needs
- Unclear data ownership and business logic, requiring relational discovery across departments
- A small, overextended internal analytics team, unfamiliar with modern tooling and architecture
- Urgent executive demand for insight, despite the absence of foundational capabilities
The stakes were high, leadership needed clarity to guide the new initiative, but the division lacked the structure and alignment to deliver actionable insight. Without a clear analytics strategy, the risk of misalignment, inefficiency, and missed opportunities loomed large.
Our Approach
Analytic Vizion engaged as a collaborative partner to guide the division from ambiguity to clarity. The team began by facilitating stakeholder conversations to define what success looked like, identifying key questions the division needed to answer that were distinct from the parent organization. They focused first on relationships: understanding who had domain knowledge, aligning on business logic, and clarifying ownership of metrics.
From there, the team supported the client with hands-on delivery, designing scalable data pipelines and dashboards. They used familiar tools at first to reduce change fatigue, then introduced modern platforms as the foundation matured. The guiding principles were flexibility, alignment, and progress over perfection.
The How
The project unfolded with intentional pacing. Analytic Vizion implemented a “crawl-walk-run” methodology, beginning with existing tools (e.g., Alteryx) inherited from the legacy organization. This minimized disruption for analysts and allowed early wins. As stability increased, the team migrated workflows to more modern platforms (e.g., Databricks), unlocking automation and scalability.
Key technical and strategic components included:
- Discovery Workshops: To define metric priorities and build alignment across stakeholders.
- Relational Mapping: Identifying key data owners and documenting business logic to avoid confusion and duplicate effort.
- Iterative Documentation: Creating a living record of decisions, data lineage, and rationale to support sustainability and onboarding.
The mindset was shaped by two principles:
- Fail Fast – Try, learn, and adapt quickly.
- What’s Now, What’s Next, What’s Later – Prioritize immediate needs while planning for scalable evolution.
Tools & Technology
The Results
The new division progressed from having no analytics foundation to operating with clear, actionable insights that supported real-time decision-making. With Analytic Vizion’s guidance, the team defined key performance questions, aligned stakeholders around metric ownership, and implemented dashboards that reflected the unique goals of the new business line.
Key outcomes included:
- Clear alignment on what to measure and why, resulting in a focused set of metrics tied to the division’s strategy
- Deployment of dashboards and data pipelines that enabled visibility into performance where none previously existed
- Stronger relationships between data and business teams, built through intentional discovery and documentation
- A seamless transition from inherited legacy tooling to a modern platform, rolled out at the right pace for the team’s maturity
- A flexible analytics infrastructure designed to grow with the division as its needs evolved
Leadership gained confidence in their ability to make informed decisions about the division’s progress, while analysts were equipped with sustainable tools and processes that reduced rework and supported faster delivery.
Key Takeaways
Start with Relationships, Not Tools
Aligning people around questions, data ownership, and decision logic is the foundation for analytics success, especially in new environments.
Document As You Go
Building a living record of metric definitions, business logic, and data sources ensures continuity and reduces risk as the project evolves.
Match Tooling to Maturity
Begin with what the team can support today. Scaling too soon adds unnecessary complexity and risks failure before value is delivered.
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