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Digital Experience

From Fragmented Dashboards to a Unified Measurement Framework

Unifying measurement definitions, eliminating dashboard sprawl, and building an implementation-ready analytics framework for a multi-brand QSR company.

Role

Strategy Advisor

Duration

Part of 6-Month Engagement

Industry

QSR

Focus

Measurement & Analytics

The Challenge

A multi-brand QSR company had a measurement problem hiding in plain sight. They had plenty of dashboards, but none were comprehensive, none served as a source of truth, and many weren't accessed by the right people or updated regularly.

Across brands, teams used different definitions and measurements for the same things. Leaders had conflicting opinions about which metrics mattered. The digital team couldn't connect their work to business goals, and without alignment on what to measure or why, prioritization was driven by opinion rather than evidence.

Unified
Measurement definitions aligned across all brands
100%
Of metrics tied to OKRs and business outcomes
End-to-end
Implementation plan delivered with dashboard specs and review cadence

What I Did

I interviewed every leader who had a stake in digital measurement, collecting the metrics each team needed and documenting how they were currently defined and used.

  • Identified duplicates and overlaps across brands, reconciled conflicting definitions, and established a single set of standardized measurements
  • Tied every metric to OKRs and business outcomes, pushing back on vanity metrics that didn't connect to goals
  • Defined a process for requesting data from the analytics team and for creating new dashboards
  • Worked with the insights team to prepare them for the new request process, and helped the data dictionary team make updates
  • Specified what dashboards should exist, what each should include, how often they should be updated, and who should have access
  • Delivered a full implementation plan with periodic review cadences, handing off a ready-to-execute framework before the engagement concluded

The Frameworks

I created two core frameworks to guide how metrics were categorized, prioritized, and organized into dashboards.

The Indicator Spectrum

Classifying metrics along a spectrum from effort to outcomes to insights — and prioritizing dashboard data starting from lagging indicators mapped to business goals.

Inputs
Effort Metrics
Measuring the volume or intensity of resources, effort, or actions invested to drive results.
Emails sent Offers created Ad spend
Leading Indicators
Predicting Future Success
More immediate signals that suggest potential success or failure by indicating trends that precede outcomes.
Traffic Engagement Open rates Click-through rates
Lagging Indicators
Measuring Past Success
Outcome metrics that show actual performance after the fact and align with KPIs that track business success.
Sales Conversion CAC ROI CLV
Insights
Interpreting Cause & Effect
Interpretation that connects inputs, leading indicators, and lagging indicators to explain why results occurred and provide actionable takeaways.

The Metrics Hierarchy

Grouping metrics by purpose to define dashboard types and guide prioritization when requesting or building dashboards.

KPIs
Key Performance Indicators
Top-level metrics that reflect overall success of the business; typically evergreen health metrics that are always monitored.
PPIs
Performance Progress Indicators
Indicators that track progress towards achieving specific OKRs; often provide early signs of improvement or potential problems.
DPIs
Detailed Performance Indicators
More granular details about specific areas of operations for insight into day-to-day performance.
Supporting
Contextual Data
More nuanced data like breakdowns by region, segment, or product type; help explain trends in PPIs or DPIs, but aren't regularly tracked.

The Transformation

Before

  • Different brands using different definitions for the same metrics
  • Dashboard sprawl with no source of truth
  • Dashboards not accessed by the right people or updated regularly
  • Leaders disagreeing on what to measure
  • No process for requesting analytics or creating new dashboards

Delivered

  • Unified measurement definitions across all brands
  • Every metric tied to OKRs and business outcomes
  • Dashboard specifications with ownership, access, and update cadences
  • Defined processes for data requests and new dashboard creation
  • Full implementation plan with periodic review schedule

The Outcome

The engagement produced a comprehensive, implementation-ready measurement framework that the team could execute on after handoff. Leaders across brands were aligned on what to measure and why, with standardized definitions replacing the inconsistencies that had made cross-brand comparison impossible.

The framework included dashboard specifications, data request processes, a updated data dictionary, and a periodic review cadence to keep measurement aligned with evolving business goals. The team was positioned to move from fragmented, opinion-driven reporting to a unified, outcome-focused analytics practice.

Key Takeaways

Alignment before dashboards

More dashboards don't solve a measurement problem. If leaders can't agree on definitions, no amount of reporting will create clarity.

Talk to the people, not the data

The framework came from interviewing every stakeholder who mattered. Understanding what each leader actually needed revealed the overlaps, gaps, and vanity metrics hiding in the system.

Design for handoff

A framework only works if the team can execute it after you leave. Implementation plans, process definitions, and review cadences make the difference between a deliverable and lasting change.