When the data exists, but the truth doesn’t
Most reporting problems do not begin in the dashboard. They begin underneath it: conflicting revenue definitions, inconsistent source data, unclear customer lifecycle rules, mismatched grains, and business logic scattered across spreadsheets, SQL, and BI tools.
The result is familiar. Finance, Marketing, eCommerce, and Analytics report different numbers. Analysts spend more time reconciling than analyzing. Leaders receive dashboards but still cannot get a confident answer.
Report Pantry fixes the reporting foundation first.
Reporting foundations built for implementation
Revenue Truth Sprint
Align critical revenue and customer definitions, reconcile key metrics across systems, and create an implementation-ready reporting foundation. Timeline: 5 business days after the fit check Final scope and fixed fee are confirmed after the Fit Check based on the number of systems, reporting conflicts, and required stakeholder alignment.
Deliverables:
- Canonical revenue logic
- KPI dictionary
- Customer and lifecycle definitions
- Revenue Truth Map
- Source-to-canonical field mappings
- Validation and reconciliation queries
- KPI status labels: Trusted, Review, or Blocked
- Prioritized Engineering Action List, when needed
- Executive delivery brief
Revenue Integrity Sprint
Everything in the Revenue Truth Sprint, plus analysis of revenue discrepancies, payment issues, discount leakage, cohort behavior, retention patterns, and attribution gaps—with the highest-value opportunities quantified and prioritized. Timeline: 7–10 business days Final scope and fixed fee are confirmed after the Fit Check based on data availability, analytical complexity, and the number of revenue questions included.
Deliverables:
- Everything included in the Revenue Truth Sprint
- Revenue discrepancy analysis
- Failed-payment analysis
- Discount and promotion analysis
- Cohort and retention analysis
- Attribution-gap diagnosis
- Financial-impact estimates
- Prioritized revenue opportunities
- Executive recommendations
Trusted Reporting Build
IMPLEMENTATION ADD-ON Implement approved definitions and reporting models in warehouse views, dbt models, or one BI semantic layer, with validation tests and handoff documentation. Timeline: 2-3 weeks Available after the reporting foundation has been approved. Final pricing depends on warehouse maturity, systems, implementation complexity, and review cycles.
Deliverables:
- Two to three core reporting-ready models
- Warehouse views, dbt models, or BI semantic-layer implementation
- KPI logic implemented in one BI environment
- Data-quality and reconciliation tests
- Technical documentation
- Business-facing metric documentation
- Implementation handoff
From disputed metrics to trusted decisions
Diagnose
Identify the decisions the business needs to make, the systems involved, and where definitions, logic, or reported numbers currently conflict.
Define
Establish canonical KPI logic, reporting grains, lifecycle rules, source mappings, calculation standards, and metric ownership.
Validate
Reconcile key numbers across systems, test for duplicates and missing data, and label each metric as Trusted, Review, or Blocked
Put It to Work
Turn the approved definitions into implementation-ready models, SQL validation logic, governance documentation, and a prioritized action list for Analytics and Engineering.
Built for businesses that have data—but not yet a dependable reporting foundation
Report Pantry works with growing eCommerce, subscription, customer, and digital revenue businesses whose data is distributed across multiple systems and whose teams need more consistent answers.
Different teams calculate or report the same KPI differently.
Revenue, customer, marketing, or retention data does not reconcile across systems.
You need trusted numbers and a clear action plan fast
The company needs reporting-ready definitions and models before investing further in dashboards, forecasting, attribution, or AI.
Senior analytics expertise, applied to complex reporting problems
I’m Abisola “Abi” Ayiloge, founder of Report Pantry and a BI and analytics leader with more than 10 years of experience helping businesses turn digital, eCommerce, customer, and revenue data into reporting they can use with confidence.
Across Johnson & Johnson, Kenvue, Merck, and other organizations, my work has included KPI strategy, forecasting, customer and subscription analytics, revenue reconciliation, semantic modeling, dashboard development, and analytical enablement.
At Johnson & Johnson, I led the development of real-time DTC sales and forecasting reporting that gave business teams a shared view of performance against forecast and the marketing-channel, traffic, conversion, and average-order-value drivers behind the results. The approach expanded across multiple consumer brands, and I worked directly with other analysts to help them build, validate, and maintain similar reporting. That work was recognized internally through a Bravo Award for its cross-brand impact and contribution to the team’s analytical ways of working.
I founded Report Pantry to apply that same discipline to a problem many growing businesses face: the data exists, but conflicting definitions, fragmented systems, and inconsistent reporting make it difficult to know which numbers to trust. Report Pantry helps companies establish the definitions, models, validation rules, and governance needed to turn that data into dependable business decisions.
Your next dashboard isn’t the first step.
Start with the definitions, logic, models, and controls that make every report—and every decision built from it—more reliable.