Global Financial
Consolidation
How we unified 12 global business units into a single Power BI semantic model — cutting monthly close reporting from 4 days to 3 hours and saving $1.2M annually.
Client Context
A global manufacturing conglomerate operating across 12 business units in 4 continents engaged Garnet Grid to solve a critical visibility problem: their executive leadership lacked a single source of truth for financial performance.
Each division maintained its own reporting stack — a patchwork of Excel workbooks, on-premise SSRS reports, and legacy Crystal Reports. Monthly close required manually exporting and reconciling data from 7 different ERP instances, 3 separate chart-of-account structures, and 4 different currencies.
The existing process consumed the FP&A team's first four working days every month, delaying strategic decision-making and introducing reconciliation errors that averaged $340K in quarterly adjustments.
Four Days of Darkness Every Month
The CFO's team coined a term for the first week of every month: "the blackout." No real-time data, no KPI visibility, just spreadsheet reconciliation across time zones.
🗄️ Data Silos
Seven disconnected ERP instances across D365, SAP, and Oracle — each with different chart-of-account hierarchies, fiscal calendars, and currency denominations.
⏱️ Manual Reconciliation
FP&A analysts spent 4 full days every month exporting, transforming, and validating data in Excel. Intercompany eliminations alone required 6 hours of manual cross-referencing.
🔒 Security Gaps
Regional controllers could see all divisions' data. No row-level governance existed, creating compliance risk across EU data residency requirements.
📊 Stale Reporting
Reports were static snapshots — by the time the board saw them, the data was 5-7 days old. No capability for drill-through or ad-hoc analysis.
Unified Semantic Architecture
We designed a three-tier Power BI architecture that centralized all financial data into a single semantic model while preserving each division's autonomy and data ownership.
01 — Data Integration Layer
Azure Data Factory orchestrates nightly extractions from all 7 ERP systems, normalizing chart-of-account structures into a unified conformed dimension. Currency conversion uses daily ECB rates stored in a dedicated Azure SQL reference table.
02 — Semantic Model
A single Power BI Premium composite model spans 500M+ rows using DirectQuery for real-time actuals and Import mode for historical aggregates. Incremental refresh partitions ensure sub-30-second load times despite data volume.
03 — Row-Level Security
Dynamic RLS roles map to Azure AD groups, ensuring each regional controller sees only their division's data. The CFO's executive role provides a unified cross-BU view with drill-through to any division.
04 — Automated Distribution
Power Automate flows deliver paginated PDF snapshots to board members on the 2nd business day of each month. Data-driven alerts notify the CFO of any BU exceeding variance thresholds.
DAX Patterns & Model Design
The core challenge was computing intercompany eliminations and currency-adjusted P&L aggregations across 12 business units without sacrificing query performance. We developed a set of reusable DAX measure patterns that handle multi-currency consolidation at the calculation layer.
We also implemented a star-schema with 14 conformed dimensions, including a custom fiscal calendar dimension that handles 3 different fiscal year-end dates across the group. The model's partition strategy uses incremental refresh with a 2-year rolling window — only the current quarter refreshes nightly, while historical partitions remain cached.
Measurable Impact
The transformation was deployed in a phased rollout over 10 weeks. By Month 2, the CFO was running ad-hoc profitability analyses that previously required a week of analyst preparation.
| Metric | Before | After | Improvement |
|---|---|---|---|
| Monthly Close Reporting | 4 business days | 3 hours | ▲ 96% faster |
| Data Freshness | 5–7 days stale | Near real-time | ▲ Same-day |
| Reconciliation Errors | ~$340K/quarter | $0 | ▲ 100% eliminated |
| FP&A Analyst Hours | 160 hrs/month | 12 hrs/month | ▲ 92% reduction |
| Ad-Hoc Analysis Turnaround | 3–5 business days | Self-service, instant | ▲ On-demand |
| Annual Cost Savings | — | $1.2M | ▲ Direct savings |
We went from four days of spreadsheet chaos to having our consolidated P&L ready before the second business day. The board now makes decisions with data that's hours old, not weeks. This project didn't just improve reporting — it changed how our leadership team operates.
More Case Studies
Ready to Transform Your Reporting?
Let's discuss how a unified analytics architecture can eliminate your data silos.
Start Your Project →