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Problem Statement
When Finance Can't Answer the Operational Question.
The FMCG company's FP&A team could produce a P&L. But they couldn't answer the question the CEO kept asking: "If transport costs rise 10%, what happens to our margin by product line?" The data needed to answer it lived in three separate systems — financials in the ERP, transport costs in the logistics platform, and volume data in the CRM. No joins. No shared keys. No answer. The xP&A data lake solved this by creating a unified schema where operational drivers fed directly into the financial model. A change in any driver — units, price, cost — cascaded automatically into the full P&L.
Base Case Drivers
Units Sold
4.2M
Annual volume
Avg Selling Price
$12.40
Per unit
COGS / Unit
$5.20
Production cost
Transport / Unit
$1.10
Key variable driver
Marketing Spend
$3.8M
Fixed commitment
Fixed Overhead
$6.2M
Annual base
The data lake didn't just connect the numbers — it changed the conversation. Finance moved from reporting what happened to modelling what would happen if. The CEO got an answer in seconds. The FP&A team became indispensable.
Adapted from: FMCG xP&A Case, McKinsey "Putting the A back in FP&A" / FP&A Trends 2024
Scenario Simulation — 4 Planning Scenarios
Base Case
Revenue$52080000
COGS$26460000
Gross Profit$25620000
Gross Margin49.2%
EBIT$15620000
EBIT Margin30.0%
Units4200000
+10% Transport
Revenue$52080000
COGS$26922000
Gross Profit$25158000
Gross Margin48.3%
EBIT$15158000
EBIT Margin29.1%
Units4200000
-15% Demand Shock
Revenue$44268000
COGS$22491000
Gross Profit$21777000
Gross Margin49.2%
EBIT$11777000
EBIT Margin26.6%
Units3570000
Stress (Both)
Revenue$44268000
COGS$22883700
Gross Profit$21384300
Gross Margin48.3%
EBIT$11384300
EBIT Margin25.7%
Units3570000
Revenue by Scenario
EBIT Margin % by Scenario
Gross Margin vs. EBIT Margin — Scenario Comparison