Case 05 | Consumer Goods | Extended Planning & Analysis

xP&A Data Lake &
Driver-Based P&L

Company
FMCG Consumer Co.
Base Units Sold
4,200,000
Avg Selling Price
$12.40
Scenarios Modelled
4
Method
Driver-Based xP&A
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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.

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

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