Retail & FMCG Analytics
Most FMCG planning teams are running weekly forecasts from data that's already four days old. In a market where promotions shift demand overnight, four days is the difference between a stockout and a writeoff.
What we hear from operators
The problems we solve
Demand planning runs on weekly data exports
The planning team exports sales data from SAP weekly. Loads it into the forecasting tool — or more often, into Excel. Applies the forecast model. Sends to supply chain. By the time supply chain acts on it, the underlying demand has already shifted. Promotions calendar isn't connected. Seasonality isn't modelled at SKU level. The forecast is always chasing reality.
Trade promotion ROI is measured after the fact, if at all
Most FMCG companies spend 15–25% of revenue on trade promotions. Most can't tell you which promotions drove incremental volume and which just accelerated existing demand. The promotion data is in one system, the sales data in another, and nobody has connected them with enough granularity to calculate a reliable promotional lift factor.
Distributor sell-out data arrives too late
Sell-in numbers are visible in real time from the ERP. Sell-out from distributors arrives weekly or monthly in a spreadsheet. The gap between what you shipped and what actually moved off shelf — the one that tells you whether you have a distribution problem or a demand problem — is often invisible until the next reorder cycle.
By market
Retail & FMCG Analytics — market-specific pages
Each page below covers what retail & fmcg analytics looks like specifically in that market — the local ERP landscape, compliance context, and the operational patterns we actually see there.
Singapore & Malaysia
United Kingdom
North America
By industry
Retail & FMCG Analytics — industry-specific pages
How retail & fmcg analytics applies to the specific systems, metrics, and operational challenges of each vertical.
Technology stack
Start with a conversation, not a proposal
First call is 45 minutes. No deck. We ask about your systems, your team, and your most pressing operational problem. You get a clear view of where the gap is and what closing it looks like.