Industries
Consumer Packaged Goods
Demand sensing, assortment, pricing and supply-chain decisions.
Overview
Consumer packaged goods companies balance demand that is shaped by promotions, seasons and channels against supply chains with long lead times. Better signals and clearer trade-offs improve both availability and margin.
Common challenges
- Forecasting at SKU and location level with promotions
- Fragmented retailer and distributor data
- Measuring the return on trade and marketing spend
- Volatile input costs and logistics constraints
Where AI and data science help
Demand forecasting
Hierarchical forecasts that reflect promotions and seasonality.
Promotion effectiveness
Estimate incremental volume and cannibalisation.
Assortment and pricing
Scenario analysis for ranges and price architecture.
Supply planning
Optimise inventory, production and distribution.
Typical data sources
- Sell-in and sell-out
- Promotion calendars
- Inventory and logistics
- Market and weather signals
Responsible use
Data-sharing arrangements with retailers and distributors affect what is feasible, and we plan around the data you can lawfully use.
Bring us a decision you want to improve.
Tell us about the problem and the data you have. We will reply with a candid view of where we can help.