Featured Customer

We found that with Retail Solutions, Unilever's forecast accuracy will improve on average 9% compared to the models we were using previously. [...] We are rolling out this solution in 2009 to support our North American business with nearly 200 retail customers.

-Andy Patel, Manager Business Capabilities, Unilever

Supply Chain Solutions

Forecasting

Current forecasting techniques just do not work well enough: according to the GMA 2008 Logistics Survey, the weekly Mean Average Percentage Error (MAPE) stood at 45%, both by shipping location and by product family. Most companies still forecast shipments to DC or stores on the basis of past shipments. As a result, baseline forecast accuracy continues to be plagued by the much-maligned bullwhip effect resulting from small changes in POS driving large and sudden changes in retailer order patterns.

Retail Solutions' unique access to point-of-sale (POS) data provided the foundation to a novel approach to forecasting. Our solution leverages robust statistical algorithms against the richest available data set (including POS when available and/or shipment data) to create a smoother, less biased and more accurate baseline (turns) forecast. This solution establishes a stable foundational baseline from which all other forecasts and plans are built to reduce inventories, improve service levels and lower logistics costs.

Overview Benefits Features

By leveraging point-of-sale (POS) data when available and by applying an advanced class of algorithms to eliminate the impact of outliers, Retail Solutions customers have been able to show double-digit improvements in forecast accuracy across all products and all channels. Some of Retail Solutions use cases for forecasting and sales and operations planning include:

Automated baseline forecasting - at the DC and/or the store level, by customer
Integration into the overall Sales & Operations Planning process

Retail Solutions helps you cut down inventory levels and logistics costs by achieving a more stable baseline forecast.

Eliminate large forecast errors: Retail Solutions' algorithm performance is significantly better for the 20% of items that wreak havoc on your supply chain today
Transform a more stable forecast into lower, more controllable operating costs
- Reduce safety stock inventories required to achieve target service levels by reducing forecast error
- More predictable production and transportation schedules which can result in fewer unnecessary changeovers and expedites/cross-ships
- Drive down unsaleables through reduced forecast bias
Eliminate both the workload and the bias induced by the involvement of customer teams into account-level forecasting: apply a unique, proven method no matter whether POS data is available or not
Improve visibility on real consumption throughout your enterprise, to fuel your S&OP processes

Retail Solutions forecasting solution enables CPG companies to build a more effective, more efficient forecasting process

Granular - by customer DC, by item, by week
Automated - removing the need for customer team resources
Based on sales, not (only) shipments - but can also operate from shipment data when POS is not available
Designed to fit into your replenishment processes - the baseline forecast output feeds directly into your existing Demand Planning system and processes; there is no need to uproot any existing systems