Join CGT for this exclusive web seminar featuring:
Jeff Metersky from Chainalytics on benchmarking forecast accuracy at 30 top consumer goods businesses
Lora Cecere, "The Supply Chain Shaman", on the implications of the Item-Location forecast on the consumer goods supply chain
ToolsGroup CEO, Joe Shamir, on new techniques for improving Item-Location forecast accuracy
Forecast accuracy at the Item-Location level is a big problem at most CPG companies. These detailed forecasts just are not accurate and reliable enough to support account management and supply chain planning. Highly variable, intermittent and "long tail" demand drives forecast error (e.g., MAPE) up as much as 40% at this level - too high to respond properly.
For most companies, an incremental improvement just isn't good enough. They need accurate, reliable forecasts that account managers and supply chain planners can really trust. They need to be able to predict future demand behavior and volatility to eliminate the forecast error that is hindering responsive replenishment.
Forward-thinking CPG companies are employing innovative new techniques to go beyond standard time-series forecasts by taking advantage of order-line data and even downstream "big data" such as social media, POS or web sentiment. This improved demand management provides an accurate account level forecast and reduces latency via fresh demand data.
Creates a demand pull signal to significantly reduce forecast errors (e.g., 85+% forecast accuracy at the DC level) for improved supply chain planning
Extends supply chain visibility within the network (e.g., daily sell-to data) to minimize uncertainty and improve responsiveness
Creates a reliable demand plan to support the account planning and S&OP processes