A global CPG company's analytics and planning teams operated with disconnected forecasting tools, with no unified view connecting brand, SKU, and category forecasts or visibility into key performance drivers. There was no top-down to bottom-up reconciliation connecting category and brand forecasts to individual SKU plans. Without driver-level decomposition, it was impossible to understand what was impacting brand performance versus plan.
Cloverpop developed a comprehensive driver assessment of statistical impact on brand sales and reconciliation algorithms aligning top-down and bottom-up forecasts into one unified view. A unified consumption model integrated MMM, innovation driver, and category trend inputs, and a simulation tool enabled scenario planning based on driver assumptions.
Results
4pp error reduction at brand level
12pp error reduction at PPG level
Analytics teams gained a single, reconciled view of brand and SKU performance, with top-down to bottom-up forecast reconciliation and clear driver decomposition enabling more precise planning decisions. Unifying disparate forecasting tools into a single reconciled model gave planning teams a clear, connected view and a simulation capability for scenario planning.