Key Metrics to Track for Demand Planning for New Products in Retail for Growing Brands
Retail launches require specialized metrics that detect risk early. Mature brands monitor structured launch KPIs beyond standard forecast accuracy.
Launch Metrics Are Different From Steady-State Metrics
Retail new product launches cannot be measured using the same KPIs as mature SKUs. Historical WMAPE alone is insufficient because the objective during launch is uncertainty management—not perfection.
High-growth brands implement specialized launch dashboards to surface early warning signals.
1. Weekly Sell-Through Velocity by Store Cluster
Velocity is the primary early indicator of launch health. Monitoring store-level performance identifies regional variation and shelf placement issues.
Cluster-level analysis prevents misleading averages that mask underperforming segments.
2. Launch-Phase WMAPE
Tracking forecast error relative to projected ramp curves highlights early drift. This metric should be evaluated weekly during the first 8 weeks.
3. Launch Forecast Bias
Persistent over-forecast bias inflates working capital. Persistent under-forecast bias creates stockout risk and retailer dissatisfaction.
4. Inventory Days on Hand by Launch Cohort
Tracking inventory days specific to new product cohorts isolates launch-driven capital exposure from steady-state SKUs.
5. Markdown Exposure Probability
Scenario modeling should quantify the probability of forced discounting under conservative velocity scenarios.
6. Cash Conversion Impact
Launch-specific inventory should be tied to cash conversion cycle tracking to prevent silent liquidity pressure.
Metrics Enable Early Correction, Not Post-Mortem Analysis
Retail launch KPIs must focus on early detection. Mature brands measure velocity stability, bias, and capital exposure weekly—not quarterly.
See how AI-native dashboards surface retail launch risk metrics in real time.
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