How Probabilistic Forecasting is Transforming the Spare Parts Supply Chain
As technological advancements transform nearly every industry, customer expectations for speed and convenience are reaching unprecedented levels.
Today’s customers demand same-day support and immediate product availability. Any delay can result in customer frustration, negative reviews, and even lost business to a competitor.
To align inventory with increasingly unpredictable demand, forward-thinking businesses are implementing sophisticated demand forecasting solutions. This strategic shift is especially critical for manufacturers and distributors managing extensive product portfolios and aftermarket parts inventories.
The Downsides of Conventional Forecasting
Conventional forecasting methods rely on a top-down approach, using broad demand projections based on aggregated historical data or simple year-over-year percentage increases.
The problem? They prioritizes simplicity over accuracy.
Projections rely on past trends in aggregate, but this smoothing process filters out critical demand signals. While an overall forecast may only be off by a few percentage points, those small errors can compound—resulting in a staggering 40-50% discrepancy for specific weeks, distribution centers, or SKUs, leading to costly miscalculations in inventory and replenishment planning.
