Bullwhip Effect

Example

Retail demand for a product ticks up 10% one week. The retailer, wanting a buffer, orders 20% more from the distributor. The distributor, seeing that 20% jump and wanting its own buffer, orders 40% more from the manufacturer. By the time the signal reaches raw-material suppliers, a 10% demand change looks like a 60%+ swing.

Every tier is behaving rationally on the information it has — the distortion comes from each layer reacting to the order it received rather than the underlying demand driving it.

The practical fix is sharing point-of-sale data upstream directly, so every tier forecasts off the same signal instead of off each other’s orders.