REMOVING FORECASTS ISN’T THE ANSWER:

Most supply chain dysfunction traces back to forecast error: bullwhip, excess and shortage inventory, expediting, KPI overload. And because Tier 1, Tier 2 and sub-tier suppliers each plan off the signal above them, the error compounds at every echelon.

But removing forecasts isn’t the answer, because the forecast is a symptom, not the root cause. The root cause is the gap between cumulative lead time and customer tolerance time. Where the first exceeds the second, planning on expectation is unavoidable. In aerospace, with long lead times on raw material, forgings and castings, that gap is structural.

So, the objective is to shrink the gap and decouple execution from forecast error:

▪️ DDMRP: decoupled buffers at strategic points, replenished on actual consumption

▪️ Lead time compression: smaller lot sizes, flexible capacity, forward-positioned stock

▪️ Postponement: hold semi-finished or common configurations, differentiate on order

▪️ End-demand visibility: share real consumption data with all tiers so each stops building its own forecast

▪️ Framework agreements: reserved capacity and volume bands instead of week-level precision

▪️ Flexibility over buffers: dual sourcing, capacity reserves, regional suppliers

Full forecast-free operation is rarely achievable. A realistic target is to confine forecasts to long-horizon capacity and strategic planning, while execution runs on actual demand and pull signals.

Which of these has delivered measurable results in your network, and where did it fall short?