Probabilistic inventory without a PhD
Days-of-cover is simple, and that is the problem. Here is how thinking in probabilities frees working capital without hurting service.
Updated June 2026 · iForecastPlan team
A flat days-of-cover rule treats a predictable item and a volatile one the same way. You end up holding too much of what is steady and too little of what surprises you. The result is cash tied up on the shelf and stockouts on the items that actually move the service number.
Stock to a service level, not a habit
Probabilistic inventory asks a sharper question. Given how this item behaves, how much do we need so that we meet demand a set percentage of the time? Quantile methods answer it directly. Steady items need a thin buffer. Volatile items get protected where it counts.
You do not have a stock problem. You have a placement problem. Put the buffer where uncertainty lives.
Think across echelons, not one node
Holding safety stock at every location multiplies the buffer. Multi-echelon placement decides where in the network a buffer does the most good, so a central position can cover several downstream nodes. That is how teams cut total inventory while protecting, or even improving, service.
Keep it moving with the forecast
Reorder points and safety stock are recomputed as demand shifts, so the policy never goes stale. Because inventory reads the same spine as demand and feasibility, a change in the forecast updates the buffer without a separate project.
Probabilistic, multi-echelon inventory is the same play the enterprise leaders use. We just make it understandable, and tie it to the rest of your plan.