Supply chain literature most often focuses on ordering policies where each separate item is treated in complete isolation to all the other items: the decision to order more units of item A is strictly independent from the decision to order more units of item B. In contrast, the prioritized ordering policy emphasizes multi-item decisions, where each item competes for capital allocation with all the other items.
Inventory is optimized only when the capital allocation for inventory maximizes the market potential of the company while taking all inventory risks into account. Within this capital allocation, all items are in constant competition with each other for every marginal investment. Each item should be assessed against its expected returns and its expected costs for the next additional unit to be ordered.
At Lokad, we have observed that when a probabilistic forecasting technology is available, approaches that rely on the purchase priority list systematically demonstrate superior inventory performance.