Risk Pooling in Business Logistics

Abstract

Risk pooling in business logistics can reduce the total variability of demand and/or lead time and thus uncertainty and risk (the possibility of not achieving business objectives) by consolidating individual variabilities (measured with the standard deviation) of demand and/or lead time. These individual variabilities are consolidated by aggregating demands (demand pooling) and/or lead times (lead-time pooling). This reduction in uncertainty allows to reduce inventory without reducing the customer service level (product availability) or to increase the service level without increasing the inventory or a combination of both and to cope with product variety. Risk pooling can be achieved by (1) inventory pooling, (2) virtual pooling, (3) transshipments, (4) centralized ordering, (5) order splitting, (6) component commonality, (7) postponement, (8) capacity pooling, (9) product pooling, and (10) product substitution. These risk-pooling methods can reduce demand and/or lead-time uncertainty. Risk pooling is explained by the Minkowski-inequality, the subadditivity property of the square root of non-negative real numbers, and the balancing effect of higher-than-average and lower-than-average demands and/or lead times. The ten risk-pooling methods can be implemented everywhere along the supply chain and mainly pertain to the value activities storage (1), transportation (2 and 3), procurement (4 and 5), production of goods and services (6, 7, and 8), and sales and distribution (9 and 10).