Many service organizations are characterized by a large service parts distribution network, particularly a large number of field stocking locations (FSLs). These field stocking locations can be dedicated warehouses, rented storage locations, storage space in customer premises, and/or field engineers' truck trunks. The number and nature of these FSLs pose special challenges to the service parts planning process. On the one hand, many critical parts need to be close to the installed base in order to respond to customer demands in a timely fashion. In many cases, the stringent customer service level agreements rule out the possibility of shipping the requested parts directly from the central stocking location, even using an expedited transportation mode. On the other hand, these parts or at least many of them usually have very low demand volume at any one of these FSLs and some of them may be quite expensive. Deploying many parts to a large number of small FSLs will incur prohibitively high inventory carrying (or holding) cost and obsolescence. Furthermore, the number of parts that can be stored in these field locations may be constrained by the space. A straightforward solution to this problem is to introduce a middle-tier network location - between the central stocking location and field locations - where some inventory is consolidated. However, the cost of this solution is more capital investment to build more warehouses. Often, this extra capital expenditure cannot be justified.

Pooling parameters introduce the critical concept and method of field inventory pooling to achieve the compromise between consolidating parts into central stocking or building more regional warehouses and stocking many parts in the field locations. The basic idea is to let one selected field location (pooling location) among many field locations within a certain predefined geographic region (e.g., within 2-hour driving distance) to store some parts for the rest of the field locations group, effectively serving as a mini-warehouse for those parts for the rest of FSLs in the group. The other FSLs then would not need to stock these parts at all. The demand forecasts of these parts at each field location within the group/region are then consolidated into the one demand forecast for the part at the pooling location. When a demand comes in for one of these parts at a field location within the pooling group, the field location would need to get the part from the pooling location.

Pooling parameters are managed using pooling schemes.

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