We provide an analytic methodology that identifies the optimal (least cost) policy for managing an inventory of aging assets. The policy specifies when to replace an asset, when to repair or refurbish an asset, and when to test an asset. Testing is an interesting aspect of the optimal strategy, because the test result can reveal valuable information about the condition of the asset. It is the present condition of the asset that helps one forecast the future behavior of the asset. It is the forecast of future behavior that indicates what to do with the asset at any time.

The methodology is based on company-specific data and judgment about the behavior of the asset. We have made the data-gathering requirements as simple and straightforward as possible. This methodology substitutes mathematical sophistication for reams of data. The methodology is implemented in very easy-to-use software.

The methodology has been applied to the electric power industry, with particular attention to managing populations of transformers, underground cable, and wood poles. The cost savings are significant. There is no restriction whatsoever on the asset type or industry. The methodology is universally applicable.