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8 McCollom 2006; D'Alessandro et al. 2009; Laver 2009) as mary of asset actions (replacement or mid-life maintenance) part of good asset management analysis. However, there is funded on-time, later than scheduled, or not at all, and changes limited information in the literature about how these mid-life in the backlog of actions throughout an analysis period. actions should be defined for all asset types. The limitation of the Boston approach (McCollom 2006; D'Alessandro et al. 2009) is that the consequences are related SCENARIO TESTING to the successful completion of desired programming actions. It does not estimate impacts of underinvestment on operating Most of the applications documented in the literature provided costs, service reliability, safety, and passenger usage. estimates of the capital funding needed to bring the assets to, and maintain the assets at, SGR. This might be termed "ideal SGR funding." SUMMARY However, in many communities, funding is limited. Deci- The limited availability of literature on this topic suggests that sion makers would like to know the consequences of provid- the active use of asset management systems for more than data ing less than ideal funding. collection and manipulation of asset inventory data is not com- mon. As the state of the industry matures, it is reasonable to The Boston methodology (McCollom 2006; D'Alessandro expect more reports on this subject. et al. 2009) was the only one identified that included the abil- ity to prioritize the funding of specific asset renewal or replace- Although the literature is limited, it provides a strong indi- ment projects in constrained funding environments. It uses a cation of where methodical improvements will be made. Sig- weighting scheme that relies on several factors, such as rider- nificant advances were found in the definition used for SGR ship impact, replacement costs, and impact on operations, to and the asset costs considered in the analyses. More work is determine funding priorities. The consequences include a sum- needed in forecasting the consequences of underinvestment.