**4. From whole-life costing to long-term analysis of indefinite life systems**

Comparing intervention alternatives from the financial stand point requires that all relevant costs and revenues incurred during the asset life be taken into account. The costs in particu‐ lar include such items as design and building costs, operating costs, maintenance costs, asso‐ ciated financing costs, depreciation, and disposal costs. Most of the reference literature on asset management recommends a whole-life costing approach (also known as life-cycle ap‐ proach). However, this is not directly applicable to urban water infrastructures and other networked infrastructures that have indefinite lives and behave as systems, not as mere col‐ lections of components with independent functionality.

activity through the production of performance measures. Performance measures are the specific parameters that are used to inform the assessment. The principal categories of per‐

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**•** Performance indicators, which are quantitative efficiency or effectiveness measures for the activity of a utility. A performance indicator consists of a value (resulting from the evaluation of the "processing rule") expressed in specific units, and a confidence grade which indicates the quality of the data represented by the indicator. Performance Indica‐ tors are typically expressed as ratios between variables; these may be commensurate (e.g. %) or non-commensurate (e.g. \$/m3). The information provided by a performance indica‐ tor is the result of a comparison (to a target value, previous values of the same indicator, or values of the same indicator from other undertakings) (Alegre *et al*. 2006; ISO 24500,

**•** Performance indices, which are standardised and commensurable measures, may result from the combination of more disaggregated performance measures (e.g. weighted aver‐ age of performance indicators) or from analysis tools (e.g. simulation models, statistical tools, cost efficiency methods). Sometimes they aim at aggregating several perspectives into in a single measure (Alegre, 2008, Sjovold *et al*. eds., 2008).Differently from the per‐ formance indicators, they contain a judgment in itself, intrinsic to the standardization

**•** Performance levels, which are performance measures of a qualitative nature, expressed in discrete categories (e.g. excellent, good, fair, poor). In general they are adopted when the use of quantitative measures is not appropriate (e.g. evaluation of customer satisfaction

Performance indicators may be converted into performance indices through the application of a performance function, or into performance levels when they are compared with refer‐ ence levels, in order to support interpretation or multi-criteria analyses. Such transforma‐ tions may be particularly useful in the graphical representation of a set of performance

Risk analysis may address an organization in its entirety, a system or sub-systems (aggregat‐ ed or lumped analysis), or individual system components(component or discrete analysis). Risk assessment may be carried out in many different ways, and is often (though not al‐ ways) quantifiable: for instance, if the probability of failure of every pipe in a network is known, as well as its consequence, expressed in terms of the ensuing reduced service (un‐ met demand), the total risk of not supplying the users may be expressed as the expected val‐

Risk analysis is a vast field of expertise where several mainstream frameworks have been developed for infrastructure-based problems, such as fault-tree analysis or the approaches centered on risk matrices (Almeida *et al*., 2010). The latter is one of the most versatile and structured formalisms available when approaching the range of (quantifiable or unquantifi‐

process (e.g. 0 – no function; 1 – minimum acceptable; 2 – good; 3 – excellent).

by means of surveys) (Alegre, 2008, Sjovold *et al*. eds., 2008).

ue of the annual unmet demand (Vitorino *et al*., 2012).

formance measures include (Sjovold *et al*. eds., 2008):

Sjovold *et al*. eds., 2008).

indicators.

**5.2. Risk assessment**

As argued by Burns *et al.* (1999), infrastructure assets are defined functionally as assets that are not replaced as a whole but rather are renewed piecemeal through the replacement of individual components, whilst maintaining the overall function of the system. As a whole, infrastructure system assets have indefinite lives. Conversely, economic lives can only be as‐ signed to the individual components of an infrastructure system.

However, intervention decisions cannot be made based exclusively on the analysis of each individual asset. Individual assets cannot deliver a service by themselves, but only as part of a system or subsystem. The causes of malfunctions are often located away from where the symptoms emerge. Levels of service cannot be allocated to individual assets, for most of the infrastructure's components. Intervention alternatives, aimed at producing the desire defect, tend to imply jointly modifying a combination of assets, which display different remaining lives, values, condition, etc..

These two key features – the indefinite life of the infrastructure as a whole, and its system behavior – make the classical life-cycle approach effectively unsuitable to IAM. The objective is to ensure that the service provided meets the targets over time, keeping the risk in accept‐ able levels and minimizing the overall costs from a long run viewpoint.

How long is "long-term"? Long enough that interventions are given time to reach their infra‐ structural maturity, all the lifecycle stages of the most relevant assets are included in a meaningful way, and the investments under consideration are rewarded by their accrued benefits; but not so long into the future as to unreasonably limit the significance of the as‐ sumptions made for the scenarios considered, such as demand or land use projections.
