3.4.5.4 A procedure for cross-asset allocation

The final report of the PROCROSS project (ENR 2012) includes a specific cross-asset allocation procedure, which is based in the combined approach described above and comprises the following activities:

• Description of strategic targets for each performance area, i.e. riding comfort, environmental sustainability, compliance with budget constraints, and so on.
• Translation of strategic targets into technical performance indicators.
• Design of specific treatments for each single asset.
• Automated, semi-automated or manual definition of combined project alternatives covering the needs of the different assets considered.
• Calculation of the strategic target-related performance indicators for each of the alternatives defined.
• Application of a mathematical optimization process to determine the combined alternative that best meet the strategic objectives for the whole road-network.

A procedure for cross-asset allocation is also provided in the Report 806 of the US National Cooperative Highway Research Program (Maggiore, Ford, CH 2M Hill, High Street Consulting Group & Burns & McDonell, 2015). In this case, the procedure is made up of the tasks below:

• Identification of road organization goals clearly articulated through objectives that reflect the priorities of both the organization and the road network.
• Evaluation of performance measures linked to the organization goals and objectives.
• Assessment of project impacts through the application of predictive models to forecast asset future behavior in terms of the performance measures used. This step includes the combination of projects addressing different performance areas into pooled sets.
• Application of decision science techniques to express the project impacts in the same units and compare benefits across investment areas, as well as prioritize and optimize works programs.
• Conducting of trade-off analysis to determine the performance level that can be reached for different investment scenarios.

Form the above listings, it can be concluded that both procedures are quite similar, even though the PROCROSS method do not include a step for comparing the effects of funding levels.

A further procedure for cross-asset allocation is presented next. Although, on the one hand, this procedure is based on the two methods outlined previously, on the other hand it assumes that the organization has developed a performance framework (see section 1.4) so the following items are already available:

• Strategic objectives
• Strategic (customer) and technical levels of service, including the translation of the former into engineering terms
• Performance measures and targets

Given the above, a cyclical procedure for cross-asset allocation can be depicted as shown in Figure 3.4.5.4.

The steps illustrated in this figure can be described as follows:

Assessment of current performance. It implies determining the organization progress in reaching the strategic targets defined within the performance framework. Any difference will represent a performance gap that has to be addressed through the proposed investment programs.

Development of individual programs. Works dealing with improving the condition of individual assets or any other attribute of the road network are identified in this step using specialized management systems for each asset / operational issue (pavements, bridges, safety, etc.) The resulting programs are intended to minimize the risk of not achieving the targets proposed for each performance area.

Formulation of cross-asset alternatives. Combines the projects selected for the individual programs in order to cover all performance areas with a single works program. Also, define alternative programs containing project options different from those selected in the previous step so that the preferences stated in the performance framework can be considered while carrying out cross-asset allocation under budget constraints.

Program evaluation. Refers to a decision-making process that should be applied to identify, using diverse criteria, the alternative of a cross-asset program that best contributes to attaining the targets specified in the performance framework. This involves comparing projects in terms of their benefits, which are normally expressed in different units depending on the performance area addressed by each project. Thus, all benefits should be normalized (i.e. converted to a common metric) to allow for comparison.

The international experience on cross-asset works programming comprise the application of decision-making techniques such as the following (Proctor & Zimmerman, 2016; Porras-Alvarado, Han, & Zhang, 2014):

• Prioritization based on perceived utility. Transfers resources from one investment program to another in order to increase the overall benefits perceived (not measured or quantified) by the decision makers. This kind of prioritization is based on actual data about asset performance so that it can be regarded as a rational method for decision making. However, it is not as transparent as desirable because it depends on the judgement of the individuals involved.
• Benefit / cost. Uses as a comparison base the ratio of the monetized programs’ benefits to their costs. Even though this certainly allows the joint evaluation of dissimilar projects and programs, on the other hand it might need broad assumptions for entire asset classes or performance areas. Also, monetizing intangible benefits could be very difficult, as could be estimating costs in the early phases of planning.
• Multi-criteria analysis. Comprises the steps listed below:
  • Assigning weights to the different performance areas or road network attributes considered.
  • Defining criteria for evaluating each alternative within each performance area.
  • Rating alternatives for all defined criteria using a common scale.
  • Calculating an overall rating for the alternatives as the weighted sum of the ratings granted within each performance area.

The multi-criteria analysis may provide various advantages. First, the analyst priorities are specifically declared through the assignment of weights to the different performance areas. At the same time, the decision maker objectives are clarified while translating them into criteria for evaluating intervention alternatives. Furthermore, the system for evaluating alternatives is transparent since it leaves a clear record of the weights and criteria applied. Finally, the multi-criteria analysis is flexible as it permits criteria to be added as well as disparate criteria to be used.

However, it also has disadvantages: i) Costs and risks are not explicitly involved in the analysis; ii) Results are very sensitive to the values attributed to weights, so these can be determinant of the alternatives selected.

• Risk-reward based allocation. It is an investment strategy aimed at distributing resources among investment programs in such a way that the overall benefit is maximized, while risk are kept below an acceptable level. This method applies the concept of “efficiency frontier”, which is used to determine the highest level of return that can be obtained given a certain level of risk. In this case, the best combination of investments is a function of the performance a road organization wants to offer and the risk level it is willing to deal with.
• Fair division approach. Seeks at allocating funds so that participants believe they are receiving a fair share based on collective utility functions. In this approach, “utility” is defined as the ratio resources allocated / requirements corresponding to each participant. The collective functions are used to carry out trade-off analyses of different allocations considering the total utility and the total envy together with the corresponding overall network performance.
• Cross-asset optimization. All the above methods essentially prioritize candidate projects, i.e. they produce a list that indicates the order in which treatments should be executed until available resources are exhausted. However, they do not explore alternative scenarios that could increase benefits for the existing budget ceiling. In fact, this can only be accomplished by applying optimization tools.

Cross-asset optimization involves the use of recursive mathematical procedures to find the maximum level of benefits that can be produced by a given set of investments subject to technical performance requirements and budget constraints. Its application implies the use of a software capable of evaluating a considerable number of options (hundreds or even thousands) to find the one yielding the greatest benefits. It this way, cross-asset optimization generates more sophisticated and quantified results, yet it requires extensive data about all candidate projects evaluated.

Scenario analysis. This last step is equivalent to the last step of the cross-asset allocation procedure proposed in the US NHCRP Report 806 (Maggiore, Ford, CH 2M Hill, High Street Consulting Group, & Burns & McDonell, 2015). As the latter, it consists of determining the effects of various investment scenarios and funding levels in the performance of the road network both as a whole and considering each individual asset / operational feature individually. The results of such an analysis can be used to identify the needs of stakeholders concerning the different performance areas and the budgeting required to meet those requirements, and eventually to modify appropriately the performance targets in use.

Finally, it should be noted that the procedure described above is based on the combined approach for cross-asset allocation portrayed in figure 3.4.5.3.3, as it starts with the individual analysis of each of the different performance areas, and then it combines candidate projects from the different programs to obtain a solution oriented towards achieving the performance goals of the road organization.