Asset Management has Evolved
Today’s Asset Managers are tasked with making the best use of available funding to manage a wide variety of assets at an acceptable level of service. This means having to manage a broad range of assets within a portfolio, with each asset deteriorating at a different rate and requiring interventions and funding that often times are not optimally coordinated to reduce cost and limit disruption to customers. Quite often, the maintenance, renewal and replacement of different asset classes are managed by diverse operating entities or “silos” within an organization. This piecemeal or silo-based planning can result in poor communication between operating entities and sub-optimal asset portfolio performance and funding.
Understanding the life cycle costs and risks at the asset level, and how that rolls up and integrates at the organizational level, to maximize the performance of a diverse asset portfolio is paramount. Today, many forward thinking organizations’ track and manage their assets at the portfolio / whole network level to understand the trade-off of cost, and risk between different asset classes. They deploy and coordinate resources to optimally manage assets across the traditional silos.
Cross Asset Optimization (CAO)
The Cross Asset Analysis process generally allows an organization to maximize the benefit of allocating funding between different assets to help determine an optimum distribution of funds. The following scenario illustrates the challenge that Cross Asset Analysis is intended to solve:
Within an organization responsible for pavement and bridge assets, the pavement assets are given an annual budget of $2.5 million and the bridge assets are given an annual budget of $1.0 million. Both assets require substantially more funding than is available within the agency to halt the increasing deterioration of the assets. If the agency receives additional funding of $2.0 million dollars a year, what is the proportion of the additional funding that should go to the pavement assets and which proportion of the funding should go to the bridge assets?
Each asset in a Cross Asset Analysis starts with a set budget (based on a budget scenario for the asset). The analysis also specifies an additional amount of funding which is distributed among the assets (based on maximum allowable percentages you can assign) once an asset's original budget is expended.
Multiple Uses for Cross Asset Optimization
Typically CAO allocates resources across assets, but it can also be used for allocating resources across districts, regions, and between different classes of assets. For example, use cross asset analysis to optimize funding for:
- All of the pavement elements and bridge elements in the network.
- Each district in a pavement network.
- Each classification in a municipality (arterial, collector, local).
When setting up a cross asset analysis, one example is to configure additional funding where each asset (district, class) is given a guaranteed minimum amount of funding for that asset, and then an additional amount of funding is set aside that can be used for any of the assets. But, as another example, it is possible to give each asset zero dollars as a guaranteed minimum and then use the total budget as the additional funding. The cross asset analysis is flexible to enable both types of analysis.
How CAO Works
CAO works by establishing a budget scenario for each asset you want to include within the CAO. The budget scenario provides the minimum guaranteed funding for the asset and the analysis variables for present value benefit and present value cost that are used in the optimization. dTIMS uses the same type of incremental benefit cost optimization across assets as it does within a normal asset analysis. It is a good idea to ensure the benefit model of all assets included within the cross asset analysis is similar.
Next, you specify an annual amount of additional funding to be distributed between the assets included in the analysis. For each asset, you must also specify the maximum percentage of the additional funding that can be applied to each asset in each year. If all assets are given values of 100%, then each asset could receive up to 100% of the additional funding.
Funding is optimized for each budget scenario and the additional funding (up to the limits you have specified) by using an Incremental Benefit Cost Optimization. The result is an optimized maintenance and rehabilitation program for each asset and the optimum funding distribution across the assets according to the benefit and cost models supplied in the asset budget scenarios.
Working Example
As an example, lets consider a DOT with three major assets under management: highway pavements, highway bridges, and buildings. Each of these assets have an established Life-Cycle Cost Analysis in dTIMS, including: analysis variables, performance prediction models, treatments, analysis sets and budget scenarios. The dTIMS LCCA outputs funding impacts for each of these assets and a recommended construction program.
In the next fiscal year, the DOT will have finally paid off a number of bonds used to finance highway system enhancement and the DOT will see a significant increase in revenue for management of these assets. The DOT is projected to have an additional $25 million at its disposal for the foreseeable future and desires to learn the appropriate distribution of that additional funding amongst its three biggest assets.
The following table outlines the historical expenditures for each asset over the last five years. You can see that there is a good deal of variability across the assets with 2020 estimated revenue shown.
Within the agency pavement assets are generally well funded with bridge assets suffering a decline in condition each year. Building assets are maintaining status quo condition and could never expend more than $10 million a year on projects as they do not have the staff.
So how should the agency determine the best distribution of funding for the additional $25 million? Using the dTIMS Cross Asset Analysis and Optimization, the agency can determine how to divide the $25 Million dollars between the assets. A new budget scenario is created for each asset to store the minimum budget for each asset and to store the results.
When the new budget scenarios are created, they do not have to be optimized before running the cross-asset analysis and optimization as the function will do that.
Setting up the cross-asset analysis and optimization involves creating the object and then setting the additional flexible funding for each year as well as the maximum amount of funding an asset can receive from the flexible amount. Setting a maximum percentage of the funding ensures an asset does not get more funding than they can handle (see buildings above). In our example, bridges and pavements can use every dollar they can get, so the maximum for those assets is 100%.
When the cross-asset object is executed, dTIMS takes all the strategies generated for the asset’s analysis set and assigned funding level budget scenario and optimizes them all at once. Strategies from all assets are sorted on their Incremental Benefit Cost Ratio (IBC) and the dTIMS BA IBC optimization proceeds as normal, using each asset’s individual budgets when possible and then using flexible funding when those budgets have been exhausted. Results of the optimization are stored in the budget scenarios so that they can be reviewed like every other budget scenario in dTIMS. A Cross Asset report is available that details the expenditures for each asset showing how much of the assigned budget and the flexible budget were used for each asset. The report is similar to that shown below:
You can see that buildings have only received a little flexible funding with the bulk of the flexibly funding going to the bridge assets. The dTIMS BA Budget Charts can be used to see the impact of the flexible funding on each asset and the dTIMS BA Budget Comparison charts can be used to compare scenarios with and without the flexible funding. It is important to note that the optimization is using the present value benefit and the present value cost from the asset strategies during the optimization. If the benefits and costs of the strategies from the assets are too different, where one asset has low cost – high benefit strategies, that asset may get more of the flexible budget then intended. It is important to ensure that the benefit and costs for each asset are normalized prior to running a cross asset analysis.