It was emphasized in the Application Catalog that a management system feature to trade off cost versus performance is a sterile exercise if the decision-maker has no framework of performance expectations. Developing such a framework requires four main ingredients: 1. An agreed-upon set of defined performance measures;
2. A process for determining reasonable and achievable performance objectives;
3. An accountability process to create incentives for all involved parties to strive toward those objectives; and
4. A way to tell, at any given time, how well the objectives are being met.
All of these ingredients imply information technology requirements. The first of these is given greatest emphasis because, at today’s state of the practice, a large number of organi- zations lack the basic set of definitions that make the other ingredients possible. For the purposes of IT design, performance measures can be grouped in the following categories: 1. Raw condition data, such as bridge element condition states, pavement roughness and
rutting, sign reflectivity, and average grass height;
2. Raw performance data, such as travel time, accident rates, and customer satisfaction survey results;
3. Normalized performance indexes, such as a zero to 100 “health index” scale of facility condition, a safety index representing facility accident risk, or a customer satisfaction index representing the impact of a wide range of facility conditions on satisfaction survey results; and
4. Economic performance indicators, such as avoided future agency costs, user costs, asset valuation, and benefit/cost ratios.
These four categories are arranged in the order in which they are usually implemented. Each relies on all of the ones before it for inputs to the calculation. Each contributes in its own way to the realization of the needed performance framework.
Raw condition data can be standardized on an industry-wide basis, because it is quite repeatable from one agency to another. For example, the AASHTO CoRe Bridge Elements, adopted by AASHTO in 1995, have been widely accepted by the states as a basis for bridge inspection and bridge inventories, even though there is no Federal requirement that they be used. AASHTO is also currently starting the process of standardizing highway maintenance elements in the same way. With this standardization in place, the
NCHRP Project 20-24(11)
Task 2 – Asset Management Framework
private sector will be in a position of lower risk to develop data collection equipment and inventory systems to make the routine calculation of performance measures possible. Raw performance data may also be standardized relatively soon, because this, also, is uni- versal. Even in the absence of industry standards, organizations can safely develop a set of basic raw performance measures without worry that a future industry standard will be much different. The key here is to stick with basic transportation values that are a part of every transportation agency’s mission, such as travel time, reliability, safety, comfort, customer satisfaction, and security.
Raw condition and performance data are the outputs of the Performance Monitoring application, serving then as inputs to needs identification, policy development, and long- range planning. Raw condition data are also used in conjunction with work accomplishment data to develop predictive models for planning purposes, especially facility deterioration and cost estimation. Because these raw indicators are highly objec- tive, they can form the basis for performance objectives for many parts of the asset management process. Using deterioration models, even existing asset management sys- tems can predict the outcome of policy and project decisions in terms of raw condition measures. Existing transportation planning tools can often predict raw performance sta- tistics as a result of certain types of infrastructure investments. Existing asset manage- ment systems can also summarize the current raw condition data for the inventory, to tell decision-makers how they are doing at any given point in time.
Raw condition data are often too detailed for certain purposes, especially routine reporting of the state of the system to elected officials and the public, and budget negotia- tions. For these purposes, it is useful to develop summary normalized performance indexes that are not specific to asset types and do not require an engineering under- standing of the component’s functional role. California, for example, has summarized the conditions of 108 types of bridge elements into a summary indicator, the Bridge Health Index, describing the overall health of a bridge or the inventory as a whole. This approach could be extended to other types of assets, since it is defined in a way that is related to asset valuation and not tied specifically to bridges.
Performance indexes form a very good basis for State-of-the-System reports delivered routinely to elected officials and the public. With a complete inventory and Performance Monitoring process in place, these reports can be updated on a frequent basis or on demand. Performance objectives for the agency can be developed and tracked on this basis, as is already done in several states. Several state DOT web sites have very good examples of public reporting of agency performance using summarized indexes.
The calculation of normalized performance indexes would logically be another output of the performance monitoring application, since that application has all the necessary inputs to the calculation and since several other applications would use the results. Agencies should not wait for this to be standardized on an industry-wide basis, since there is no guarantee that that will happen any time soon. Instead, define an indicator scale that makes sense and is consistent across all asset types, that can be computed with readily available data.
NCHRP Project 20-24(11) Task 2 – Asset Management Framework
Economic performance measures are still somewhat controversial, in that they are highly processed in relation to the raw condition and performance data from which they are cal- culated. However, this level of processing has some very attractive benefits: it permits comparisons to be made across different types of agency objectives; it provides a uniform, objective way to compare project benefits with costs; and it supports comparisons to be made with non-transportation investments. Economic benefits are widely used in pave- ment and bridge management systems because they facilitate an automated calculation of relative priorities of maintenance investments.
Economic performance measures often require a knowledge of maintenance and improvement alternatives that are available to the decision-maker, so they require infor- mation found in the needs identification application. This would be a logical place to calculate them. The outputs of this process are useful to policy development, long-range planning, prioritization, budgeting, and resource allocation.
In the past, the definition of economic performance has been closely tied to specific pave- ment or bridge management systems, each system choosing a definition that is convenient for the analytical framework used in that system. It is unlikely that there will be industry standardization of these measures any time soon, but the number of definitions used in existing systems is quite limited. Calculations to convert one definition to another are possible, and can be provided within an agency’s own data interfaces.
Establishment of a performance measurement framework is on the critical path for asset management maturity in many agencies. It is tempting to spend a lot of time agonizing over these definitions, fearing that they will be difficult to change later. To a certain extent this fear is justified, because performance measurement systems do have some inertia. However, the potential to spend extra time on refinement is almost unlimited, so man- agement must set a clear process and time constraint to get the job done, allowing suffi- cient time for thorough discussion and negotiation, but no more. Six months is generally sufficient for most transportation organizations.