The NCDOT operates the second largest State-maintained highway system in the Nation, which includes more than 78,000 centerline miles of highway and 17,250 bridges collectively spanning 380 miles. The highway system is divided into 14,616 miles of primary highways (Interstate, U.S., and N.C.) and 63,467 miles of secondary roads.
The NCDOT is in the early stages of developing a comprehensive Asset Management system. The agency has several operational engineering management systems, including pavement, bridge, and maintenance management systems that can support decisions regarding individual asset classes independently. However, these systems have not been integrated in a holistic Asset Management system.
Overview of the Agency's Decisionmaking Processes
The NCDOT's Asset Management division is organized in eight operational units: bridge maintenance, equipment and inventory control, intelligent transportation systems, oversize/overweight permits, pavement management, roadside environmental, secondary roads, and state road maintenance. This review focuses on the state road maintenance unit, which is the largest unit in terms of personnel and budget. The unit operates the agency's MMS, collects road maintenance data, and provides support to other units that use the MMS program. The MMS is operational; however, some of the decisionmaking processes are still being defined and developed.
Geographically, the State is divided into 14 local division offices that report to the Asset Management division. This division recommends to the board of transportation the distribution of maintenance and resurfacing funds across the 14 geographical divisions and 100 counties, and it provides various program funding and expense reports for field operations and central units.
The field division offices are responsible for implementing the programs and policies established by the board of transportation under the supervision of the State highway administrator and the chief engineer of operations. These division offices are responsible for construction, maintenance, roadside environmental programs, traffic services, and the fiscal and facility operations involved in administering these functions.
The decisions regarding fund allocation and program delivery for the various organizational units can be divided as follows:
Tradeoffs among investments in different types of assets and units are made at the legislative level. These decisions are not directly based on analysis of condition information, though they use some of the information provided by the engineering management systems. This procedure is expected to change once the agency fully embraces a comprehensive Asset Management approach for the allocation of resources.
Maintenance Management System Overview
The condition of the network for the MMS is assessed periodically using a statistical sampling procedure. The condition of the sample of roads assessed is used for estimating the overall network condition based on certain predefined defects, (e.g., low shoulder). Once the overall condition is determined, the system selects feasible treatments from a list of corrective work functions that are defined for each defect type. Then the system recommends the most appropriate treatment for each condition rating. Appropriate work functions then are selected for these treatments based on generic performance guidelines included in the software. Last, the work functions assigned are used to estimate the funding required for the defect to an acceptable level. The same process is repeated for all defects.
The MMS program uses the efficient frontier method to optimize the allocation of the maintenance funds. The analyst can determine the maintenance level of service (LOS) that can be achieved with a given budget or the budget required to achieve a desired LOS. The agency has defined minimum acceptable LOS for each defect.
The MMS is used to analyze the overall Statewide system and to develop the budget to be proposed to the legislature. Once approved, a formula (based on population, area, etc.) with asset condition as one of its factors is used to allocate the money to each division; however, the agency is moving toward using the MMS to allocate the resources and develop needs-based budgets using the efficient frontier method previously mentioned.
In addition to providing the budget, the central engineering office advises division engineers regarding the areas on which they should concentrate their efforts. The division engineers are responsible for all the different assets within their division, and they allocate funding to different asset classes. These decisions mainly are based on the division engineers' experience and knowledge about the area and the condition data provided by the MMS. The division engineers conduct the tradeoffs and are held accountable to meet the targets for budget and performance or LOS. They have access to the MMS, which can help them with the allocation of maintenance budget. Other units support division engineers with other information. Monthly meetings between the central office personnel and division engineers provide the division engineers with the needed data.
The agency purchased a commercial MMS software package through a contract that included installation and implementation of the system. The NCDOT staff worked closely with the consultants to develop a system that provides NCDOT with the methodology and computer tools necessary to plan, organize, direct, and control maintenance field operations.
The project started in 2001 with the consultant performing onsite interviews with NCDOT personnel located throughout the State. The consultants then conducted a series of subject matter expert orientation and work sessions, customized the software to make it compatible with NCDOT operation business practices, and interfaced it with the agency's existing databases and GIS. Upon the completion of software customization, two pilot division areas (divisions 3 and 9) were selected, and their personnel were trained on the use of the software. After making the necessary adjustments, the system was installed in all other divisions, and Statewide training started soon after.
Maintenance Data Collection
The road maintenance unit has a maintenance condition assessment program. The program periodically evaluates the condition of certain elements, collects and organizes the data, and analyzes the results to determine the LOS of the road system. Every 2 years, the road maintenance unit conducts a condition rating on a statistically representative percentage of the highway systems. The sample size was determined using a statistical analysis that allows determination of the repair cost with a maximum error of $150,000.
The evaluation is used to estimate percentage of asset at each performance level. Twenty-one different defects have been defined. The last inspection conducted in 2004 included samples from each division area. The sampling is performed on rural interstate as well as primary and secondary road systems. The urban road systems also were included in the inspections; however, the agency does not plan to continue to include urban roads in future campaigns. The data collected and the performance measures for different units were determined through committees that have been formed for the different types of assets. The committees will also decide what specific work activities are associated with particular performance measures. The data collected were revised for the first time in 1998. The director of the Asset Management division also is in the process of defining a strategy for handling a broad range of assets across the agency.
The NCDOT units involved in asset data condition collection are road maintenance, pavement management, and bridge maintenance. The road maintenance unit employs two or three data collection teams for each division. The pavement unit uses one team per county, and the bridge unit conducts the assessment using one team per division. Extensive training including distribution of detailed manuals is offered to the data collection teams before the operations. In addition, three quality assurance teams from the road maintenance unit assure the quality of the data collected for the entire State by reevaluating approximately 5 percent of the highway samples (randomly selected) covered by the division teams.
Road maintenance data are stored in a central database, but these data are not integrated with the pavement and bridge management data; rather, each division maintains its own condition database. In addition, preprocessed data from each unit are periodically fed to a State data warehouse, but no analysis has been done using these data. It is expected that once the new Asset Management system is implemented the output from the PMS and BMS also could be used in the MMS. The MMS data collection is done manually. The outsourced data collection cost included with the MMS implementation was approximately $1.5 million. It is expected that in-house data collection will cost less than half of that amount. The agency will conduct the first in-house evaluation in 2006.
It is clear from the case studies that there is no one-size-fits-all approach for Asset Management data collection. The most appropriate approach will depend on the agency's needs and culture as well as the availability of economic, technological, and human resources. A gradual implementation of the data collection efforts appears to be the most appropriate approach because it provides opportunities for adapting the processes as data is collected and experience is gained. Most of the data collected is being collected separately as of present for individual assets types that support decisions within their corresponding silos. However, as the agencies embrace the Asset Management philosophy, the need for more consistent data collection among asset types and locations increases. Furthermore, the availability of advanced multipurpose data collection equipment has made this type of data collection not only possible but also more cost effective.
There appears to be a trend toward outsourcing at least part of data collection. In this case, it is very important that the asset owner provide clear expectations in terms of the data to be collected, required precision, and quality control and assurance procedures to evaluate the collected data. One common characteristic of success stories is that the agency has emphasized the usefulness of the information by collecting the data that is needed to support the various asset management efforts within the organization.
The main highlights of the data collection effort and Asset Management implementation in the visited agencies are the following: