“A Comparative Analysis on Data Collection For Assisting Investment Decision Techniques of Asset Management” |
Transportation agencies engage in extensive data collectionactivities in order to support their decision processes at various levels.However, not all the data collected supply transportation officials with usefulinformation for efficient and effective decision-making. This research presents research aimed at formallyidentifying links between data collection and the supported decision processes.The research objective identifies existing relationships between AssetManagement data collection and the decision processes to be supported by them,particularly in the project selection level. It also proposes a framework foreffective and efficient data collection. The motivation of the project was tohelp transportation agencies optimize their data collection processes and cutdown data collection and management costs. Asset Management is a strategic approach to the optimalallocation of resources for the management, operation, maintenance, andpreservation of transportation infrastructure (FHWA 1999). The concept of AssetManagement combines engineering and economic principles with sound businesspractices to support decisionmaking at the strategic, network, and projectlevels. One of the key aspects of the development of AssetManagement is data collection. The way in which transportation agenciescollect, store, and analyze data has evolved along with advances in technology,such as mobile computing, advanced sensors, distributed databases, and spatialtechnologies. These technologies have enabled data collection andintegration procedures necessary to support the comprehensive analyses andevaluation processes needed for Asset Management. However, in many cases, thedata collection activities have not been designed specifically to support thedecision processes inherent in Asset Management. As a result, the use of theaforementioned technologies has led agencies to collect very large amounts ofdata and create vast databases that have not always been useful or necessaryfor supporting decision making processes.