One of the key aspects of the development of asset management is data collection. The way in which road organizations collect, store, and analyze data has evolved along with advances in technology, such as mobile computing (e.g., handheld computers, laptops, tablet notebooks, etc.), sensing (e.g., laser and digital cameras), and spatial technologies (e.g., global positioning systems (GPS), geographic information systems (GIS), Building Information Modelling (BIM) and spatially enabled management systems). The use of the aforementioned technologies has enhanced the data collection and integration procedures necessary to support the analyses and evaluation processes needed for asset management but at the same time has led organizations to collect very large amounts of data and create vast databases that have not always been useful or necessary for supporting decision making processes.
The data collection activities should be designed to support asset management decision processes at different levels. This should include a rational evaluation of what data should be collected to cost-effectively support the asset management decision. As asset management includes a variety and type of assets, one type of data, for example traffic, may be needed for multiple applications. Information for all asset needs should be considered when establishing the data collection program. Once the data needs are established, a data collection plan can be developed to outline the type and frequency of data collection. The plan should include procedures for quality control validation of the data. Once the data quality is confirmed, it can then be transformed into performance indices.