Primary Author: Mr. William E. Kraus P.E. CCP
Audience Focus: Intermediate
Application Type: Application
Venue: 2014 AACE International Annual Meeting, New Orleans, LA, USA
Abstract: This paper addresses an aspect of Asset Historical Database Management described in 6.3 of the TCM Framework. Actual benchmark data is stored in a database in order to provide historical project information (10.4 in the TCM Framework). Unit costs bid on projects nationwide over a 20-year timeframe reside in the database and are available for comparison with estimated values. Unit costs from projects in the database provide a gut check for estimates under review. The database provides a means to store, catalog, analyze, and present historical unit costs to make the process of reviewing these as-bid costs more efficient as the historical bid costs were stored in a variety of media: hard copies filed in individual project files, historical cost files, and electronic copies stored in a variety of places. The process of searching out this information as well as normalizing the unit costs to the timeframe and location of a project for which an estimate was being prepared was both inefficient and time-consuming. Output for average, minimum, and maximum unit costs bid on the projects in the database is provided.
Audience Focus: Intermediate
Application Type: Application
Venue: 2014 AACE International Annual Meeting, New Orleans, LA, USA
Abstract: This paper addresses an aspect of Asset Historical Database Management described in 6.3 of the TCM Framework. Actual benchmark data is stored in a database in order to provide historical project information (10.4 in the TCM Framework). Unit costs bid on projects nationwide over a 20-year timeframe reside in the database and are available for comparison with estimated values. Unit costs from projects in the database provide a gut check for estimates under review. The database provides a means to store, catalog, analyze, and present historical unit costs to make the process of reviewing these as-bid costs more efficient as the historical bid costs were stored in a variety of media: hard copies filed in individual project files, historical cost files, and electronic copies stored in a variety of places. The process of searching out this information as well as normalizing the unit costs to the timeframe and location of a project for which an estimate was being prepared was both inefficient and time-consuming. Output for average, minimum, and maximum unit costs bid on the projects in the database is provided.