Their are multiple issues with using national average cost data bases, with or without associated location factors. These are described below. Properly developed locally researched detailed unit price cost data provides unparalleled cost visibility and transparency.
Here are a series quotations from independently published research papers or professional articles noting the issues associated with the use of location factors.
“Location factors are used during preliminary project evaluations. They are not intended to be used when preparing appropriation-quality estimates. They often are applied to conceptual estimates for identifying “go/no-go” projects at an early stage.” (Peitlock, B.A., ccc, Developing Location Factors Using a Factoring Method, International Cost Engineering Council, ICEC International Cost Management Journal (ICMJ), 1998.)
Location factors are primarily used in class 4 and 5 estimates and are not intended to be used for higher quality estimates, such as class 3, 2, or 1. The RSMeans city cost index (CCI) and the Department of Defense area cost factor (ACF) index are two primary examples of location factor publications. (Martinez, A., Validation of methods for adjusting construction cost estimates by project location , University of New Mexico UNM Digital Repository, 2010)
“Despite its potential weaknesses, estimation by adjustment factors is a very common approach for all types of construction. A very common approach for performing quick-order-of-magnitude estimates is based on using Location Cost Adjustment Factors (LCAFs). The accuracy of cost estimates in the early phases varies within an expected range that spans from -100% to +200% ” “Using the results of this study, various commercial entities (e.g., RS Means) could enhance their online tools by uploading publicly available socio-economic variables and allowing users to perform geostatistical analysis. As a result, a cost engineer could input the location of a project and obtain the most accurate location adjustment factor through a mix of interpolation and geostatistical prediction techniques.” (Migliaccio, G., Empirical Assessment of Spatial Prediction Methods for Location Cost Adjustment Factors, J Constr Eng Manag. 2013)
“Problems within the methodology, unfortunately, will continue to arise as standardized estimation tools (CCI) simply cannot account for the unique characteristics of individual states. Unfortunately, the accuracy of program-wide CCIs occasionally led to swings of ±20 percent after projects had gone through the bidding process. Additionally, no direct application of market or economic conditions existed in this conventional CCI process, which was theorized by FHWA to potentially be a significant influence on resulting project estimate accuracy. ” (University of Colorado Denver College of Engineering and Applied Science Department of Civil Engineering, Validation of Project-level Construction Cost Index Estimation Methodology, 2017
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