Cover Image

Not for Sale

View/Hide Left Panel
Click for next page ( 44

The National Academies of Sciences, Engineering, and Medicine
500 Fifth St. N.W. | Washington, D.C. 20001

Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement

Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 43
8 Estimating Soft Costs for Major Public Transportation Fixed Guideway Projects S.3. Soft Cost Expenditures: As-Built Analysis This report analyzes a database assembled by the Federal Transit Administration of as-built costs for 59 rail transit construction projects in the United States over the past four decades (summarized in Figure 3) and concludes that: The current industry practice of using percentage add-ons for soft costs appears to be a valid approach to estimating soft costs. Project characteristics such as complexity, mag- nitude, mode, context, and others identified by industry estimators are correlated with soft costs in dollar and percentage terms. Soft cost expenditures have averaged around 30% of construction costs, with a range across all projects of between 11% and 54%, depending on the characteristics of the proj- ect, as Figure 3 indicates (outliers excluded). Cost estimators typically begin estimating soft costs with average percentages that corre- spond closely to historical averages for each soft cost component, as Table 3 shows. However, actual soft costs in past projects have shown a wider range of variability than estimators currently use. While estimators report choosing from within a range of around 20 percentage points, past projects have varied within a range of around 40 percentage points (outliers excluded). Some variability in soft costs cannot be explained solely with information available to the estimator prior to construction. The statistical analysis applied in this research was able to explain around 60% of the changing relationship between hard and soft costs with data available during planning phases. This suggests that the remaining variability in soft costs must be estimated with a blend of science, judgment, and art. S.4. A New Approach to Estimate Soft Costs This report is accompanied by a guidebook that presents a new method to estimate soft costs for a planned transit project that is firmly rooted in historical experience. The Guide- book also serves as a primer on soft costs and takes the reader through a step-by-step process to estimate the relationship between a given transit project's hard costs and its likely soft costs, given certain characteristics about the project and its sponsor. Soft Costs (% of Construction) 60% 50% 40% 30% 20% 10% 0% Hud-Berg II Hiawatha Sacram. I Hud-Berg I Portland So Sacram. Fol Portland Int Charlotte LA Gold East LA Gold Pasa Sacram. So Portland W South NJ Pittsburgh N Portland Seg1 Pittsburgh I LA Blue VTA Tas E Pittsburgh II Denver SW VTA Capitol Phoenix CTA O'Hare DC U St. DC Anacost DC Addison DC L'Enfant DC New Ca DC Shady G DC Huntgtn DC Glenmt 1 CTA Douglas NYCT 63rd CTA Orange Baltimore DC Vienna MBTA Orang CTA Brown MARTA N-S Miami San Juan DC Anacost O DC Springfld DC Glenmt 2 DC Greenblt BART SFO Phil Frankf. NYCT Stillw Salt Lake St. Louis San Diego Light Rail Heavy Rail Figure 3. Historical soft costs by project and mode (outliers excluded).