We source and maintain current, LOCAL MARKET GRANULAR COST DATA that is superior to the traditional use of “national average cost data” and location factoring.
Significantly improve cost visibility and cost management for ALL your facilities repair, renovation, maintenance, and new build projects.
#1 Over 85,000 line items available. Granular line items for repair, renovation, maintenance, and new builds organized by expanded CSI MasterFormat. Also preventive maintenance cost data with costs and checks for every PM frequency, organized by TriServices expanded UNIFORMAT.
#2 Over 1.2 Million datapoints updated quarterly.
#3 Proven and in use by multiple public sector deparments and agencies.
#4 Supported by secure cloud technology and information management practices (NIST, CMMC LvL 3 compliant) enabling Program, Project, Proposal, Estimate, Workorder, Document, and Issues/Task Mangement, and more.
Supporting Reference Information:
Independently reported issues with 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
- In the United States, RSMeans and other published construction cost data are useful for estimating the overall cost of a project. However, these are typically nationally aggregated mean costs and intended to be used with a local multiplier. Prior studies have found that locally adjusted RSMeans costs vary from actual local material prices. For example, Estes (2016) found that for a slab-on-grade foundation assembly with 0.1 m (4 inches) thick slab, vapour barrier and welded wire fabric in Baton Rouge, Louisiana, United States, concrete was found to be underestimated by 18% and vapour barrier by as much as 67%. Additionally, assembly costs for 0.1 m (4 inches) thick concrete slab were found to differ significantly (p = 0.004, α = 0.05) when comparing locally sourced costs and adjusted RSMeans cost data (Estes, 2016). Published cost data also lack accuracy due to the type and manner of data collected and represented. For example, RSMeans data do not account for variations caused by local codes, productivity rates, climate conditions, labour quality and availability, or costs related to land prices and permit fees (Ontario Construction Secretariat, 2001). (Kodavatiganti Y, Rahim MA, Friedland CJ, Mostafiz RB, Taghinezhad A and Heil S (2023), Material quantities and estimated construction costs for new elevated IRC 2015-compliant single-family home foundations. Front. Built Environ. 9:1111563. doi: 10.3389/fbuil.2023.1111563
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Four BT, LLC – www.4bt.us – Exclusive supplier of current, LOCAL MARKET GRANULAR COST DATA and supporting cloud technology, as well as full support services for Program, Project, Proposal, Estimate, Workorder, Document, and Issues/Task Mangement, and more.