If you are using “industry leading cost data” and “following the pack” , then it’s time to optimize construction cost visibility and management.
Many organizations, especially in the public sector, are resistant to change. The belief is that there is safety and surety in maintaining the ‘status quo’. The net result is a failure to adopt innovative, productive, and cost saving solutions.
The following is a direct copy of a recent solicitation for “Construction Cost Estimating Software”. I have inserted informational comments in “red” and would love to hear your comments.
The acquisition of software to enhance the accuracy, efficiency, and competitiveness of our construction cost estimation process, acquiring RS Means is a strategic necessity. RS Means is a comprehensive and industry-standard database of construction cost information, offering detailed and up-to-date pricing data across a wide range of construction activities, materials, and labor. (RS Means is indeed a comprehensive industry standard database and very useful for reference purposes. It does not, however, provide up-to-date pricing for local market conditions. Price books are created annually and quarterly updates are provided using factors, called a CCI. The use of factors has been shown to introduced significant errors in costs. It is also important to not the CCI is only based 66 materials, 21 trades and six pieces of equipment (plus fuel and maintenance costs, and reflective of a comparsion to thirty (30) defined ciities throughout the United States. Further more RS Means notes that CCIs should NOT be used to to compare construction prices across different years, to predict price trends over time and for a specific location or to adjust for local requirements, union practices, and building codes.)
With the dynamic nature of construction costs, the need for accurate, region-specific data is critical for project planning, budgeting, and ensuring that estimates reflect real-world conditions. (Construction costs are indeed dynamic and highly influence by local market, regional, and national factors. That said, the only objective and verifiable method of creating a dependable estimate for a local site is to use locally reserached labor, material, and equipment costs applied to granular construction tasks based upon relevant commercial construction means and methods. The latter is not accomplish with RS Means to the level available from alternative sources.)
The following key points highlight the importance of acquiring RS Means:
Accurate Cost Estimation: RS Means provides reliable cost data for both new construction and renovation projects, ensuring that our estimates are based on current, localized market trends. (Most importantly it is important to understand an “accurate cost estimate” is a falacy. Accuracy requires a datum, and a construction cost estimate lacks any quantitative, reliable datum. Construction estimates and be objective, verifiable, and granular.)
This level of precision will help reduce the risk of underestimating or overestimating project costs, leading to better financial planning. (There is no basis in fact for this statement. Independent authors have noted that RSMeans costing methodology can result in significant error due to the reliance upon national averages and CCI factoring, resulting in both overestimating and underestimating. See References below.)
Time Efficiency: RS Means includes a wide range of pre-built formulas and unit costs, which will streamline the estimation process. This allows our team to produce detailed and accurate estimates faster, saving valuable time on each project. (Speed in estimating comes from the use of a standardized data architecture, such as expanded CSI Masterformat and the associated aggregation of construction activities basis upon commercial standards. Again, while “accurate estimates” is a misnomer/oxymoron, a more reliabe estimate for a specfic location can be achieve using local market labor, materials, and equipmetn data that is readily availabe via altenative sources.)
Industry Credibility: As a widely recognized and trusted source, RS Means data will enhance the credibility of our estimates with clients, contractors, and stakeholders. This will contribute to building trust and maintaining a competitive edge in the industry. (RSMeans is known as an “industry leader” due largely to its long-term use and market presence. It is, however, known by most skilled professional estimators to be a research resource. In today’s environment, the ability to created verifiable local market cost estimates and to validate contractor and subcontractor bids is critical. This can only be accomplished using data that is locally researched and current and does not depend upon cost factoring, either location-based or economic.)
Comprehensive Data Coverage: RS Means offers a broad scope of cost data, covering various construction types, geographical regions, and market sectors. This breadth of information will support more informed decision-making for diverse project types. (RSMeans provides approximately 90,000-line items of cost data, alternative source provide comparable quantities.)
Mitigating Cost Overruns: With access to detailed historical cost data and trends, RS Means enables better forecasting of future price changes. This will allow us to anticipate fluctuations and incorporate contingency plans, minimizing the likelihood of cost overruns during project execution. (Historical cost data has very little, if any, influence upon forecasting future costs. Like the stock market, there are far too many variables that cannot be quantitatively considered to provide any significant level of predictive precision. While some organization may have and may continue to market the ability to predict future prices and costs, the ability remains elusive. The real source of cost overruns lies in poor organizational leadership, poor processes, use of improper data, and a lack of accountability.)
Care should be given as to what form of cost data is being used. Objective, verifiable, and locally researched detailed line-item construction tasks, replete with labor, material, equipment and productivity information, provide the highest level of cost visibility and cost management capability. 4BT exclusively offers this information for any location, with all line-items organized using expanded CSI MasterFormat, enabling clear communication, collaboration, and alignment with all technical domains and participants throughout the planning, procurement, and project delivery lifecycle.
Other, less stringent forms of cost estimating include the following:
- national average line-item cost data (with or without adjustment or localization factors),
- system level cost data,
- assembly level cost data,
- building level,
- and/or other forms of parametric cost data,
- historical cost data and economic factoring,
- contractor, subcontractor quotes.
[NOTE: UNIFORMAT is best used to express functional elements (assemblies) of a repair, renovation, maintnenance, or new build project). It provides a consistent approach that describes associated components across different projects in cost and function. It’s primarily use is in early stages of a project where a specific work scope (scope of work/SOW) has not been fully defined and critical characteristics of the projects not yet been determined. MasterFormat, accounts for specific details of practical knowledge and terminology inclusive of means nd methods, and is primarilpy used at stages of a project where enough particulars and specific work scopes have been established, such as when a project is ready for procurement, or for the development of a reliable cost.]
Metrics for a Construction Cost Database
#1 Verifiable – All components are traceable, including labor, material, and equipment costs.
#2 Current – Cost data has been updated within the past quarter.
#3 Standardized, Easy to Understand, and Uniquely Identified – Common industry terms and definitions are used for all construction, repair, renovation, and maintenance task. Data is organized using a standard data architecture such as CSI MasterFormat or expanded UNIFORTMAT.
#4 Detailed – Data is presented at a granular level sufficient to support line item estimating.
#5 Local – Data is locally researched and does not rely upon location factors or economic factoring.
“Prevailing wage” is equivalent to the wage paid to at least 30% of workers in a given trade in a locality.
References:
Multiple independent sources have noted the issues associated with using national average cost data and location factors as noted as follows.
“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, labor quality and availability, or costs related to land prices and permit fees
(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) Front. Built Environ., 21 May 2023 Sec. Construction Management Volume 9 – 2023 | https://doi.org/10.3389/fbuil.2023.1111563)
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