There are multiple False Assumptions associated with Area Cost Factors. As a result, more than 40 years after the introduction of area cost factors (ACFs), the federal government and most other public sector facilities owners are no closer to its goals of having construction cost estimates match actual construction costs, or properly adjusting for regional (location based) variances.

Definition of Area Factor – A multiplicative value used to reflect relative geographical cost differentials. They are used in the development of construction cost budgets and project estimates.

The use of area cost factors (ACFs) for capital planning budgeting or estimates for construction repair, renovation, and new build projects remains a fundamentally flawed approach.  Examples of areas cost factors and economic factors include, RS Means City Cost Cost Index, ENR, GSA, and DoD Area Cost Factors.  It’s been over 40 years since ACFs and the computerized use of ACFs have been introduced, and their initial concept and their use remains a significant barrier to construction cost visibility and transparency.  ACFs have proven to be flawed, and not capable of reliable providing valid estimations of construction costs for specific locations.

There is overwhelming statistical significance and audit reporting that the cost estimates used to for physical infrastructure decision-making are highly and systematically misleading. The result is the misuse of billions of dollars.

ACFs, and other forms of location factors, cost indices have been evaluated by several independent sources and through actual practices and proven not to be capable of providing a workable budget and/or reasonable estimate for repair, renovation, or new build construction projects.

Area cost factors (ACFs) are typically used to adjust national average cost data, and/or historical costs to a particular location, or to use a previously developed cost estimate for a different location.   The use a single factor to adjust ­all costs in an estimate which discounts the different impacts that local and regional markets have on labor, material, equipment, and productivity. Errors in estimation caused using these adjustment factors result in a corresponding cumulative impact on the overall error of estimates. Area Cost Factor assumptions erroneously posit that productivity is constant for all locations. In fact, many data publishers make the disclaimer that “productivity is not considered” in their location factors.  Similarly, applying a cost index to labor is a poor practice as labor costs vary widely by trade. Currently available cost factors are simply incapable of accurately representing local market factors and costs.  Variances in labor, material, equipment, productivity, and means and methods cannot be accounted for by simply using a cost factor.  Indeed, using cost factors result in errors of -25+% to +40%” at best and 150% to 6x at worst depending upon their specific application.

The net effect of using ACFs is lack of confidence among both the user base, and those responsible for obtaining and approving sustainment and new construction funding. Significant government overpayments on both large capital projects and the numerous on-going repair, renovation, and maintenance projects remain the norm.

Real property owners would be far better served using verifiable and current locally researched detailed line-item construction cost data for all construction related planning, procurement, and project delivery activities. Furthermore, adoption of best value LEAN construction planning, procurement, and project delivery would not only provide higher cost visibility and transparency, but also assure the consistent delivery of quality of sustainment and new construction projects on-time and on-budget. T

DOD and congressional decision-makers may not have reliable estimates to inform their decisions regarding appropriations and the oversight of projects. – GAO

References

• 1981, NBSIR 81-2250 Estimating Area Cost Factors for Military Construction Projects: A Computerized Approach
• 1985, Cost overruns in public projects.
• 1990, Military Planning and Design Funding Requirements, Report AROIRI
• 2016, Investigation in Construction Cost Estimation Using Monte Carlo Simulation AFIT Scholar J.D Bucholtz
• 2016, Indefinite Delivery/Indefinite Quantity project selection framework using stochastic techniques
• 2018, Correlation between cost growth and procurement methods on USACE construction projects
• 2018, Action Needed to Increase the Reliability of Construction Cost Estimates, Defense Infrastructure, GAO-18-101 The Chapter 5 paper presents a statistical analysis on the performance of twelve existing