The combination of unit cost benchmarking and systems-thinking can yield dramatic reductions if both financial and economic waste spanning all aspects of built environment lifecycle management.
Process Transformation
- Objective, verifiable, locally researched granular repair, renovation, maintenance, and new cost data organized using standard data architectures, terms, and definitions. (Note: Market average cost data and the use of location factoring is not a viable substitute.)
- Consistent application of robust, systems-thinking based Planning, Procurement, and Project Delivery process frameworks – Standardized processes and data
- Intelligent sourcing
- Focus upon long-term mutually beneficial relationships between owners, products and services providers, and the community
- Development and monitoring of quantitative performance indicators
- Continuous, competent and accountable governmental and real propery owner leadership
Cross-functional approach
The of standardized cost data through integrated, interoperable services, to deliver cross-domain insights enables evidence-based decision-making.
4BT exclusively provides local market cost data, tools and services to enable verifiable project costing, superior cost visibility, and superior cost management capability.
- Improve Project Control: Gain local market labor, material, equipment and productivity visibility to manage projects proactively from day one.
- Enhance Decision Making: Make informed decisions based on realistic, verifiable cost projections and time requirements.
- Reduce Delays and Overruns: Mitigate change orders to prevent project delays and cost overruns.
- Better Resource Utilization: Allocate resources efficiently to optimize productivity and reduce waste.
- Increase Stakeholder Confidence: Transparent proposals and reporting builds trust among owner and design-builder project teams.
- Scalable Solutions: Secure cloud technology hosted on Microsoft Government Cloud Environment. CMMC-LvL 2 compliant for DoD applications.
References:
#1. – “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.)
#2. 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)
#3. “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)
#4. “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)