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The amount of data required for construction estimating lends itself to a Predictive Cost Model, which not only simplifies the entire process but automatically captures repetitive data from established sources. Models also provide an audit trail about the development of the estimate.
As an example in varying locations, construction costs in Alabama or Mississippi are only 70 to 80 percent of national averages; however, costs in New York, San Francisco and Anchorage are 130 percent of national averages. The variance between locations is 60 percent or more which is significant for construction programs involving many geographic areas. Location differences that affect estimates are established with RSMeans CCI (Construction Cost Index) which provides labor, materials and equipment cost data to a specific zip code.
With RSMeans national databases covering 900+ locations in the U.S., a cost model built from data for one location is easily adjusted to reflect regional costs anywhere in the country. This capability allows Predictive Cost Models to be used for evaluation of construction budgets as well as a negotiating tool and third party validation of contractor's bids. Engineers develop Predictive Cost Models in Means CostWorks™ a proprietary system that develops cost models that apply material and labor data from Means' extensive databases. When modeling data is linked to client benchmark data, the results can be extrapolated to any location in the U.S.
LINK TO BUSINESS CASE DOE
For more information and a web ex demonstration, E-Mail
Laura Dempsey, Senior Consultant
RSMeans Business Solutions
404-433-3583
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