![Image result for RS Means](data:image/png;base64,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)
RSMeans cost data is a highly useful and necessary tool. They provides accurate and up-to-date cost information to help owners, developers, architects, engineers, contractors and others carefully and precisely project and control the cost of both new building construction and renovation projects.
Means publications keep track of the costs for you, along with a wide range of other key information, including city cost indexes, productivity rates, crew composition, and contractor’s overhead and profit rates.
RS Means is a division of Reed Business Information that provides cost information to the construction industry so contractors in the industry can provide accurate estimates and projections for their project costs. It has become a data standard for government work in terms of pricing, and is widely used by the industry as a whole.