biscoPro calculates materials, labour, sub trades, hire equipment, in fact any type of resource required for a building project. It can automatically update price and cost updating from suppliers or other sources. When the project proceeds you can create create purchase orders automatically.
The user can choose what is included in the estimate and the level of detail required so that the estimate is appropriate for the phase in project life cycle.
Some more detail
Our interface exposes all of the available properties from the CAD database and appends any additional information required to ensure accurate estimation of the design. Once we have the information from the CAD model in a standardised format we can use if for further processing.
Our estimating methodology, a technology we developed called Feature driven Activity Based Intelligent Costing (fABC or Faebic). This methodology uses information from 3D CAD models to identify features that drive changes in cost and then use traditional Activity Based Costing to estimate the cost of these features. This methodology captures the decision-making knowledge of the estimator and uses the information from the CAD application to connect this to the costs for building different components to determine the cost of complete structures.
An example might be a concrete slab, which has features of thickness and strength so we use these, plus the volume to determine material quantities and labour. A feature of the slab might be that it is actually first floor slab so therefore fABC will allow for formwork, concrete pumping, reinforcing and extra labour.
We have subsequently discovered that Stanford University in the US have also researched feature based cost estimating. Their research found that this method was 17% faster on small projects than traditional best practice estimating and up to 50% faster on large ones but more importantly it was 99% repeatable and more complete. Comparing the methods against an ideal estimate feature based estimating scored 86% for completeness against only 68% for best practice. The difference was even greater on revisions where best practice achieved only 29% and feature based a massive 92%.
Source: A feature ontology to support construction cost estimating. Staub-French, Fischer, Kunz, Ishii, Paulson
biscoPro also includes manual estimating inputs so you do not have to use only a 3D model as the input you can also input via a manual form or an Excel spreadsheet.
