Don’t Under Estimate: Building Information Modeling (BIM)
BIM’s been around the block!
Building information modeling (BIM) has been around for about 40 years now. Yes! You read that right – 40 years. Though in the 1970s when the concept was developed, BIM (as we know it today) wasn’t really implemented until the late 1980s. So I guess we can say, it has been a little slow taking hold. However, as time has zipped on and technology has improved, BIM implementation has rapidly increased.
Job cost estimating benefit
Building information modeling started as a production of 3D design models to help catch architectural system variances and clashes. Since then, it has become an effective tool in project management and ever more prominent in job cost estimating.
Traditionally, estimators begin their process by doing manual take-offs or digitizing architectural construction drawings. Or possibly, they may be importing CAD plans into an estimating software package. The thing about these processes is that they all have higher risk of error by way of unknowingly incurring an omission or duplication. This has the potential to logarithmically propagate cost errors throughout the estimating process.
Using a BIM solution can significantly reduce (though not completely deny) human error. As the project experiences changes, as they always do, the model can be updated. If properly configured, the BIM should update the takeoffs, schedule, and costing data for the project as the changes occur.
Integrates to accounting
After the BIM is established, pricing information is the next critical set of data which needs to be considered. Estimators can extract the quantities provided by the building information modeling solution and output the information via linking it to a product such as Sage 300 CRE. From there, an estimator may generate estimates based on historical data.
Some of the most critical tasks in estimating are having accurate and current takeoff information, and applying that to accurate pricing and scheduling data. BIM solutions can help to make the quantification tasks easier and more accurate. The integration of this data into an estimating solution can mean that estimators are more accurate and can spend their time and knowledge doing higher value activities.