Catalyst Revolutionizes the Preconstruction Process
Building Catalyst gives preconstruction professionals a powerful resource of knowledge - not just about cost - but also about the program and design efficiencies. Lead and inform decision making and problem-solving based on this new knowledge.
The benefits roll out in three ways - by predicting, optimizing and steering project outcomes:
The secret is found in a new form of data processing called big data. Construction's complexity requires big data to properly handle the high variety of attributes that determine outcomes.
The Power of Big Data
Building Catalyst gives you the ability to predict and steer project outcomes based on dozens of interacting variables or attributes. The results are remarkable - enabling you to far more accurately predict outcomes at any stage in the preconstruction process - and at a fraction of the time and effort.
A study of 100 projects across several building types, states, and produced a variety of builders shows this. Critical data entities were taken from each of these projects – data that would be available prior to the start of schematic design. From it, the building program, key parameters, schedule, and costs are predicted, then compared to the actual results.
Using a bounded range of 8% of the direct building costs (excluding site work and indirect costs) predictability varies dramatically based on the metric basis. In each case, all project results were normalized to the same location (St. Louis, MO) and construction start (2020). In the first case, costs were averaged by Building Category (i.e. Hospital). As shown below, only 17 of the project's actual building costs (per GSF) fell within 8% of the average. In the second case, getting more granular, the averages were taken by Building Type (Critical Access Hospital, Rehabilitation Hospital, etc.). In this case, the predictability increased dramatically to 53%.
The third case applied the big data approach - starting with the Building Functions (Emergency Treatment, Patient Bed, Exam Room, etc.) but also accounting for the number of floors, quality classification, plus a dozen or so other attributes. As shown below in 85% of the projects, the actual versus predicted costs were within 8%.
These results are especially remarkable given the unconditioned data that was available. As data quality processes improve, you will see even better predictability. Put the power of knowledge and automation in your own hands to more effectively plan, estimate and delivery projects.
Want to explore further? This Overview shows you how projects are created, defined, and reported in Building Catalyst.