Advancing Computational Building Design 2018 Retrospective
After chairing the recent conference for Advancing Computational Building Design (#ACBD2018), I am left reflecting on three questions that strike me as critical to the way buildings are designed and constructed.
- What impact will computation have on the industry?
- What can we learn from it?
- How will we implement?
Adoption is Only the Beginning
Listening to our keynote presentation about leveraging tools and data to integrate computation into collaborative design, it occurred to me that the process needed to begin by enabling architects and engineers to leverage tools that create data. Specifically, they need access to useful data with a lifespan longer than the stage during which it was created. Computational design is no longer just about the forms that can be created within specified parameters. While those efforts led to the creation of our processes around this practice – and it has served the industry well – it’s time to move beyond those digital limits. The field of computation is increasingly complex, and growing in diversity, expertise, and clarity. While we digital computation practitioners agree that a database of information is not the end-all, though we seem to have responded to this challenge by creating more data to address the growing complexity of the process. In fact, the newest reality I heard addressed is that our industry, building owners, and clients alike are suffering from data overload. Which standards and metrics must we establish as the process matures?
Digital design modeling in the DLR Group studio. Photo © DLR Group.
I see experts in the field are approaching the conversation differently and are beginning to ask: “Why?” Once we understand the client’s values, we can offer our expertise through precise systems or certification metrics that best match a project’s computational goals. This relieves the pressure of forcing a design process into a box of auto-generated forms, and leaves room to select the outcome that best meets the project needs. It also becomes a value-added approach to any given building project, rather than a strict set of standards around which to mold the design process.
Finding a Common Language
Communication is still the axel that turns the wheels of progress. While there is a lot of new, explicit language presented at ACBD, there are also implicit lessons learned. This year, I recognized topics that have been developing over the past two conferences and noted an evolution in the way this knowledge is changing. The way this knowledge is evolving appears to follow a consistent innovation cycle. Using The Lean Startup by Eric Reis, we talked about treating a computational initiative like a startup to build a minimal viable product with your tools, then enter it into the innovation cycle. Once recognized, this cycle can then be applied to many other domains of knowledge that, in turn, can help identify where an organization is in that cycle and what needs to happen to move to the next level. We seem to be harvesting more data to offer meaningful insight into why certain actions or design choices affect the life of a building, yet many of these knowledge areas appear to be at the burden-of-proof phase. I also see that this particular phase is the point where most ideas stall out before moving on to mainstream adoption. I expect to see more advanced research coming from a variety of businesses and organizations in the coming year. It is easy to forget that computation is the process, not the outcome.