“There is a magic in graphs. The proﬁle of a curve reveals in a ﬂash a whole situation — the life history of an epidemic, a panic, or an era of prosperity. The curve informs the mind, awakens the imagination, convinces.” Henry D. Hubbard, National Bureau of Standards, 1939
Whether you realize it or not, some aspect of your life is driven by data. We rely on smartphones for up-to-minute social media updates from our friends. We check the weather app before looking outside. We use Fitbits to make daily decisions about our health. We live in a world where almost every aspect of our daily life is, in some way, influenced by the consumption or creation of data. We generally accept this new reality with open arms even in the face of emerging privacy and surveillance concerns.
There can be no doubt that the architectural design process has become more and more ‘datafied’ as new technology is adopted. CAD turned drawings digital, and BIM made buildings virtual. Alongside the artifacts of 2D document sets exist sophisticated containers 3D geometry and queryable databases. Yet with all data our disposal, as an industry, we still give priority to the artifacts of the process rather than the living data sources that created them.
Data has been described as the new oil for the digital economy. Is the building industry mining all it can from this raw, renewable resource? Within the world of building design, we are starting to see a new paradigm take shape that leverages data as the fuel for creativity and the means for delivering value: Data-Driven Design.
To put it quite simply “Data-Driven Design” is a process that makes use of quantitative and qualitative data as the driver of design decisions. Beyond convincing clients of a design’s apparent ‘elegance’ and ‘beauty’, data is used to gain insight into performance and is used to demonstrate value with the client and end user in mind.
Will the hospital provide optimal daylight values proven to reduce patient recovery time? Does this commercial building comply with cost and constructability constraints? Can the stadium box seats provide spectators with the best possible viewing experience?
The answers to these types of questions come from meaningful applications of data to prove the concept. Here are some ideas to consider:
Leverage BIM for what it is…not what it replaced
We can’t have a conversation about data in the building industry without refering to BIM. Building Information Modeling is a ubiquitous concept to describe how building teams are delivering work today. However, more often than not, we tend to think about BIM as another production tool akin to CAD. Whereas CAD replaced the 2D drawing, BIM is often thought of as a faster version of CAD capable of managing the document sets we have been familiar with for decades.
The opportunities for using the latent data present within BIM to impact the building lifecycle costs are still rarely capitalized on within design practice. However, this is changing as new data requirements are introduced and required. For example, in 2014, Singapore made electronic BIM submissions a requirement for buildings over 5000 square meters as part of its roadmap towards ‘smart cities’. In another part of the world, the UK intends to require 3D BIM submissions as part of all government projects by 2016.
Beyond a mode of production, I like to think of BIM is our industry’s current database “schema” for design, delivery, construction, and operations. While this will no doubt evolve in the near future, BIM is central to a data-driven design process.
Embrace a new skillset: computation and automation
If BIM is the industry’s “data schema”, computation is the processor to make our data usable. Computation involves the novel application of algorithms, scripts, and other workflows within the building design process. Within a design process, this might result in a flexible parametric model capable of conforming to constraints and data. Computation might also come in the form of a script which is used to automate complex data so a designer can more freely explore the possibilities within a design problem.
When I do strategic consulting engagement, I often enquire about staff skillsets. Do you have programmers on staff? Do any designers use tools like Grasshopper or Dynamo? Can anyone script? These types of skills are invaluable if your firm is embracing a data-driven workflow.
Measure your design through testing and simulation
Buildings are large, costly, and take a long time to make. Wouldn’t you want to know how it might work before it’s occupied? Whether we realize it or not, we are not strangers to simulation. When Gaudi made his hanging chain models for his cathedral designs, he was creating an analogue structural simulation model to define optimal curvatures and vaults. Yet while we praise such ingenuity in architectural history, digital simulation has still yet to be adopted as a commonplace activity within the mainstream architectural design process.
But that may be changing as simulation tools become less expensive and models become less time consuming to produce. I often hear of teams producing energy models only at the latest stages of design when most decisions have been made. These models have traditionally required specialist modeling and were time consuming endeavors. Today, there are many solutions hitting the marketplace focused on providing more intuitive, fast, and iterative analysis solutions. If I put myself in the owner’s shoes, I would want my design team to show me that it’s going to perform before I pay the money to build it.
Gain insight and predict outcomes with analytics
Analytics gives us the means to make sense of the data at our disposal in order to discover trends and predict outcomes. In the design process, analytics might involve quickly consuming and understanding program requirements through visualization. As a design develops, analytics can enable a designer to effectively compare analysis data in order to determine design options with the best performance.
For a successful implementation of analytics, design teams need to have a skillset in using data as a medium. With analytics, teams will be challenged to validate and structure their data as fluidly as they would compose and coordinate their drawings.
Towards a Data-Driven Practice?
Statistician W. Edwards Dennings once remarked “In God we trust. All others must bring data.” Building teams are increasingly seeing new data requirements in their deliverables, there are new targets to meet for performance, and clients are expecting teams to provide evidence that they are getting the best possible design. Meanwhile, our desktops and servers are filled with untapped resources for delivering value through design.
Personally, I think design could use a little more proof…
Are you interested in leveraging data in your firm?
- We can help you define your firm roadmap for innovation with data.
- Take one of our data-driven design workshops.
- We can work with you to validate and visualize your data.