Saturday, November 30, 2013

Data Driven Design and Construction - Answers to Randy's questions

Randy started a new blog that will focus on Data Driven Design and Construction. He asked few questions in his first post. Here is my take, feel free to comment. I recommend you should follow his blog. He will be coming up with a book on this topic next year some time. I can't wait to read it. Here are his questions and my answers - 

  • How do we, as a discipline, capitalize on data and metadata to drive innovation in architecture and construction, just as other disciplines and industries have?
Evidence based design is one of the leading fields of research that will eventually result in data driven design and construction. Understanding the end user requirements better and designing products that reach to the highest level of customer satisfaction would require data driven design. On technology front, building information modelling (BIM), virtual reality and augmented reality will help collect the data related to customer requirement. Moreover, when construction is in progress real time data collection from different data points on construction sites, architect, engineer, contractor and supplier offices will help in making better decisions and reduce waste from construction processes. Once the facilities are built, sensors and different data collection tools in facilities will help improve the user experience and make the environment more productive and healthy for occupants. Moreover, greater energy efficiency and reduced water usage will be achievable.

  • What forces and technologies are coming together in the second decade of the millennium that make the gathering and use of data possible for industry practitioners for firms both small and large?
I think these technologies will facilitate data driven design
1)      Sensor Technologies
2)      Virtual Reality
3)      Augmented Reality
4)      Cloud computing
5)      Web
6)      Internet
7)      Faster and more powerful hardware (Smartphones, Tablets, Cameras, AI, Google Glasses etc.)
8)      RFID, QR codes and Smart Dust

Forces coming together to make data driven design possible

1)      Building Information Modelling (BIM) Adoption and Government Mandates
2)      USGBC – LEED Certification
3)      Lean Construction
4)      agcxml
6)      The construction open software alliance

  • Why is the architecture, engineering and construction (AEC) industry the last to discover – and utilize – data, for their benefit?
The reason lies in the following –
1)      Fragmented nature of the industry
2)      One of a kind product design and production
3)      Geographically dispersed production sites and project stakeholders
4)      Lake of single entities doing it all together

In other words - A number of players, who may or may not know each other, come together to build a facility that is one of its kind design and construction and it is to be built in a location that may or may not be known to everyone.

  • In what ways can design and construction professionals and owners benefit from capturing, collecting and using data in their building models?
Information is power, if you know how to use it right. This might sound like a cliché but this is true. Now a day not only having the right information but having the information in right format is also important. Meaning human interpretable and actionable information derived out of all the information received from different data points.

Using big data with right software tools will help design and construction professionals and owners to make better and faster decisions.

  • What implications does the DIKW hierarchy have for presenting findings to owners and others who may not be as data savvy?
DIKW (Data, Information, Knowledge and Wisdom) has huge implications as data in its raw format will be a disaster as we move forward and collect more and more data. Information overload is already a headache for lot of early adopters of technology. We would need tools and processes to present the data to lay man and DIKW has a big role to play.

  • What is the business case for implementing a data transformation within one’s organization?
Business case at this moment (in Nov 2013) is about -
1.      Reduced waste due to improved coordination using BIM (works very well for MEP guys)
2.      Improved hospital facilities designed using evidence based design
3.      Energy efficient facilities designed using data analysis
4.      Competitive advantage, especially with more and more government and institutional  mandates requiring the use of building information modeling (BIM) also for marketing.

  • How is data currently being used in the AEC industry?
At present data is being used in fragmented format. There are several authoring tools and several analysis tools and interoperability is a hurdle in harnessing the full potential of the available data.
Building Information Models (BIM) is used for producing drawings, estimating, scheduling, visualization, coordination and collaboration. I am not sure if BIM is successfully implemented for facilities management anywhere yet.
Second comes the data collected by building information management systems (BIMS), they should help improve future building design and improve existing facilities energy and water use. I am not sure if this is being done successfully either.
Moreover, information generated in design and construction process is used for different purposes such as budgeting, estimating, scheduling, project controls and monitoring etc. There are several other systems as I mentioned earlier and data is being used for one purpose or the other.

  • Can building data be crunched into a form that can be analysed by non-experts? Or will architects and other design and construction professionals need to adapt to working with, even alongside, data scientists and analytical experts?
The answer to this question is not a straight forward one. This can be said that technology exists that can make gaining the wisdom out of building data a no brainer but that would also require a certain level of understanding from the non-experts side. Meaning, non-experts will have to become techsavvy and need a primary education in the tools that will be used for extracting that wisdom out of data.

  • Is there a precedent for this situation, perhaps in another industry, that architects can learn from would do well to model and emulate?
Manufacturing industry shows the roadmap. Cars and space craft design processes might help.