Currently Reading

The Big Data revolution: How data-driven design is transforming project planning

BIM and Information Technology

The Big Data revolution: How data-driven design is transforming project planning

There are literally hundreds of applications for deep analytics in planning and design projects. We profile some early successful applications.  

By David Barista, Editor-in-Chief | December 28, 2014
Sasaki Associates used detailed network visualizations like this traffic flow pa
Sasaki Associates used detailed network visualizations like this traffic flow pattern of the College Hill neighborhood in Provid

This article is part of BD+C's special five-part Technology Report 2014: Top tech tools and trends for AEC professionals.


Gregory Janks feels a bit like an impostor at his firm. A self-proclaimed “numbers geek” with a PhD in mathematics and degrees in science and economic science, Janks relies on a much different process for developing and vetting planning and design strategies than the tried-and-true approaches utilized by many of his peers at Sasaki Associates (www.sasaki.com).

His rigorous, data-driven methods have opened the eyes of many at the design table, and have helped the firm’s clients—primarily higher education and healthcare institutions—tackle some excruciatingly difficult capital planning questions, most notably: What should we build next? And where?

“There’s a facilities arms race happening in higher education and other sectors, where the feeling is, ‘More is better,’” says Janks, Principal and Director of Sasaki Strategies, a group formed in 2005 to bring a strong analytical function to the firm’s planning and design work. “What we’re trying to promote is more isn’t necessarily better; better is better. We’re using a more objective, somewhat scientific approach to help our clients indentify the projects that will add the most value. Instead of asking, ‘What do you think you need?,’ we’re able to help them prioritize their needs.”

Data analytics, for example, helped the Sasaki team make a strong case to Brown University leaders that the school’s plan to move its engineering department off campus to an innovation district nearby would be detrimental, both financially and strategically, to the Ivy League institution.

4 ways Building Teams benefit from data-driven design

1. Enhance iterative design. Designers are able to capture and analyze key building performance metrics, such as energy use intensity, during conceptual design. That information can then be used to tweak and optimize early prototypes. 

2. Use project data on future work. By collecting data on every project, design firms can eliminate rework and apply best practices on future projects.  

3. Understand how people interect with spaces. Firms can test and evaluate design concepts against the real world, using feedback data from building occupants.   

4. Automate the planning process. Some firms are applying algorithm-based approaches to improve the traditional project planning process. 

The firm came to this conclusion after analyzing numerous datasets—from course enrollment numbers to faculty collaboration patterns to university financial data—and then creating a series of network visualizations to help “tell the story” to school officials, says Janks. Data collection methods included custom mobile surveys to faculty and real-time, crowdsourced feedback on how students and faculty use the campus via Sasaki’s Web-based interactive mapping program, MyCampus.     

“The results were dramatic,” he says. “For example, it showed that there’s a wonderful intermixing of how students behave in course enrollment, including engineering. It’s inseparable. You can’t pull this core network out without greatly affecting the students, faculty collaboration, and ultimately research dollars. The data helped us convince them to go in another direction.”


Make way for the rise of data-driven design

Janks may be in the minority at his firm, but he’s among a growing number of data analysis and software programming experts to make their way into the AEC field in recent years. A number of BIM and technology consultancies have popped up, as well, to meet the growing demand for data expertise.

Firms like CASE Design Inc. (http://case-inc.com) and Terabuild (www.terabuild.com) are making their living at the intersection where data meets design. Others, like San Bruno, Calif.-based Aditazz (www.aditazz.com), were built from the ground up as data-centric design and planning firms. It’s Silicon Valley meets the AEC field.

“Using data in the AEC industry is not new. The built environment has long been an abundant source of data,” says Randy Deutsch, AIA, LEED AP, Associate Professor in the School of Architecture at the University of Illinois at Urbana-Champaign. “What is new is the amount of data that is available to us, our capacity to measure and ability to capture, process, and act on that data, and, frankly, our industry’s urgent need to do so.”


Arup used a variety of data collection methods, including mobile surveys, security camera footage, and traffic flow reports, to better unify two neighborhoods in Pittsburgh: North Side and Oakland. The resulting scheme incorporates improved wayfinding, public artwork, open spaces, and interactive components like real-time public transportation and weather information and pay-by-phone bike sharing.


Deutsch, who is currently writing a book on Big Data applications for the AEC field, says the data boom represents an opportunity to completely transform how firms design, construct, and operate buildings. But getting there means they must overcome some significant barriers, namely interoperability, reliability of the data, privacy, and security. There’s also the trust factor. Data-driven design, for instance, may require the client to open its books or allow greater access to its employees or end users for feedback. 

“The use of Big Data in decision making in design involves securing a commitment within teams and the organization, reinventing internal and external processes, and modifying organizational behavior,” says Deutsch. “The AEC industry is among the last to address these challenges. We need to catch up, and quickly.”


Lessons from early data-driven application 

There are literally hundreds of applications for deep analytics in planning and design projects, not to mention the many benefits for construction teams, building owners, and facility managers. For the purposes of this report, we’re focusing on data-driven design and planning applications only. Here are some early successful applications, according to the experts interviewed for this report: 

Enhance iterative design. By condensing the feedback loop on conceptual design schemes from days (or even weeks) to just hours, design teams can tweak and optimize early prototypes based on the simulated performance and characteristics of the design. Software providers like Sefaira and Autodesk offer off-the-self solutions for on-the-fly energy modeling (see page 34), but some firms are taking the iterative design process to new levels with customized solutions. 


Sasaki Associates is among a number of design firms to develop custom survey and interactive mapping tools to better understand how building occupants and end users interact with the built environment. Using the firm’s MyCampus and MyBuilding (pictured) mapping tools, Sasaki designers are able to collect real-time information on everything from where people hang out on campus to what they like most and least about a building.


The Chicago office of RTKL recently commissioned CASE Design to develop a software program that captures dozens of key project metrics—including total building area, floor area ratio, area based on project program requirements, percent of green space on the site, percent of green roof area, and façade area—straight from the 3D conceptual design programs RTKL’s designers regularly use (SketchUp and Rhino). The program will even run a solar analysis of early conceptual designs, providing feedback on shading requirements and daylighting performance. The early stage design data is fed automatically into an Excel document and shared with the client and design team in real time using charts and dashboards. 

“Instead of using building information as a capture of the final design, it’s fed back into the early design process to help the team make decisions that will ideally lead to a better building downstream,” says Nathan Miller, Associate Partner and Director of Architecture and Engineering Solutions with CASE. “The program automates what typically is a manual process—capturing building information from conceptual models—which allows the team to adjust and tweak the design on the fly.”

Capture project data for future use. The data feedback loop extends beyond the project, as well. Firms like Skidmore, Owings & Merrill are creating databases of past project information and geometries for use on future work. If a particular design component worked well on a project, the firm will be able to share that information for use on other designs. This approach also minimizes rework, allowing designers to focus their time on solving new challenges. 

Understand how people interact with spaces. Design teams are tapping into a host of data sources—from Twitter feeds to mobile surveys to security camera footage—to observe how people use and move through spaces. Often, they discover that design intent does not match reality. 

“In theory, using the formulas and benchmarks that most standard building programming exercises depend on, you’ll be able to predict exactly what people need,” says Sasaki’s Janks. “But when we test designs against the real world, we find that often there is zero relationship between the two.” 


Silicon Valley startup Aditazz used a largely algorithm-based process to develop its winning design scheme for Kaiser Permanente’s Small Hospital, Big Idea competition (the firm tied for first place). By supplementing tried-and-true design and planning methods with computer-driven processes, the firm was able to quickly develop and test thousands of design schemes to find the best solution. 


Janks offers a dramatic example: During the initial planning stages for a renovation project at Harvard University’s John F. Kennedy School of Government, the Sasaki team used its MyCampus interactive mapping program to poll the students, faculty, and staff on what they liked and didn’t like about the campus. They also tracked their movement throughout the spaces. Among the findings: hardly anyone entered the building through the front door. 

How Big Data will improve urban planning

Last November, Arup and the Royal Institute of British Architects released a joint report, Designing with Data: Shaping our Future Cities, which explores the many potential uses and benefits of Big Data analytics in an urban environment. The report highlights four key applications: 

1. Designing for people. By collecting real-time data (via social media, mobile surveys, video cameras, sensors, etc.) on how people use public spaces and infrastructure, design teams and cities will have a better understanding of user needs and can create spaces that better meet those needs. 

2. Experimentation. Data and modeling tools could allow designers and planners to save time and potentially money by testing designs before they enter the construction process. This could also help identify likely objections and model solutions, saving time in the planning process.

3. Improve policy implementation. Cities have the potential to use the vast amounts of data they hold to improve the planning and delivery of services to citizens, by using the data to identify and address urban problems.

4. Transparency. By making more data publicly available, cities and governments can make it easier for designers and planners to get critical information on development sites faster.

“The map showed this torrent of people coming in through the back door, and absolutely nobody going through the front door,” says Janks. “It’s the kind of thing that previously we’d argue back and forth with the client about. But when we showed them the map, the entire conversation changed instantly. As a result, the campus plan was completely reorganized to what was the back side of the building.”

Automate the planning process. Could a computer one day replace a human planning team? Not likely. But it could take on a large portion of the traditional design planning tasks on projects, according to Deepak Aatresh, Founder of Silicon Valley planning and design startup Aditazz. 

An entrepreneur with a background in silicon chip design and manufacturing, Aatresh is bringing his analytical approach for designing, testing, and building microchips to the healthcare design world. The firm, which launched in 2009, applies a series of algorithm-based processes, virtual simulations, and other digital planning tools to design healthcare facilities based on the hundreds of programmatic and operations inputs from the client, as well as outside factors such as building code requirements and green standards. 

The goal is to develop the optimal design solution as quickly as possible by relying on computers to do what humans can’t: perform millions of complex calculations in fractions of a second. For instance, by applying automatic space-planning tools on projects, Aditazz designers can test thousands of iterations of building configurations and layouts in seconds. 

The firm’s process kicks out thousands of design options based on client input, and then quickly narrows the list down to a few ideal solutions. Aatresh argues that as much as 80% of the typical decision making that goes into creating a healthcare facility—from building orientation and space layout to patient wait times and traffic flow—can be handled through computation. 

Aditazz surprised many in the architectural community in March 2012, when its largely algorithm-driven design scheme tied for first place in Kaiser Permanente’s Small Hospital, Big Idea competition, beating out more than 100 entrants. The firm has gone on to win numerous commissions for healthcare work, most recently a cancer hospital project at Shantou University Medical College in Guangdong, China.


The data-driven future

Our report highlights just a few potential applications for data-driven design. Many more uses will be discovered, our experts argue, when the industry reaches a tipping point where the majority of project stakeholders—from AEC firms to building owners to government agencies—get serious about analytics for the design and planning of building projects.

Related Stories

Affordable Housing | May 30, 2024

General contractor’s keys to a successful affordable housing project

General contractors can have tremendous influence over a project’s success in terms of schedule, budget, and quality. However, to ensure a project is put on this path, there are a few factors that must be considered.

AEC Tech | Apr 30, 2024

Lack of organizational readiness is biggest hurdle to artificial intelligence adoption

Managers of companies in the industrial sector, including construction, have bought the hype of artificial intelligence (AI) as a transformative technology, but their organizations are not ready to realize its promise, according to research from IFS, a global cloud enterprise software company. An IFS survey of 1,700 senior decision-makers found that 84% of executives anticipate massive organizational benefits from AI. 

AEC Innovators | Apr 26, 2024

National Institute of Building Sciences announces Building Innovation 2024 schedule

The National Institute of Building Sciences is hosting its annual Building Innovation conference, May 22-24 at the Capital Hilton in Washington, D.C. BI2024 brings together everyone who impacts the built environment: government agencies, contractors, the private sector, architects, scientists, and more. 

BIM and Information Technology | Mar 11, 2024

BIM at LOD400: Why Level of Development 400 matters for design and virtual construction

As construction projects grow more complex, producing a building information model at Level of Development 400 (LOD400) can accelerate schedules, increase savings, and reduce risk, writes Stephen E. Blumenbaum, PE, SE, Walter P Moore's Director of Construction Engineering.

AEC Tech | Mar 9, 2024

9 steps for implementing digital transformation in your AEC business

Regardless of a businesses size and type, digital solutions like workflow automation software, AI-based analytics, and integrations can significantly enhance efficiency, productivity, and competitiveness.

AEC Tech | Feb 28, 2024

How to harness LIDAR and BIM technology for precise building data, equipment needs

By following the Scan to Point Cloud + Point Cloud to BIM process, organizations can leverage the power of LIDAR and BIM technology at the same time. This optimizes the documentation of existing building conditions, functions, and equipment needs as a current condition and as a starting point for future physical plant expansion projects. 

AEC Innovators | Feb 28, 2024

How Suffolk Construction identifies ConTech and PropTech startups for investment, adoption 

Contractor giant Suffolk Construction has invested in 27 ConTech and PropTech companies since 2019 through its Suffolk Technologies venture capital firm. Parker Mundt, Suffolk Technologies’ Vice President–Platforms, recently spoke with Building Design+Construction about his company’s investment strategy. 

AEC Tech | Jan 24, 2024

4 ways AEC firms can benefit from digital transformation

While going digital might seem like a playground solely for industry giants, the truth is that any company can benefit from the power of technology.

AEC Tech | Jan 8, 2024

What's driving the surge of digital transformation in AEC today?

For centuries, the AEC industry has clung to traditional methods and legacy processes—seated patterns that have bred resistance to change. This has made the adoption of new technologies a slow and hesitant process.

Digital Twin | Jul 31, 2023

Creating the foundation for a Digital Twin

Aligning the BIM model with the owner’s asset management system is the crucial first step in creating a Digital Twin. By following these guidelines, organizations can harness the power of Digital Twins to optimize facility management, maintenance planning, and decision-making throughout the building’s lifecycle.


More In Category

AEC Tech

Lack of organizational readiness is biggest hurdle to artificial intelligence adoption

Managers of companies in the industrial sector, including construction, have bought the hype of artificial intelligence (AI) as a transformative technology, but their organizations are not ready to realize its promise, according to research from IFS, a global cloud enterprise software company. An IFS survey of 1,700 senior decision-makers found that 84% of executives anticipate massive organizational benefits from AI. 


Most Popular Content

  1. 2021 Giants 400 Report
  2. Top 150 Architecture Firms for 2019
  3. 13 projects that represent the future of affordable housing
  4. Sagrada Familia completion date pushed back due to coronavirus
  5. Top 160 Architecture Firms 2021