“Big Data.” The concept seems to be on the minds and lips of those even remotely interested in business trends in the 21st century. And yet, as alluded to by Matthew Quint, director of Columbia University’s Center on Global Brand Leadership, the reality of Big Data is often misunderstood. During his presentation, the fourth in the five-part Transforming Architectural Practice Series, Quint presented case studies of data usage by corporations, debunked myths about data, and outlined a compelling case for the value of data collection and analysis in architectural practice.
Quint pointed out that data is all around us. It is collected by every mobile phone, appliance, and surveillance camera in the world. The Internet alone generates incalculable reams of it. In and of itself, however, this information has no practical use. It is only noteworthy once it has been parsed, organized, cross-referenced, cleaned, and securely stored. Quint suggested it is only then that data becomes Big Data that can be used to generate a better product or service.
To illustrate the relevance of this type of information, Quint quoted from an article in the Harvard Business Review by Erik Brynjolfsson and Andrew McAfee: “The evidence is clear: data-driven decisions tend to be better decisions. In sector after sector, companies that embrace this fact will pull away from their rivals.” And yet, a recent study by David Rogers and Don Sexton suggests that, in spite of understanding the necessity for data analysis, many companies simply are not doing this crucial work. The reasons for failing to collect and analyze data are myriad, but some examples include not having enough data to begin with or simply not being able to tie information to specific customer preferences and habits.
Quint also addressed another potential motivation for reticence to collect data: once acquired, it can be deployed inappropriately or even stolen, resulting in public criticism and an attendant loss of consumer confidence. He mentioned several controversies that have embroiled Target. In February of 2012, an article published in The New York Times revealed that the company’s data analysis had accurately predicted customer behavior and life changes based on past purchasing trends. Consequently, direct-mail marketing materials sent to specific consumers sometimes infringed upon privacy. For instance, a father was shocked to learn of his teenage daughter’s pregnancy from Target mailers, addressed to her, that contained coupons for baby care merchandise. To make matters worse, during the 2013 holiday shopping season, Target was the subject of a massive and coordinated data theft which resulted in the loss of sensitive information from 40 million accounts.
Despite the ethical issues involved in data analysis, this practice can still be a powerful force for good. Quint was able to find a handful of excellent case studies of architects and engineers using readily-available information to generate better design solutions. For instance, Sasaki Associates was engaged by Brown University to assist in determining the location of a new engineering building. After studying student and faculty movements and collaborations, the planners came to the conclusion that constructing the facility within the traditional campus would better serve the university’s educational core mission, rather than positioning it off-campus on a site that was less culturally and intellectually interconnected.
Although the analysis of information is not a novel concept within the design fields, it has assumed greater prevalence, and greater authority, as computational power has grown. In the past, architects had to rely on painstaking head counts or space-usage studies, which took many months to process and came to limited conclusions due to small sample sizes. Today, however, a designer can run massive quantities of available data through algorithms that spit out results in hours. Clearly, there is great power in using these tools. However, architects must still make sure to use them responsibly, and to exercise good judgment when doing so. The influence of Big Data must not trump that of common sense or nuanced human logic.
Matt Shoor, AIA, NCARB, LEED AP BD+C, is an architect, writer, and educator currently employed by Macrae-Gibson Architects. He is a frequent contributor to e-Oculus, and can be reached at firstname.lastname@example.org.
Event: Transforming Architectural Practice Series: Measure of Be Measured – Marketing in the Digital Era
Location: Center for Architecture, 05.12.14
Speaker: Matthew Quint, Director, Center on Global Brand Leadership, Columbia Business School; and Melissa Marsh, Founder and CEO, Plastarc (moderator)
Organizers: AIANY Chapter Professional Practice Committee