If you’re familiar with the movie Moneyball (based on a nonfiction book of the same name), you know that in the film, the Oakland Athletics general manager and assistant manager take a unique approach to building their baseball team within the constraints of their limited budget. Instead of relying on the more subjective information often used by their competitors, like the way a certain player runs or wears their uniform, the two used a sophisticated analysis of multiple empirical data sets to track players’ in-game activity and statistics to guide their decisions.
At CRE.Converge 2018 in Washington, D.C., Brookfield’s Global Head of Corporate Development/Executive Vice President Kevin Danehy likened the Athletics’ evidence-based approach to the way building owners and operators could leverage big data.
“Collecting data is all about taking information and breaking it down so that it’s effective in helping us make business decisions,” said John Schwab, partner at Wipfli LLP, who moderated the panel. He introduced Donna Salvatore, CEO of Megalytics, Inc., and asked her about the data that is available now to help developers make business decisions.
Salvatore’s company has access to many forms of what she calls “non-traditional data,” including:
- Geofencing retail, office, multifamily and industrial sites – This allows the company to track activity in any area, such as a building, a parking garage or lot, an entire shopping mall, an urban shopping corridor or a sidewalk. Data is derived from 100 million mobile devices that have location apps and GPS tracking turned on. This sample size covers 40 percent of the U.S. cell phone population.
- Merchant credit card data – This enables the company to see who visited a site and made a credit card purchase.
- Social media search – Data can be collected in real time from all Google searches, Instagram and Facebook, and two types of information is generated: active intent (what people are looking for right now) and passive intent (likes, shares and comments on Facebook).
- Move data – Fifteen percent of the population moves every year. This data set includes information on when individuals moved in and out of their residences, their ages and genders, time at a residence, and includes every move going back 30 years.
- Traffic data – This data is culled from the navigation systems in 350 million vehicles, including cars and fleet trucks. It tracks traffic for 2.5 million miles or 1.8 million road segments in the U.S. The data is from June 2018 – specifically chosen because it reflects “typical” conditions, meaning it is not impacted by weather, accidents or other incidents.
- Pedestrian traffic – This is calculated based on the number of GPS devices seen on the area of the sidewalk and about 20 feet of building fronts over time. It uses the same sample size of 100 million mobile device users used in geofencing.
The breadth and depth of data available is staggering, and so can be the task of organizing and interpreting it. “We have a very fragmented technology structure,” Danehy said of his company, Brookfield. “Our data, though we have a lot of it, is captured in various Excel spreadsheets and accounting software.” While the company has access to veritable mountains of data, that data isn’t collected in a central place where it can easily be used to make decisions or create future projections. “I’m guessing we’re not alone there,” he said.
Danehy talked about how companies are just starting to effectively collect data, but are still barely able to use it. “We’re still in the first inning” of big data adoption, he said. But the company is taking steps to streamline and integrate their processes. Brookfield is in the midst of adopting a new accounting system for all of their North American offices.
Ideally, Brookfield will eventually be able to use their data and smart building integration to measure their tenants’ behavior and preferences to create the ultimate personalized experience. For example, an employee could put in a lunch order before they go downstairs to a café and pick it up without waiting in line, or put in a request for an umbrella on a rainy day. The visitor check-in process could be streamlined, and face recognition could eliminate the need for plastic security badges.
“This provides an opportunity for owners,” Danehy said. “We can establish a direct relationship with the employees of the companies who are tenants of our buildings. That has never been possible before.” He added: “Tenants used to be thought of as mainly a source of cash flow. Now they are customers. That comes from having a relationship with the people who are coming in and out of the asset every day.”
No conversation about big data would be complete without discussing the privacy implications. Salvatore said that so far that isn’t much regulation, because her company’s data is anonymous and aggregated.
“We’re just starting to scratch the surface” on figuring out what is appropriate and employees’ rights in regards to data collection, Danehy added. “We’re actively seeking guidance. We have to figure out – along with our peers – what is responsible as far as using people’s data.”
One thing’s for certain: The companies that find a way to leverage big data will set themselves apart in an increasingly competitive environment.
Brielle Scott is Senior Communications Manager at NAIOP.