Big data has revolutionised the way organisations work and do business across industries and around the world. And it has only been in the recent years that big data has gained traction in the real estate market.
At the recent full-house event, “Big Data, Big Real Estate Decisions”, ULI Singapore and Aon Risk Solutions co-hosted a panel discussion with business leaders from the property and investment sectors. Moderated by Chris Camerieri, chief operating officer of Aon Center for Innovation & Analytics (ACIA), the panel explored how players in the real estate industry can differentiate between the hype and reality of big data, and yet leverage data analytics for effective decision-making.
Wong Hwee Lim, head of group business solutions & systems of CapitaLand, termed big data the “new currency”, which enables real estate stakeholders to further understand the business so as to drive revenue forward. While the ability to get meaningful information out of big data has always been a challenge regardless of industry, technology has now evolved to allow even those with little technical experience to create data visualisations within a short timeframe.
However, this is not without issues. Individual teams in organisations often collect massive volumes of data. As they work within their own data sets, these teams miss out on a volley of valuable insights available within the wider organisation. To counter this, CapitaLand, for example, combined all data assets into a new, scaleable data platform two years ago.
Once streamlined into a single repository, organisations can harness the power of information from their global office network at their fingertips.
Tapping on the data contributed by global offices enhance cross communication and knowledge sharing for better decision-making. It also helps in developing new and creative uses for real estate that no one else has thought of. Such shared data will enable property owners to see the changing demand for real estate.
Alan Miyasaki, senior managing director & head of Asia acquisitions of the Blackstone Group said, “As real estate investors, you really need to focus on these drivers because they impact who your tenants will be and what they will do in the future.”
Building operators are also tapping on the value of videos for data analytics for the early detection of security events. Operationally, wiring up buildings enable them to pull sensors information around how their equipment are working. These data give operators early insights to any equipment anomalies for preventive maintenance. This not only improves the overall customer experience, but more importantly, optimum functionality saves organisations money in the long run.
Among the questions raised from the floor was on governance and standards. Drawing on an example, it was discussed that malls could work with banks to better understand the types of credit card transactions to serve their customers better. Although this is the ideal scenario, data privacy poses a challenge for such partnerships. While organisations collate their data assets, they are bound by different regulations. Each regulation has its own sets of constraints that prevent data sharing. Moving forward, it might be necessary for regulators to think about how regulations can be simplified for big data to work effectively.
In the session wrap-up, Ang Choon Beng, senior vice-president of GIC Real Estate shared what organisations now face with the advancements of technology.
He said, “Technology has advanced so much that the ROI for basic levels of analytics fluency is just not easy to meet… The (challenge) is to go beyond this basic level of analytics to try to drive the decision-making using the collected data. That will be the next area of focus for our firm.”
Of the potential that data can offer, Wong concluded, “We can start pivoting from the traditional services and products that we have, and move into new, adjacent product offerings that we may not even have today.”
Data analytics has advanced in such a form that organisations just may be able to better ascertain customers’ preferences even before they realise it.
Lee Wai Leng