Video transcript:
“The way we’re collecting data, in particular on the asset level, right. If you’re a shopping mall owner, the Optical Recognition Software now can recognise the number of people coming in, so regular shoppers you know their habits.
“If you’re in the logistics business, likely you’ll be able to optimize and actually even teach your occupiers how to better optimize the space, how to supply robotics into moving the goods around. So a lot of it you can actually optimize and move up the curve to not just be a real estate supplier of space but be a service provider in supplying technology as part of the offering.”
“But in terms of investment management businesses, I think it’s a little bit too early. [An] investment management business a lot of the time relies on gut. And gut instinct comes from a collection of a lot of different data points that may seem irrelevant sometimes.
“But if you’re trying to figure out which neighborhood is trying to gentrify quicker than the other neighborhood then you’ve got to figure out where the artists are moving to, where’s the chef moving the restaurants to, or [a] star chef because he’s going there for low rent.
“If you think that’s a low-rent district but he’s moving there, [then] there’s a good likelihood he will attract the mainstream users.”
“So stuff like that is still hard to capture on data. It’s still very much [that] you just have to have a sensory feeling out there and then collect…overlay it with empirical data and then come to a thesis.
“So I do think machines are not quite there yet, in terms of giving us those theses. But, the more data we collect obviously the more educated we’ll be and the quicker we’ll come to our conclusion – the thesis – quicker.”
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