Hyper Local

A report released by McKinsey this week, describes how big data is transforming real estate. In particular, it points to how large data sets allow for increasingly granular and ‘hyper-local’ analysis of investment decisions. The report notes that traditional metrics (e.g. vacancy rate) only partly explain the potential for future growth. The combination of these metrics with non-traditional variables (e.g. number of cafes within a mile, or proximity to highly-rated points of interest) enables much greater accuracy when predicting market changes. For example, proximity to highly-rated restaurants (on Yelp) and changes in nearby apparel stores, ‘explained 60% of the changes in rent in an area’. Similarly, when the same tools were applied to multifamily buildings in Seattle, ‘the models predicted rents with an accuracy rate that exceeded 90%’. Whilst the technology is available today to be able to obtain such insights, the challenge remains one of data integrity, platform and skills. The report concludes with a need to start building diversely-skilled teams now, in order to capitalise on the increasingly rich data sets in the future.