Space for Thought: Connecting the data points to the future of PropTech
While media attention around PropTech has historically focused on high growth, platform economic plays such as WeWork, a colossal opportunity lies within the walls, by the water cooler, and everywhere in between the residential, commercial, industrial spaces around us (and beyond). Specifically, real estate sits on a unique and largely untapped set of data that has historically remained underutilized, to the detriment of the industry. This was fully realized as the sector was both the hardest hit and slowest to react at the onset of the COVID-19 pandemic, in part because of the lack of information available across residential, commercial, and industrial spaces, and also in part because the category lacks software to extract this data in the first place. Because of this, the future of PropTech lies in solutions that position the sector to harness the highly-versatile data sets of this multi-trillion-dollar industry, to not only drive innovation, but protect the downside of this recession-prone corner of the economy.
To be clear, platform economic solutions such as WeWork should not be replaced, but rather augmented with technologies that can more effectively extract and analyze sets of data, exponentially increasing the value of the square footage from which they are derived. As if the sheer size of the real estate market was not large enough, with the value of professionally managed real estate hitting almost $10 trillion globally in 2019 or the $3 trillion in gross real estate assets managed by REITs, imagine the value of the industry if it took advantage of the proverbial low hanging fruit. Specifically, despite the scale of their assets owned, REITs are valued at relatively low valuation multiples with the average market cap to FFO (funds from operations) trading at ~15x and many smaller REITs trading as low as 5x FFO. In contrast, Amazon currently trades at almost 100x forward earnings, largely because the value of REIT FFO has always been contemplated as a function of rent paid — nothing more than a transaction. But what if real estate ownership became more than just a transaction in the wake of the pandemic? Think about the opportunity to immediately supercharge the value of a property by utilizing data to not only better inform decisions for the holder of the real estate, but also to inform any adjacent use of the property utilized by the likes of insurance providers, public market investors, and urban planning outfits? With REITs now beginning to tap into the wide variety of data generated by users, whether that be to better understand layout effectiveness or heat map commercial spaces, an increasingly data-focused tenant experience will continue to further drive occupancy demand, and ultimately pricing power and margin expansion for tech enabled real estate assets. More importantly, this continued sector convergence will likely be manifested in multiple expansion, especially as the category is forced to adapt even further to autonomous vehicles, the continued proliferation of e-commerce, and the shared economy. And this assessment doesn’t just stop at industrial, commercial, or residential assets — how can all spaces, such as say airplanes, harness the power of their own data to maximize their ROI on everything from faster cleaning times to how their employees can more productively, as they say, move about the cabin? Now the paradigm has shifted from defense to offense with multiples responding accordingly.
Most interestingly with PropTech, though, is the versatility of the data. While data across some verticals is only truly valuable once it hits critical scale, data within real estate can be quite useful sourced and utilized at the local level. For instance, how do our employees interact within our office space (Proxy)? Or how do customers interact with the products in our stores (b8ta)? At a more global scale, some of the most useful data aggregated on real estate can be collected externally, with satellite imagery providing important insights to inform decisions adjacent to the direct use of the real estate. Examples of this include how to best underwrite residential real estate insurance (Arturo), or in the wake of say a global pandemic, how can local commercial property owners best utilize their space (Locate.ai)? Thus, going forward, the value of asset managers should no longer be thought about in the context of assets under management or rent paid, but rather, how the information derived from these assets is utilized to continue to boost their value in flywheel fashion. Notably, commercial real estate giants have taken the first steps towards this transformation, with the likes of CBRE employing geographic information systems (“GIS”) technology to support its brokerage and portfolio management services by utilizing mapping software to improve market analysis.
In this context, the chart below maps out the disruptive ways technology is leveraging data extracted from the physical world to drive value across applications. Specifically, on one end of the x-axis are platforms utilizing data to inform decisions for direct real estate applications such ‘How can our properties be used most efficiently?’ On the other end of the axis, real estate adjacent applications such as ‘How can we better underwrite residential property insurance?’. The takeaway being the value of data derived from real estate doesn’t just stop at the boundaries of this sector but is quite useful in informing decisions across adjacent categories such as insurance or geospatial tools (say for use by a Doordash).
Despite the sizable opportunity data in real estate presents, as with any category, there are considerations. In some geographies, both software platforms and investors alike face GDPR restrictions on everything from methods of data extraction to the application of this data. Additionally, traditional real estate has been playing a difficult game of catch up to staff its ranks with data scientists who can properly analyze and execute on the value from this data (opportunity for verticalized MlaaS anyone?). Similarly, creating a go-to-market sales motion that can effectively identify champions and communicate ROI into a category lacking the technical data acumen of more forward-thinking enterprises will be critical for the near-term adoption of these solutions. That said, the future of the category rests in information, and with the global COVID-19 pandemic forcing 10 years of technological adoption in a slow-moving category in less than 6 months, it is only a matter of time before these hurdles are remediated. Thus, while there remains plenty of opportunity for platform economic plays, much of the future opportunity lies in the software solutions that extract data from buildings and space of all forms, and the resulting range of use cases of the data therein.
