Framing Data in PropTech and AssetTech

In PropTech & AssetTech, the data and property valuations are enormous, even though companies in real estate tech are just getting their sea-legs.

Certain numbers are staggering.  When we think of the unicorns that have emerged over the last year, we must pause to consider what “a billion dollar” valuation means for a founding team or early employees.  For most, such scale appears out of reach.  In fact, many industries are in their entirety smaller than the market cap of these new, disruptive players- many of which are in Fintech.

For some areas of the economy though, even billions appear to be child’s play.  Take residential real estate, the focus of one of the authors here.  World-wide, the value of this asset class approaches $200 trillion.  Or take Asset Management, the passion of the second author—by 2025, $120 trillion dollars will be managed by Asset Managers on behalf of clients or their own accounts.  These numbers dwarf even those numbers that impress most of us!

With so much on the line, it is natural that entrepreneurs and technologists have taken great interest in Fintech in general and in a variety of sub-areas thereof.  In the PropTech/Real Estate tech space, we see a huge amount of deal flow, though many of the innovative companies in the space are just getting their sea-legs.  The potential here is exciting, helped along by enormous industry and regulatory tailwinds.

With regard to AssetTech, the story is a bit different.  Despite the enormous size of the industry and the growing complexity, the industry continues to rely on outdated tools at worst or a pastiche of disconnected systems at best.  Players who take a platform approach to helping Asset and Portfolio Managers manage, optimize, and create high returns while maintaining fidelity to regulations and security, will emerge as winners.

Undergirding success in both of these areas is the usual suspect:  Data.  Indeed, how an organization frames data is likely going to be the single most important factor in relative success or failure. Can the right data be easily accessed, ingested, understood, and acted upon with agility?  Can new sources of data- even ones unknown at any given time- be assimilated quickly?  Can the data deluge be seen as an asset not as a water-logging impediment?

Data is now the universal language of business but, and both authors remain shocked by this, so many organizations appear unwilling to make the requisite investments- in technology, process, people, and culture—to take advantage of this beautiful and dynamic Esperanto.