Data Acquisition isn’t Enough, It’s Analysis That Matters

The rapid democratization of commercial real estate data has redefined what it takes to establish a competitive advantage in the industry.

In his provocatively-titled April 2014 Forbes op-ed, “Are Real Estate Brokers Obsolete?,” author Bruce Kasanoff posed a challenging, if straightforward, question to real estate stakeholders: “How [do you] make money when everyone has easy access to all information?”

Whether by foresight or fortuity, Kasanoff’s query has emerged as the commercial real estate industry’s million dollar question over the course of the last five years. While Kasanoff’s was a decidedly prospective question at the time, the past half-decade has seen a democratization of information so comprehensive that universal access to critical CRE data is no longer an eventuality, but a reality.

This has been a boon to many – especially smaller – CRE players insofar as it has placed them on a more level playing field with industry heavy-hitters. However, it has also dramatically reframed the way CRE firms large and small must approach market differentiation. Five years ago, using proprietary data to inform your CRE decision-making was often enough to elevate you above the competition. Today, such a data-informed approach is all but a given, and therefore no longer functions as a meaningful differentiator.

Simply put, data access in and of itself doesn’t amount to a competitive advantage in 2018. Consequently, today’s CRE professionals would be wise to heed Kasanoff’s answer to his own question: “Use common information as your starting point, rather than as the be-all, end-all.” First and foremost, this means paying closer attention to both the quality of your data and the sophistication of your data analyses.

Data Analytics: The New CRE Differentiator

Provided you have access to high-quality — that is, complete, consistent, valid, and timely — CRE data, your most pressing line of inquiry should be, “How do I use my data? How do I combine my various datasets? How do I integrate data into my workflows? How do I derive actionable insights from lifeless — and widely accessible — information?” The answer, in a word, is, “analytics.”

Scale has always been the limiting factor in CRE, as human brokers and investors can only process so much asset data at once, making it difficult to consistently produce penetrating analyses of the underlying factors at play in a particular market niche at a particular moment in time. The increasing availability of data analytics tools — especially those equipped with machine learning capabilities — removes this obstacle to effective data use by empowering brokers and investors to exploit the full range of data at their fingertips, not just the data they can manage manually or with a rudimentary tool like a spreadsheet.

Currently, analytics tools’ value-add includes more refined trendspotting (including dynamic “heat maps” of CRE activity across asset classes and geographies), easier and more accurate entity resolution, and near-instantaneous generation of sales comparables. While these are all tremendously valuable, they are, for the most part, simply scaled-up or accelerated versions of the analyses CRE professionals have always conducted.

The deeper value of data analytics rests in their predictive potential, which will be among the most powerful short- and medium-term differentiators in the industry. Of course, CRE professionals have always drawn up market forecasts and tried to beat their rivals to the punch on emerging opportunities, but there’s a direct relationship between the precision of a market prediction and the number of variables upon which it’s based.

As such, predictive analytics tools that have the “brain power” to generate forecasts using dozens if not hundreds of market variables are uniquely suited to guiding CRE professionals’ future-facing operations. A top-notch predictive algorithm can find trends in sprawling datasets that are so nuanced or complex as to be effectively imperceptible to even the most seasoned market analyst. In a CRE landscape in which access to data is universal, it’s these kinds of insights that differentiate market leaders from the pack.

Adapting to the New Normal

As someone whose entire business revolves around CRE data, I’ve been particularly attuned to data’s shifting role in industry differentiation over the years. In fact, I co-founded the CRE data aggregation platform Reonomy in March 2013 — just thirteen months before Kasanoff’s op-ed.

I’d like to think that tools like Reonomy played a part in the rapid democratization of CRE data, but that’s neither the important part of the story nor the end of it. The future is what matters most, and we’ve had to accept that, like “data access” more broadly, the platform we built in 2013 is now a necessary but by no means sufficient condition of an effective CRE operation. Brokers and investors need reliable data aggregation tools, but they also need the will — and analytics capabilities — to leverage their aggregated data in bold, enterprising ways.

By constantly evolving our own product, we’re doing our utmost to adapt to the shifting role data is playing in CRE professionals’ lives. That said, innovation begins with our users — with brokers, lenders, developers, and investors.

Ultimately, those who focus on funneling our data into cutting-edge analytics tools and applications will find themselves in pole position as the commercial real estate industry completes its digital metamorphosis. Because in 2018 and beyond, it’s not access to, but analysis of, data that really matters.

Rich Sarkis is the CEO of Reonomy. The views expressed here are the author’s own and not that of ALM’s Real Estate Media.