Moneyballing Corporate Real Estate

In Michael Lewis’ book “Moneyball”, which was made into a motion picture, he recounts the transformation of the Oakland A’s, a low budget major league baseball team using advanced analytics, rather than traditional “gut instincts” of baseball men, in evaluating players and building rosters. Theo Epstein became one of the most successful practitioners of this approach turning around the Boston Red Sox and Chicago Cubs, two of the most historically unsuccessful franchises in baseball.

I recently began to read Lewis’ latest book, “The Undoing Project” where the opening chapters describe the Moneyball phenomena that has expanded across industries of medicine, finance, education and even farming. “Moneyballing” is the concept of using analytical data to find market inefficiencies and to challenge traditional approaches guided by human instinct. It was a moment of enlightenment that gave a name to what we have been working on over the last eight years.

The long debated and recently enacted changes to the standards for accounting for leases have been minimized by many real estate and accounting experts as “simply an accounting change.” Generally, this statement is used in the context of, “we are not going to change our practices just due to an accounting change.” The data modeling and analytics we have built suggest something radically different.

Since the early FASB work groups were formed, our team has been focused on companies with large property portfolios. We have built a business helping companies locate, validate and build information systems around their property information and inventory of leases. Having accumulated information on over 75,000 properties worldwide, we began to develop models that analyzed the P&L and Balance Sheet impacts of the new rules under traditional and alternative decisions. The results were enlightening.

We were able to put metrics to the true cost of the Flexibility Premium across a large portfolio. That is the premium a company pays by continuing to execute short term lease renewals for all properties, even though their length of stay at the majority of properties exceeds 20 years. In a number of cases, companies continue to rent the same space for 30, 40 and even 50 years at ever escalating rents, all in the belief that they need the flexibility to vacate. But, they don’t leave.

In other models we were able to compare lease vs. ownership under the old and new rules and illustrate the premium being paid to developers who were immediately flipping new build to suit projects into the ultra-hot investment market for net leased corporate properties. We are beginning to work with cognitive technology like IBM’s Watson to expand the potential data factors and provide constantly evolving decision support analytics.

The question at hand in the Moneyball analogy is whether a company will invest in and trust the data and analytics, or rely on the experience and deal making instincts of a handful of executives and advisors. In the traditionally “back of the napkin” business of commercial real estate, will they begin to trust the data? In Lewis’ previous book “Flash Boys” he describes the tremendous resistance to change and accept disruptive technology on Wall Street in spite of overwhelming evidence to the contrary. There will always be those more comfortable with the status quo. While none of these books specifically discuss corporate real estate, the lessons are quite applicable, and worth understanding.