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on Draper in marketing, Gordon Gekko in finance. Forgetting their moral failings, it’s hard not to romanticize these characters for their business acumen. With pure talent and ambition, they made gutsy decisions that elevated their companies into the stratosphere.
But there’s a reason that Mad Men took place in the 1960’s and Wall Street took place in the 1980’s. These days, computer scientists writing algorithms would run circles around both characters. With the help of big data and machine learning, it wouldn’t even be fair.
And that’s exactly what has happened in marketing, finance, and many other major industries. Instead of being driven by the instincts of a few executives, these industries now operate based off enormous data sets and ruthless efficiency.
Surprisingly, the largest asset class in the world, still manage their buildings with more art than science. Largely dependent on manual processes and personal relationships, building operations have only recently become more exacting.
This is not necessarily coming easy; most owners and operators would still prefer to stick with a vendor or partner they know than to follow the cold, hard data. But will this change? If so, how soon?
There are several factors pressuring real estate to adapt as other industries have. For one, market forces are demanding greater efficiency in how CRE portfolios are managed and operated.
Over the past few years, billions of dollars have flowed into real estate properties, driving up prices for desired assets. Meanwhile, in nearly all of the 12 most expensive real estate markets, median asking rents have fallen from their peaks, all while interest rates have increased for the first time in a decade.
But market pressures are not new. What’s new is the fact that technology has changed the playing field. With the smart application of technology, new entrants can close the gap quickly or incumbents can invest their resources to solidify their position and accelerate growth.
In an environment with few players, it’s natural (and effective) to lean on personal interactions and cues from peers to form judgements and make decisions. However, in a world with an increasingly complex web of employees, vendors, and partners, depending on personal familiarity can be very bad for business.
This is true across the value chain of real estate, but especially relevant for property management and the vendors necessary to operate buildings effectively.
For example, when a boiler breaks down, most landlords have “their guy” who they will call to service the equipment. Their guy will come in, fix the boiler, and tenants will have hot water again. Everyone is happy, right?
Sure, unless the goal is to reduce costs and maximize operating income. Sometimes boilers do malfunction to a point where a specialist vendor should be called to service the equipment. However, in many cases, there is a minor issue that remains undetected for long enough to cause a complete failure somewhere down the road.
In this case, technology can replace the reliance on this relationship by uncovering small issues and notifying salaried staff to make adjustments.
In addition to ad hoc service calls, there are a host of vendors that landlords contract to provide ongoing services for a property.
An example of this is tenant submetering, where a company is contracted to record the utility consumption of tenants so the landlord can invoice each space individually for their portion of the building’s usage. Some vendors employ meter readers who physically go into each tenant space once a month to write down numbers from the meter. Others have a digital infrastructure that was developed in the 90’s and never updated.
The ecosystem that low-tech vendors grew up in is reminiscent of animals evolving in a habitat with no natural predators. These companies have no need to innovate and their business relies on strong relationships with owners and engineers, who sign contracts without a second thought.
This lack of innovation can prove increasingly costly as competitors adopt newer, more effective solutions. No matter how strong that relationship is, or how long it’s lasted, a poor service provider is wasting money that competitors are capturing and reinvesting.
The effects of shifting decision making from relationships to objective return on investment are profound and hard to understate.
This change can apply to vendors, employees, business partners, and even tenants, and will certainly not be easy. In addition to the human element of cutting off solid relationships, changing course when the industry has been on a historic streak of growth takes a lot of courage.
Still, it may be necessary, because no one wants to be here:
While some CRE companies are embracing the changes coming to the industry, others continue to believe that real estate has inherent differences from other major industries that lends itself to trust and relationships over data and efficiency.
Some are not even considering the subject because they know they don’t have the decision-making toolkit to adopt technology in a smart way.
A major reason that CRE has lagged decades behind other industries is that data is significantly more difficult to attain from physical objects (buildings) than from financial transactions or consumer behavior.
This fact seems to have played out even in the recent proliferation of real estate technology. The first solutions to be adopted in a significant way have dealt with abstract data, mostly around the buying, selling and leasing of properties.
But thanks to the lowering costs and improved precision of the Internet of Things (IoT) technology, data about the actual buildings has become abundant and ubiquitous for the first time ever.
And there goes the last inherent differences between real estate and the other major asset classes that have transitioned from best-guess decision making to data-driven decision making.
Moving forward with the assumption that ruthless efficiency, enabled by technology will blow up the relationship model of doing business in commercial real estate, the next question is: how?
One clear mistake is to “let the IT guys handle it”. Generally, members of that department lack the domain expertise to properly evaluate a product that the business team can use.
In time, most real estate firms will have technology professionals that combine both domain expertise and digital literacy. But as it stands, virtually all real estate firms have siloed software expertise and business knowledge, which makes evaluation and adoption difficult.
In the short term, companies are working backwards, starting with problems a technology intends to solve, and how easily it can be integrated into current business operations.
For example, a building monitoring system should not require building operators to pour over data to decide how to be more effective, it should provide actionable insights in real time, so they can integrate data into the decisions they makes every day on the job.
The difficulty is that, as real estate plays catch-up, it is simultaneously forging a new path.
The Internet of Things, combined with developments pioneered by more technologically mature industries, such as cloud computing and machine learning, is enabling real estate to leapfrog the traditional adoption curve similar to developing nations skipping landlines in favor of cell phones.
The solutions being evaluated to bring ruthless efficiency to portfolio management are not only cutting edge for real estate, they are at the forefront of emerging technology in general. Internet of Things, virtual/augmented reality, and artificial intelligence are gaining traction throughout the industry.
There will always be a need for a human touch in real estate management, but it will need to focus more on managing exceptions, tolerating ambiguity, using judgment, and asking the right questions. The need to have “your guy” is becoming less important.
In short, data and technology in building operations are no longer a nice to have, they’re a must have, and the relationship model of doing business may be on its way out.
Enertiv deploys technology to enable real estate owners and operators to use data in their decision making around operations. Start a conversation today to see how we can help your portfolio!