Commercial real estate data – the specifics

We move away from vague generalities, and go into specific points on why CRE data is complex. We also unpack: Where is CRE data, what does the road ahead look like? What are CRE businesses doing about it, and how does it play out? How is the CRE industry coping (or not) now?
Data is the oil that CRE runs on

Commercial real estate data – a quick overview…

  • A specific example why CRE data is complex?
  • What does the data maturity cycle look like, and where are we all now?
  • What strategies are businesses adopting?
  • How do these strategies play out?
  • What does the future look like?
  • Also – the current dark side of CRE data – “admin”

Getting specific and relevant: data in CRE

“Data is the oil that CRE runs on”

…is a cute saying. Want one fact to make this feel real? Here goes:

A property’s unit is made up 1.6K possible data fields. To show just one unit in Excel, you would need a spreadsheet from column A to column BIN (that’s A-Z 61.5 times). If that one unit were printed out*, it would need 124 pieces of A4 paper running 3.7 meters wide.

What makes up these 1.6K data fields? Here are four examples: rentable area or GLA, asking gross rental, suburb, property name. There are 1,600 more of these. A property unit has information ranging from height to eaves, to unit sub-divisibility, to location co-ordinates.

And people, we’re only talking fields of one type of data – a property unit.

In addition

Commercial real estate data is complex because it doesn’t touch only property / locations. CRE is underpinned by two of the other four public domain enterprise data assets: 1) businesses and 2) contacts. That’s 3 out of the 4 data types possible. Fortunately CRE ignores vehicles!

Plus, CRE spawns data entities that result from the intersections of these data assets. For example: leases are the intersection of a property with a business. While lease deals are the intersection of a business with various properties’ units.

CRE also deals with other data, like documents and images.

For the sake of sanity, let’s ignore, for now, the complicated hierarchical (parent-child) property data structures. (One property can contain many buildings, each with many units). Let’s also put our head in the sand re IOT data, or financial data from third parties. It’s probably also convenient to forget that data, now, is largely unstandardised. Universal data definitions despite the efforts of many, are still in their infancy.

This article is also partly a tip of the hat to all under-unappreciated CRE professionals out there. To serve their organisations and industry outsiders alike, all competent CRE professionals are data specialists. And all use, at minimum, a common, largely reliable, sophisticated technology to handle this incredible complexity. The human brain!

* Printed: Excel’s default (narrow) 64 pixel width, on A4 paper landscape layout, without any changes to margin settings.

The future

Like other industries, commercial real estate data is only going to grow – in velocity, volume and variety. And as various verticals in CRE mature (property funds, debt funders, insurers being three), adjacent verticals are going to be forced to “level up”.

We predict this pressure on CRE will be around a) processing, and b) using data more effectively. And, in a data-driven world, the businesses who succeed here will see greater profitability, and higher levels of operating efficiency.

Where are we now in the commercial real estate data maturity cycle?

Adoption of data-driven best practices is being forced on CRE by industry customers, and insiders alike.

Exciting, tangible progress in other industries around us is awakening people to best practices around data, and their benefits of this. Think about Google Maps, online shopping websites, cool data visualisation tools.

People are starting to think and say:

“Why can’t you be like my tech-driven experience in industry X?”

“They do it, why can’t you / we?”

This data maturity journey happens on a spectrum from unconscious incompetence to unconscious competence. (This conscious competence is arriving in the form of tech solutions that automate data)

So, easy on the far left, and easy on the far right. Painful in the middle part.

The far-left hand side ignorance is bliss / the comfort and safety of laagering up.

It feels like many in the industry are leaving the false comfort of the left, and are now in a painful no man’s land. It’s an in-between phase. This “consciously incompetent” world is painful. It’s stress-inducing – and time-consuming, and expensive. Further, it’s full of doubt – will we ever reach the promised land? Why did we ever leave the safety of home base? Life was so much easier when…

We’re certainly experiencing, as our industry matures and people upskill, increasingly, conversations with experienced commercial real estate professionals are starting to sound and feel like business analysis session with data engineers. These CRE professionals, independently of any formal data training, are asking the questions, reaching for solutions.

We’re on the journey now. It’s going to take time. Things feel complex. Soon, however, they will feel simple.

How are people handling CRE’s growing data needs now?

Below is where businesses are on the strategy. And each strategy has its own pros and cons.

Strategy #1: “ignorance is bliss”

For this approach, the following phrases are a soothing balm:

“This data thing is a fad”. “The good old days will come back”

“It’s them not us. We must be more selective about the tenants and service providers we work with”

“I’m too old for this”

CRE data laggards

As the image above indicates, there is risk.

Call them Luddites, it must be argued that this “wait and see approach” may be very rational.

As a strategy, unintentionally or other, waiting for a “white knight” technology solution is effective:

  • Pro: Save money on building your own tools, apply time to business as usual (BAU), stay focused and avoid distraction.
  • Con: take the short term reputational, competitive disadvantage, and business disorder hits

Strategy #2: Faster horse Excel DIY

“Excel has served us before, it will keep on serving us”. There is a great saying:

“you can only push a golf ball so far down a hosepipe”

We love the phenomenal tool called Excel. Due to its flexibility, usability and power, you can get a “lot of runs on the board”, fast.

This is exciting, but the allure is treacherous. Because, at some point, the wins start coming slower and slower. Until they stop.

The golf ball can’t go any further.

The technology, through a combination of great initiative and Excel wizardry, will eventually be shoehorned into a corner. This mismatch starts to cost – this shoehorned solution requires more and more human time to Band-Aid and manually support. Skilled professionals inside of these businesses start descending down the the “busy-not-productive” slope. The frogs are slowly being boiled to inefficiency death.

Strategy #3: DIY, and pay outsiders to learn CRE

You have identified a problem. The solutions are apparent to you. You can’t find any off-the-shelf solutions, and you know you don’t have the skills.

So you shop for a business to build your solution.

The problem with complicated domains like CRE… Industry outsiders, while they may be skilled in their solution space, “don’t know what they don’t know” when it comes to CRE.

The quality of their solution designs are constrained by a deficiency of knowledge, and first or second order thinking. Your problem: such outsiders are going to be making mistakes, that others who know the domain, have already made.

You will be “paying for people to learn”. And you will probably end up playing teacher too. Welcome to death-by-detail!

Strategy #4: Bet on a jockey who is on the product development journey

If you can’t find the tools, you have to plan B. Plan B entails betting on a specialist to take on execution risk. Jockey selection here is tough. But financially is probably more expedient. Rather lean on a third party who is pot-committed, incentivised to get this right, and forced to sweat the small stuff.

Strategy #5: Find the right tools

If the tools are built, this is an easy one. You can sidestep all the complexity that comes with NIH syndrome.

How do the strategies play out?

The ignorance is bliss team will suffer in the short term. If they can keep their heads above water, when the white knights arrive with their tools, they should win.

The DIY Excel guys will do better. Something is better than nothing.

The DIY and pay outsiders are an unknown. Sad but likely outcome – lots of money and time spent. Progress is made, but it’s slow, very time-consuming and expensive. The word refactor gets thrown around a lot.

Those betting on jockeys, have jockey-dependent success. In the event of non-performance, at least both money and mental headroom is saved. In the best case, you get a product built close to your needs, and can start a relationship with a reliable tech partner.

What do solutions look like?

This can get very technical. So let’s avoid that. I will talk simply to what the humans, the CRE professionals will experience.

To CRE professionals, the Holy Grail is systems where:

  • Data governance happens “under the bonnet” (seamlessly, invisibly)
  • The analytics businesses need are easily available, and user-friendly (slice and dice, reporting is automated)
  • Data movement is automated – reducing data quality risk, improving speed, and freeing up very skilled human time
  • Commercial real estate data is centralized (no more data silos, one version of truth, all info in one place)
CRE data revolution

The current dark side of CRE data: “admin”

Because of the industry’s less mature data tools, highly CRE professionals, in the 21st century, operate like pre-industrial revolution factory workers.

Why so? That hated part of every CRE professional’s job: “admin”.

The workers of old used to exert large amounts of energy manually moving metal and cloth around factories. Processing it. Checking the finished products. Fixing it. Dealing with all the related moving parts.

Today, CRE professionals do the same thing. It’s busywork, with high risk of error, and it’s mind-numbing. But, instead of metal and cloth, it’s the same moving, processing, checking, fixing, supporting process – but with data.

The name for that data processing. The inefficient data busy work? “Admin”!

For more info on this critical topic, there is a link below:

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