The current soul-crushing admin that most highly skilled CRE professionals have to endure for at least 30% of their days. Is it a thing? How is our “now state” similar to pre-industrial revolution business? Is there hope of change?
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.
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.
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”