Decoding the Language of Data to Inform Your Decision-Making
‘Data’ can mean many things to different people in the commercial real estate space.
From one perspective, data consists of statistics on leasing spreads, property valuations, tenant behavior, and marketing KPIs. It’s a powerful tool that enhances decision-making processes across a portfolio of businesses or real property.
But for many commercial real estate operators, data is a mountain of Excel spreadsheets that gather virtual dust in a forgotten computer folder. It is something that is collected but not used consistently in a structured way to drive growth.
In the past, having the ‘we’ll address it later’ attitude toward data did not prohibit an operator from achieving returns. However, today, the companies that leverage data-driven decision-making are achieving the most in commercial real estate.
In this article, we’ll explore how approaching data as a language enables commercial real estate operators to extract the full value from their data.
What is ‘data?’
Data can be any bit of information that you collect, digitally or traditionally.
In prior decades, operators fixated on market and property numbers, such as:
- Cap rates.
- Property values.
- Lease rates.
- Rent rolls.
- Schedule of expenses.
- Net operating income.
But data has since expanded to include many more soft variables, such as:
- Property showing volume.
- Foot traffic generated.
- Marketing metrics.
- Energy efficiency.
Curiously, a myth has persisted that getting the data is complicated. In a survey of real estate managers conducted by Deloitte, the majority spent more than 80% of their time gathering and manipulating data.
While gathering data was once considered a daunting task, it has become much easier due to the recent development of numerous ‘prop tech’ companies and data analytics firms that streamline the task.
Data speaks many languages
Would you assemble the United Nations without asking members what language they speak and employing a qualified interpreter?
No, because nothing would get done.
Yet, this happens when owners don’t take the time to assess what language their data speaks and develop solutions and teams to bridge the gap.
The challenge commercial real estate operators face when approaching data utilization is not knowing what language their data speaks or how to put it to work.
For instance, the data in your BIM (“Building Information Modeling”) system and the data in your asset management platform are held in different formats and are often siloed (isolated) in various software or databases.
How do we unravel and interpret the message — knowledge — hidden in our data?
We leverage centralized data management and analytics systems that pull all the data together and help us make sense of it.
But it’s not just tech — we also need a team of advisors that understand how the data fits together and what the reports are trying to tell us about our situation and the market.
Prevailing despite a moving target
Conceptualizing data as a language, you can bring in the synergy of tools, technology, and people to translate data into knowledge that will inform your strategic decisions.
Approaching data through this lens has become critical for commercial real estate as the industry heads into new territory. We’re confronted with a dynamic market that is redefining CRE asset classes.
The work-from-home trend, the demand for last-mile industrial, and the instability in retail require us to re-assess our strategies — a task for which we need the best intel we can get.
By translating data across your systems and putting it into actionable forms for management, you can more intelligently make critical decisions.
Discovering the missing element
Analysts remind commercial real estate operators all the time that data is essential.
Still, losses and inefficiencies confirm there’s a missing element between data gathered and data successfully harnessed to improve our investment and development strategies.
Implementing data management systems and partnering with the appropriate professionals enables you to take raw information and transform it into metrics that inform success.
Collecting data is crucial but not as vital as decoding the language your data speaks and what it’s trying to tell you.