Real estate decisions: Basic instinct or based on data?

Never have companies required more flexibility from their real estate or faced such complex decision making. The need to make decisions faster and more frequently calls for more reliable and meaningful metrics, available on demand and up to the minute.

In a short space of time, we’ve moved on from performance metrics based mainly on finances, such as occupancy cost or return on investment. Real estate professionals today are involved in productivity, technology and sustainability decision making with demand for accurate and relevant supporting data. What’s more, the pandemic has reshaped the way employees work and there’s greater experimentation around the hybrid office.

We’re seeing how operations are adapting and capturing human experience, real-time space utilisation, operation and capital cost and CO2 emissions data from real estate. For investors, financial metrics are supplemented with measuring everything from community impact and supply chain diversity to sustainable space. Meanwhile, rising demand for flexibility means the market is moving much faster. To operate sustainably, there is growing demand for predictive as well as reactive reporting analytics.

Making real estate decisions today therefore means tracking many more moving parts. Of course, companies are using data – but they typically aren’t connecting different data streams, which would help leaders see the bigger picture and make more integrated decisions - thus adding greater value.

Methodology matters

Many organisations already grapple with a sea of data, from building sensors, workplace apps and employee surveys, to information from operational, financial and supplier systems.

However, 59% say they either do not regularly capture real estate data, or that they do so only intermittently. Only 13% make use of real-time analytics for up-to-date business intelligence according to a recent JLL survey.

There is no correlation between the sophistication of a company’s main business and their analytical capability in real estate management. Even if a company has good data analysts, it may lack in-house skills in building real estate data hierarchy and capturing metrics that matter for business competitiveness.

And despite tracking more sophisticated metrics, businesses can lack consistency in the basics, which reduces the credibility of the metrics. For example, different tools may define ‘a person’ differently – is it a full-time employee, any worker, or any person who walks through the door? The same is true for space definitions in each building and in different functional systems. Without a consistent foundation, you can’t create reliable metrics and confidently connect different data sources.

Businesses need good data governance that sets out definitions of data requirements on a strategic and tactical level and ensures data hierarchy that can produce c-suite metrics and low level tactical datapoints using a bottom-up data gathering approach. For example, daily utilisation metrics could drive future portfolio strategy and at the same time be used to predict how many lunches to provide in a canteen on any given working day.

Investing in the future

These technologies and skills require investment - companies struggling to survive may not be able to shoulder the cost. However, when economic cold winds are blowing and companies need to tighten their belts, making the right decisions becomes more important than ever, meaning they can’t afford not to have data that accurately reflects today’s baseline.

One global life sciences company decided 10 years ago to introduce the discipline of collecting and analysing property data across all its buildings globally. It was one of the first to use sensors and Wi-Fi log-ins to measure real-time utilisation, combining it with other data sources to measure cost, space, sustainability and human experience as a balanced scorecard.

Its culture transformed and the company became much more conscious about space usage in labs and offices, always looking at the metrics prior to making decisions. This served extremely well during the pandemic because the business was already prepared for change and could put its measuring of performance into action.

Business goals drive data analysis

Investment in data technologies must support business strategy. In the longer term, we’ll see businesses really focusing on connecting different data streams and figuring out what bits of data they need for better portfolio planning, supply management and capital projects.

That’s easier said than done, which is why JLL Global Benchmarking Services (GBS) help clients to contextualise building data at-a-glance, allowing for internal and external market comparisons. Currently we are looking at three data streams: cost efficiency (rents and operation costs), consumption of energy water and waste, and human experience data segmented by location, job family and other demographic characteristics. As we develop and experiment with hybrid office concepts, other sources of data are being incorporated into the mix - including sensor data that captures real-time use.

Having this integrated data enables better decisions with a longer horizon because you can forecast the impact of actions taken today. We are living through a time when portfolios and benchmarks are changing.  Post pandemic changes in the benchmarks are still just marginal, but as more new purpose designed hybrid offices become reality, the cost, sustainability and utilisation benchmarks will also change. We expect a big shift in values within the next two years.  That is why market comparisons are as important as ever. We are working on establishing the change in operating parameters of hybrid versus traditional offices globally to allow our clients to build more robust business models based on verified benchmarks.

Ultimately, it’s about how business decision makers, through improved understanding of data, can use real estate to better support the business, its people, and sustainability goals. In these times of high uncertainty, the right metrics can help remove the guesswork, informing wiser decisions based on data - not instincts - and enable business productivity and growth.

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