Data Analytics Is Making Commercial Real Estate More Transparent


Updated: January 18, 2023 - 6 MIN. READ

While the impact of an economic slowdown and rising interest rates is yet to be fully seen, Commercial Real Estate (CRE) profits have been soaring. Part of this success is attributable to the economy. Another significant part involves better data for identifying risks, opportunities, and cost savings.

Savvy real estate investors and property owners are benefiting from the insights that data analytics provides and are utilizing them to transform their commercial real estate business' bottom line. Are you taking full advantage of data analytics to maximize your returns?

This article aims to help you answer that question. In addition, we will provide some suggestions to help you become a more data-driven owner and investor.

Changing dynamics

Decisions around commercial real estate have long been numbers-driven. For years, real estate firms have made decisions based on traditional data like vacancy rates, estimated expenses/profits per square foot and plain intuition.

However, the results, at times, have produced suboptimal decisions.

As a result of the current greater availability of data and analytics solutions, one can now ingest more granular data and draw more insights to make strategic decisions rather than relying on hunches or alleged best practices.

Still, the CRE market has generally lagged behind other financial sectors in capitalizing on modern data analytics capabilities. Today, property owners have much more data at their disposal than just a few years ago. New variables and technology tools are fostering better projections, cost metrics, purchasing decisions and business deals.

But NOI is still the key focus

Despite those trends, the objective remains to maximize Net Operation Income (NOI). The NOI metric is commonly used throughout the industry to measure the profitability of income properties.

The definition of NOI is the total of all revenue generated by the property minus all expenses reasonably attributable to the operation of the property. Non-cash expenses like taxes, depreciation and amortization are excluded.

To translate NOI into property valuation, you need to multiply NOI by the capitalization rate (cap rate). The cap rate is derived as:

[(Total NOI for a given year) / (the current value of the property)] * 100.

For example, if a property has a rate of return of 4%, and NOI of $1,000,000, the cap rate is 4. The value of the property is thus $4,000,000 (4*$1,000,000).

Cap rates, expense reduction and property valuation

The magic of cap rates is that every dollar of expense reduction generates an increase in property valuation (of $1.00*cap rate). For example, with a cap rate of 4, reducing operating expenses by $50,000 annually increases the property value by 4*$50,000, or $200,000.

There is a significant opportunity for improving valuations

Building owners aware that an average of $1.45 per square foot is spent annually for the maintenance, repair and operations (MRO) of CRE buildings need to be able to quickly gauge and assess their MRO spending for their real estate portfolio.

They also need data tools to try to find ways to reduce expenses while boosting profits.

With 97 billion square feet of space in the U.S. commercial real estate market, MRO alone accounts for over $100 billion in addressable operating expenses.

Quickly and effectively reducing operating expenses with high-quality data and analytics can significantly improve your bottom line. Without great data and solid analytics, you will struggle.

Effective CRE firms are using increasing amounts of data today to better assess a building's finances, from initial lending to ongoing maintenance, along with developing actionable insights. Without actionable insights, data gathering is wasted energy.

Crunching numbers on net effective rents, market demand, leasing spreads, data gleaned from the Internet of Things (IoT) sensors and other analytic solutions enables more informed decisions.

The influx of new data sources has increased the complexity of owning real estate; however, it has also enabled many property owners, management companies, and contractors to make better decisions.

Big data transforming real estate

McKinsey & Company researchers have found that non-traditional data sources are becoming increasingly relevant alongside demographic and crime information. They found traditional data sources are important, but nearly 60 percent of predictive power may come from non-traditional data sources.

One study showed apartment buildings in Seattle that are within a mile of specialty grocers, such as Trader Joe's and Whole Foods, increased in value faster than those in other areas. Another study showed the impact of proximity to a Starbucks on property values in Boston.

Big data is also transforming real estate lending by using credit risk algorithms that analyze data from various public and licensed sources to produce real estate risk scores. The result is better transparency and reduced credit risk.

The Internet of Things (IoT) is also impacting CRE. Smart devices yield powerful data that you can use to cut electricity and maintenance costs and boost property values.

One example is smart building technology. Sensors in individual buildings monitor data as basic as temperature and humidity, and more complex data like equipment runtime, mean time to failure, and maintenance frequency.

The IoT is used to connect multiple buildings to monitor and collect data on a portfolio of properties on a local, regional, national or even global level. In addition, remote diagnostics save businesses time and money.

Artificial intelligence (AI) can combine with smart building technology and the IoT to enable machine learning. Building systems can learn from data over time to optimize their performance. Thus, an entire portfolio of properties can self-optimize with real-time data. Cost reduction in things like energy, maintenance, and capital repairs is the result.

Data analytics is impacting supply chain deal-making as well. For example, Raiven’s platform aggregates information on MRO suppliers and contractors to improve purchasing decisions. Raiven leverages this aggregated data to enable property owners to boost their bargaining power and lower their average MRO expenditures per square foot.

With Raiven Marketplace, users are provided access to pre-contracted deals with pre-vetted, high-quality suppliers with discounts of 7-25% on the products your business purchases the most.

In short, Raiven provides the benefits of a Group Purchasing Organization (GPO) without the hassle of signing up for a GPO membership.

Alternatively, Raiven enables you to automate your procurement processes with an easy-to-use, cloud-based tool. If you want to plan and manage your procurement initiatives, Raiven is the solution for you.

To protect your procurement savings from rogue purchases (those made outside of negotiated contracts), Raiven Marketplace tracks compliance in real-time to give you the transparency to ensure your procurement processes are being adhered to by your buyers.

In addition, its digital assistant provides electronic guardrails to guide buyers away from non-compliant deals and towards approved ones.

In either case, Raiven provides consistent, high-quality procurement data in a central, easily accessible location. It also provides analytics for supplier performance evaluations.

Hurdles for adoption

Successful data-driven approaches can yield powerful insights into running any business, including ones in the CRE arena. So what is holding you back from capitalizing on available data?

There are several reasons why real estate professionals, investors and contractors have resisted becoming more data-driven. A key reason often cited is the lack of industry standards and processes defining data descriptions, gathering and interpretation. Without some standards, data can be misconstrued and lose its value.

Because of the lack of industry standards and processes and the sheer scale involved, data governance is crucial to success. It is a framework of integrated policies, standards, and processes focused on two major aspects: data integrity and data security, without which credibility is lost. The lack of formal data governance is a recipe for failure in big data.

Because data governance cuts across functional boundaries, it is essential to appropriately involve all relevant stakeholders. The cross-functional nature of the change demands close coordination and supports the use of a Program Management Office (PMO) structure.

The PMO should own both planning and implementation responsibilities to maintain continuity.

For many firms, a bigger issue is limited analytical capabilities. You need talent and tools to source and leverage data. Building (or purchasing) advanced analytics capabilities is no straightforward task. Collecting enough data to build accurate algorithms takes time. Scrubbing data can be costly in time and dollars, and there is fierce competition for analysts in all industries. Despite the rise of more consulting firms and applications, CRE firms need to be able to translate increasing amounts of data into actionable insights.

Getting started with data gathering

The growth of big data and vast potential types of variables to explore may seem daunting to you. Where do you start accessing data to make a difference in your bottom line?

Keep it simple.

Start with Raiven's MRO Marketplace and platform to improve your procurement results. The platform makes it easy for you to access purchasing data and deep discounts on parts and materials. You can also extend your discounts to your contractors, further impacting your results. You instantly get access to high-quality data and analytics. To learn more, visit our website or connect with us by phone or email.

Procurement Optimization