Commercial real estate (CRE) professionals are, at their core, advisors. They help business leaders make the right real estate decisions based on dozens of interconnected factors.
The best of these professionals capitalize on the power of data to forecast market conditions like property value, rent, occupancy rates and return rates years into the future, allowing them to advise clients based on the goals of each investor and occupier. With the right data, they can help investors become first movers — those who can identify subtle trends and act on them before anyone else, resulting in significant bottom-line advantages.
Predictive analytics (PA) is currently the biggest trend in CRE data analytics. In a recent Deloitte survey, more than 80% of investors indicated that CRE businesses should prioritize the development and use of PA and business intelligence, as predictive data analysis saves time and creates efficiencies.
So, what are predictive analytics? IBM provides a straightforward definition: “Predictive analytics brings together advanced analytics capabilities spanning ad-hoc statistical analysis, predictive modeling, data mining, text analytics, optimization, real-time scoring and machine learning. These tools help organizations discover patterns in data and go beyond knowing what has happened to anticipating what is likely to happen next.”
Essentially, PA harnesses the most cutting-edge technological tools so investors and industry leaders can predict trends and prevent future problems, instead of responding after trends and problems have manifested. Using machine learning algorithms, they can even identify overlooked correlations to make more accurate predictions.
The commercial real estate (CRE) professionals who can win the race toward full integration of PA will be leaps and bounds ahead of their competitors when it comes to identifying and acting on trends. At Colliers International, we have built a platform focused on collecting and aggregating data, and are in the early stages of integrating analytics into our decision making, using several proprietary analytics tools.
Here, we evaluate how data gathering and PA offer specific benefits to three major segments in the CRE world: investors, occupiers and property managers. Further, we’ll delve into the tools we utilize at Colliers, and the results these tools help CRE professionals achieve for our clients.
Predictive Analytics for investors
Real estate professionals can work collaboratively with investors to develop highly-tailored solutions, based on market indicators.
For example, the newly developed Skyline AI company has created software to collect, organize and analyze data on all multifamily properties in the U.S. — that’s more than 400,000 properties. The data is highly specific and includes statistical points that range from area restaurant locations and crime stats to demographics and education levels for specific markets. Investors immediately ascertain the predicted value of a property on the platform — a number that would usually take extensive data collection, multiple weeks and some guesswork to determine.
When applied to CRE, data like this can help CRE advisors make property recommendations based on an evaluation of where the market will be in the next 5-10 years. Will property values remain the same? How about occupancy rates and rents? CRE advisors and investors use this data to negotiate tenant lease renewals and rental rates by executing a blend and extend transaction to maximize space efficiency and minimize real estate costs, for example.
This data can also allow advisors to make investment recommendations. Predictive analytics help identify additional markets that fit each investor’s profile, based on a multitude of factors. Large-scale gathering and analysis of data offers market predictions within minutes, moving the real estate market closer toward the stock market model.
Lenders can also use survey data to evaluate and predict interest levels for properties and identify potential investors based on critical financing data.
Predictive Analytics for Occupiers
For industry leaders and large-scale national and global companies, PA will prove invaluable in offering a means to stay ahead of competitors and manage large, and often evolving, real estate portfolios.
Like in the multifamily example, PA can stitch together hundreds of small, nontraditional metrics — such as the number of gas stations in a two-mile radius or the average rating of nearby bars — with traditional metrics, such as vacancy rates, to create a fuller and ultimately more accurate picture of the future.
Likewise, PA allows CRE occupiers to predict shifting labor markets as they plan for current and future employment needs, down to the specific type of worker. These predictions are leveraged as business leaders identify new sites for expansion.
Our Colliers360 tool allows portfolio managers to recommend portfolio expansion strategies based on predictions of business revenue and growth in number of employees. It is data analytics on demand, so occupiers can make informed, data-driven choices about the trajectory of their business.
Cutting-edge analytics allow advisors to leverage data about labor markets and market access to guide the industrial site selection process. This tool allows advisors to swiftly facilitate the site selection process, reducing it by months while providing more holistic recommendations.
Predictive Analytics for Property Management Efficiencies
PA will also create groundbreaking shifts in commercial property management. CRE tech blogger Michael Beckerman notes that predictive analytics will “forecast future maintenance issues, use real time data and statistical modeling to reduce energy management costs and respond to tenants needs before they actually surface.”
And ultimately, efficient property management is predictive, not reactive. Within our proprietary real estate management services, we use data to track tenant requests, contractor work and repair history. Data points like these can point to patterns that indicate potential problems, often before they arise.
When paired with smart-building technology, Deloitte notes in its CRE Industry Outlook report, that data analytics tools “can automatically identify patterns and detect anomalies in the data that smart sensors and devices generate — information such as temperature, pressure, humidity, air quality, vibration and sound.” Property managers can identify concerns before tenants even notice, and they can use data to model “what-if” scenarios and implement innovative new models, which will increase cost effectiveness and tenant satisfaction.
Data and predictive analytics guide Colliers’ professionals through every aspect of commercial real estate — from identifying investors and guiding them to potential investments, to portfolio analysis and expansion strategies, to managing the properties within a portfolio. As we continue to collect more data and advance our analytics tools, we increase our ability to make recommendations that accelerate the success of our clients — whether an investor or occupier.
About the Authors
Jake Edens serves as Colliers’ senior vice president of Technology & Innovation, U.S.A., where he leads a team of innovators with a primary focus of building a cutting-edge commercial real estate technology platform to drive exceptional results for Colliers professionals and clients alike. Prior to Colliers, Jake founded REscour, a commercial real estate data platform and decision engine, where he served as Founder and Chief Executive Officer.
Chris Lexmond is the Vice President of Engineering and Product Development (USA) for Colliers International. In this role, he leads product teams within Colliers’ Technology & Innovation group. Before joining Colliers, Chris co-founded REscour with Jake Edens, serving as Chief Technology Officer. He has also created DevMap, a crowd-sourced mapping platform tracking developments across the country.