The way we work has changed, with more than half of Americans working from home, the office vacancy rate jumping from 12.5% in 2019 to 20% in the second quarter of 2023. This change impacts urban cores, suburban retail, commuting patterns and other ripples through our lives.

Commercial real estate firms are on the front lines of this change and are ramping up their data gathering and analytical capabilities to measure and understand the diverse needs, wants and interests of user behavior.

A team of finance and IT professionals from Carr, a privately held real estate investment trust, teamed up with students from Virginia Tech’s Calhoun Honors Discovery Program (CHDP) in fall 2022, through an introduction by AFP, to achieve two goals:

1. Develop algorithms and utilize machine learning to identify areas of cost savings for Carr and improve customer engagement.
2. Validate Carr's investment in big data and illustrate the effective use of the technology when it comes to decision-making.

The team successfully met the first goal through the development of three algorithms that could provide valuable insights into the “nervous system” of a building. Carr had increased data collecting points throughout buildings, including security access, occupancy, indoor air quality, utilities, facility management, network utilization, and social media. Carr made this trove of data available to the students to analyze.

The second goal was successfully met through the work of the students’ financial sub-team, which was tasked with demonstrating the impact of big data initiatives on Carr’s overall net operating income (NOI). Through the development of financial models, coached by Carr, the students were able to demonstrate how big data can provide financial benefits for Carr, their customers and investors by increasing revenue and/or minimizing expenses, and improved customer engagement, resulting in increased retention rates and higher building values.  

They were also able to use the information from financial models to predict energy consumption week by week, which allowed them to optimize energy usage and efficiency, predict potential maintenance, and negotiate utility rates to save money and increase the NOI.

Further, using predictive analysis, Carr is able to study customer trends to predict whether a customer is likely to renew their lease and prepare sooner for potential turnover. And when property managers are able to identify spaces that have been underutilized, they are able to reduce energy and cleaning costs.

Of the study’s findings, Jesse Mishler, Senior Vice President of FP&A at Carr, stated, “The results of the students’ research validated and emphasized the importance of the path we are on. Additional investment in big data initiatives will provide a competitive advantage by improving customer engagement, retention, earnings and ultimately value creation for Carr’s investors.”

The team of four Virginia Tech students included Sydney Snearer, Brandon Warwick, Matthew Cagle and Meher Bhohi, all of whom traveled to Carr’s headquarters in Washington, D.C., in April to present their findings to the executive leadership team. Carr employees who worked with the students include Mishler, Ilan Zachar, Chief Technology Officer; and Aaron Altscher, Director of Technology Initiatives. The collaboration took place via weekly scheduled meetings, as well as ad-hoc Zoom meetings.

Carr intends to continue the project in the 2023-2024 academic year with a potential focus on automation of systems based on machine learning models and data forecasting, AI applications and cybersecurity.

AFP has supported Virginia Tech’s CHDP with educational content, student project judging and facilitating the Carr project. CHDP encourages cross-disciplinary collaboration to promote innovation and problem-solving for real-world applications.