By Tanuja Adiani, Managing Director, U.S.
“[Real estate] is the most solid security that human ingenuity has devised. It is the basis of all security and about the only indestructible security.” – Russell Sage, American financier and businessman
As indestructible as real estate is, the winds and tides of change are formidable forces. In the data-driven ecosystem of today, information on these changes is the ultimate tool enabling growth, agility and diversification – making adoption of data-related tech critical.
This summer, we hosted a real estate and data analytics panel and networking event in New York. With external speakers from real estate technology platforms, audit firms and investment managers, offering a range of interesting perspectives, we gathered a number of insightful and actionable key takeaways.
Here, we share the top three takeaways for real estate investment firms to consider.
1. As alternative asset markets open up, real estate firms need to prioritize adoption of new technologies
Much like the wider private markets space, the real estate sector has historically been slower in tech and AI adoption, but it’s undeniable that real estate data analytics empowers professionals to make data-driven decisions regarding the operations, acquisition and disposition of commercial real estate. It’s becoming increasingly essential to expedite adoption as data analysis and stakeholder regulations becomes more complex.
A key first step in the process of effective data collection and analysis is understanding why this data is needed in the first place – e.g. LPs need strategy data, GPs need revenue data, and managers need risk-reduction and ESG data.
2. Portfolio data can be extensive and disparate, but AI is here to help
As property and investment managers look to various data sources to drive decisions and results, data integrity is essential.
Portfolio data is vital information but time-consuming to sort through. Robust processes deploying AI enable teams to reallocate resources and focus human attention on strategic business objectives.
Benefits of AI:
- With AI and data, investors and property managers can better understand:
- How are their assets performing compared to what was underwritten?
- How much have leasing assumptions changed since the underwriting?
- How are owned portfolios faring compared to industry benchmarks?
- Examples of leveraging AI and data analysis:
- Comparing asset expenses, net operating income (NOI), capitalization rates and other metrics to industry indexes such as NCREIF and INREV
- Scanning leases and providing dynamic pricing to align with markets
- Sourcing deals and understanding asset performance
- Leveraging predictive analytics to foresee risk, as Cherre’s Margaret Guelzow discussed in her example of predicting potential risk with WeWork
Challenges of AI:
- There are several lawsuits around the use of AI for algorithmic price setting, which typically raises rent and violates anti-trust laws
- Machine learning is dependent on data sets and contextual references that it’s exposed to; in the current socio, economic and geopolitical environment, there is no substitute for human analysis.
3. Specialist service providers can help firms put their best data-driven foot forward
Unreliable data is the biggest challenge in the sector right now, but we’re here to help. Through our Snowflake-powered data platform, we provide a sophisticated tool to collect, clean, organize and analyze data to ensure it is standardized and consistent.
IQ-EQ’s real estate data analytics team derives actionable insights, aiding investment managers, investors, lenders, deal-makers and auditors amongst other professionals.
With our support, data can be used for forecasting profitability, determining optimal times to buy or sell, analyzing potential tenants, conducting successful negotiations, and allocating marketing efforts – all helping future-proof your firm.
Watch our event highlights video for further insights:
To find out more about IQ-EQ’s real estate data services, please get in touch.
