All fund and real estate investors have data that they may not be utilizing because it seems cumbersome and overwhelming. Even the phrase “big data” may seem daunting.
However, big data simply means taking large volumes of data and applying computer analysis to identify patterns and trends. For example, data can be used to document occupancy, overhead and maintenance costs, and track how many employees a company needs.
Big data can effectively help guide investment decisions, and with the right tools — including artificial intelligence (AI) and machine learning (ML) — turning data-driven, decision-making into an investment strategy can be quick and efficient.
William Lively, CEO of EXtrance Inc.
Time to take action is now
With so much uncertainty and volatility in the capital markets today, owners are focusing on what they can control, and that includes the fundamentals that drive performance.
Investing in technology, specifically related to data, is key so the front office is more informed and can make better decisions in a very competitive environment. The only way to really do that is to look inward and focus on data and assets and determine what you can improve. After all, investors are evaluating different funds based on how they operate internally and the fundamentals that drive their performance.
Three things to know about the role of big data in your investments
1. Have accurate KPIs (key performance indicators)
Paying close attention to KPIs means investors can take data and drill down to very specific, actionable pieces of information, which are typically left to analysts, and, therefore, human error.
For example, investors can dig down as specific as revenue per occupied room, which requires big data to determine that number on a monthly, quarterly and yearly basis.
In an EXtrance pilot implementation during COVID-19, a hospitality fund needed to assess the real-time effects of deploying different operational strategies during the slow reopening, including whether investments in marketing translated into improvements in overall average occupancy and the resulting impact on staffing costs.
The operator also needed to know if the hotels would generate more than average F&B spend per guest because of the restaurant closures. These nuances in the data showed the effects of different operational strategies across all the KPIs using machine learning that the neural network was tracking. This allowed the operator to be smart with its cash and strategize for better overall outcomes in an extremely unprecedented and unpredictable time.
2. Take larger market data and simulate future scenarios
Using data allows investors to create a hypothetical staging environment where they can add an asset to their portfolio, for example, and see the impact it would have on cap rates and the need for future full-time employees. As we were developing the EXtrance platform, our networks were able to simulate an acquisition, with different types of capital structures, and see the impact of all relevant KPIs and the overall fund strategy utilizing a sandbox environment with massive amounts of historical data.
A fund manager may ask: “In two years, based on how the market has performed over the last 25 years, what’s a realistic picture of how this asset will appear on the books? And how will it affect our long-term vision for our fund?”
Without complex data analysis, most of these acquisitions are done on “gut-feeling” and with a quick review of simple data that doesn’t consider how one data set impacts the other data sets. By leveraging these tools, funds begin to develop a competitive advantage over one another.
3. Track performance of investments over long periods of time
Investors can gain new insight by taking 10 years of single property data and drilling down into futuristic types of projections. They can look at some strategies that worked for the property and some that didn’t. This is done by taking large sets of data, such as for family offices, which may hold an asset for 10 or 20 years. They can look at a property’s operational data including energy usage and staffing and use the data across the portfolio to see if they need to adjust strategies.
What data can tell you that you might be missing
Anomaly detection
Owners/investors can use AI and ML to find patterns in the data and define acceptable numeric values in which the data should fall. Knowing where the data should fall and being able to easily detect even the smallest anomalies gives better insight into the data and detects things that would normally be missed.
For example:
- If an investor or owner is looking at data over a 10-year period, the AI and ML system is predicting what those values should be – from food and beverage expense to room expense to any type of expense or profit that has historically been earmarked.
- Or after acquiring a new asset, administrative costs may gradually impact overall return. Our anomaly detection network uncovered that a single asset fell outside of expected administrative expenditure for its size and value due to a creeping pricing structure by that asset’s accounting firm. That expense was quickly renegotiated.
- Investors can use data to track the capital structure, debt draws, capital calls, and distributions, and determine how that impacts the portfolio’s financial outlook. This data can speak to a large fund and include performance indicators of the properties.
How data can be used for a better roadmap and better decisions
Data gives the front office the ability to focus on what is important and lay out forecasting models for how their fund is going to adjust, what types of assets they need to acquire, what assets they need to sell, how they need to look at their capital structure, and whether it is worth restructuring.
Additionally, data offers insight into whether it is worth taking on more debt, acquiring more assets, or decreasing or increasing full-time employees. Data offers insight into what the future looks like, and that can help the front office make better-informed decisions.
Using blockchain, AI and ML for smart contracts to improve liquidity
Blockchain is a technology that enables the secure sharing of information. It helps investors stay organized and streamlined by protecting contracts, records, and legal documents. Blockchain is revolutionizing real estate by making it easier for limited partnership members to buy, sell, and manage their assets.
Smart contracts are helping fuel this trend, as they automate processes, streamline transactions, and improve security, efficiency, and transparency. Smart contracts also expand the pool of prospective buyers and sellers, further boosting liquidity. Utilizing smart contracts saves time and money and is helpful with funding gaps and redemption requests.
William Lively is CEO of EXtrance Inc., a commercial real estate investment platform with AI integration, machine learning and blockchain technology. EXtrance was independently acknowledged as the preeminent AI-powered real estate solution of 2023 by Acquisitions International and featured prominently among the top ten overall real estate solutions by Proptech Outlook
