This article is sponsored by PATRIZIA
The German-based investment manager PATRIZIA has taken a deep dive into the data pool and crafted its own artificial intelligence (AI) tools to inform and justify investment decisions across its €47 billion platform. Paul Hampton, head of international funds, and Marcelo Cajias, head of data intelligence – investment strategy and research, explain to PERE’s Mark Cooper where the data is taking them.
How can data and analytics be used to enhance a value creation strategy?
Paul Hampton: Investing well is based on developing an edge and forming a conviction – a strong view. An investor’s team and track record have always been an integral part of such a value creation approach and Patrizia obviously benefits from having one of the largest operating platforms in Europe; we have more than 900 experts on the ground – 200 of them in residential. However, it’s no longer just about team and track record, especially when it comes to predicting trends and forming strategies based on those trends.
If the last year has reminded us of anything, it is that the future isn’t always a function of what has gone before. Therefore, the way we’re looking at and using real estate data is changing seismically. We are focusing more on technology to inform our investment decisions and to help identify behavioral trends behind the macro trends driving real estate. This is knowledge-backed investing and to that extent, we have invested in artificial intelligence to more precisely understand how to plot our future course.
We are in a fortunate position of having €47 billion in assets under management, which means we have a lot of information coming in from tenants and partners across that portfolio, which is incredibly valuable. However, we also use data to take a deeper dive into individual markets and inform investment decisions.
How is Patrizia using data and analytics to provide investment insights?
Marcelo Cajias: We started incorporating technology around eight years ago – collecting data, analyzing data, cleaning data and merging data. Today, we have a suite of tools to find patterns in data. For example, we’ve created an asset-pricing report, which can tell us the current level of rents in a certain city and what is driving them. We collect data from multiple listing systems and our algorithm allows us to determine what’s driving pricing. For example, the tool shows us that, in Munich, there is a rental premium for assets with a built-in kitchen. However, in Stuttgart, the most important price driver is the existence of a balcony. And in Vienna, for example, it’s the proximity to the Metro.
In the past year, we’ve developed a new tool – the Amenities Magnet report. What we have done is to teach our systems to evaluate locations, based on their amenities. This is what AI tech is all about, recreating the knowledge of human professionals, but at scale and at speed. The report provides us with a heat map of the city, which benchmarks locations from 0 to 100. A location with a score of 100 would be a street with the highest availability of amenities, including restaurants, schools, kindergartens and pharmacies. The tool confirms and quantifies what we might feel about a market and supports investment decisions.
Also, we have a tool which we use to understand the fluidity of assets – how many weeks it takes for a listed property to be rented. In Munich, for example, you would wait on average one week, but in other cities you’ll wait two months. This means the vacancy risk in Munich is nearly zero, but higher in other cities, which will be a factor in underwriting.
We’ve developed a Spatial Dynamic Analysis, which uses AI to find patterns in rental data for cities, based on data we’ve tracked for years, in order to create a weather map for rents, showing which locations are getting hotter and which colder. This drives investment decision-making and also allows us to benchmark our portfolio more accurately.
We invested in these technologies because investing in real estate today is much more complicated than a decade ago and because we have much more data to deal with. We have developed our own algorithms to process this data and we collaborate with universities in this development.
So, the future of real estate investment is digital?
PH: The digital underpinning of the knowledge supporting an investment thesis is going to be absolutely critical. We recently took a survey of a significant number of the firm’s investors and a high proportion – 80 percent – said digitally informed strategies are very important.
And once investments are secured, knowledge-based data reporting is going to be critical to assess performance. And this information will need to be delivered quickly and on demand. We live in a world where it’s all about speed and accuracy of data, especially for investors managing global portfolios. Data needs to be available at the touch of a button.
It will also be extremely important in the context of increased reporting requirements, which our investors need to adhere to, particularly ESG reporting. ESG has become much more of a focus for managers, investors and occupiers, and this drives a need to use technology to help quantify the E in the ESG. People want to see their impact over time: What’s my carbon footprint? How are things improving? How are costs changing? We need technology in order to be able to answer those questions effectively and efficiently.
ESG is intrinsically linked to the concept of smart living, which is the cornerstone of our Living Cities residential fund. It’s becoming increasingly important to show our residents that we are a thoughtful investor and that we’re here for the longer term. That means developing buildings that are smart, which inform us as to how they should be managed and can share information with occupiers on how things should be improved.
We’re increasingly looking at installing smart systems within the buildings, particularly where those buildings have centralized building management systems, so we can monitor energy use, for example, and work with tenants to reduce those costs over time. Part of that is forming more of a partnership with tenants, rather the traditional adversarial model. One way to rethink this relationship could be to learn from the hospitality industry and how they strive to ensure a comfortable living experience.
Can you give an example of how data and ESG link into Patrizia’s investments?
PH: We’re investing in five projects in the Poblenou area of Barcelona, known as 22@. We started researching and developing our investment thesis seven years ago, but what attracted us in the first instance was just how progressive a city it is. Barcelona has been designated as a smart city and Poblenou is a showcase of that approach. As an example, there are more than 12,000 sensors in this small 200-hectare area collecting data on weather, traffic, air quality and other metrics. This data is invaluable in helping city planners and informing decisions on building design and local amenities. And of course, it matches our data-driven ethos.
Poblenou used to be a textiles district, which has been regenerated into a much trendier hipster area and now attracting design businesses, fashion and some biotech businesses. There are a number of universities in the area, and it’s really a melting pot for creativity. We’re working on a residential scheme and a number of office projects too, catering for a tech-savvy and ESG-conscious tenant base. And we’re dovetailing that with the smart city in building design, using smart construction and community involvement. It’s a work in progress, but extremely exciting.
With more AI in real estate, is there a smaller space for human intelligence in the world of digital investment?
MC: Definitely. Real estate is a people business and always will be. We need storytelling around our assets and data. However, AI and data can give you a completely different perspective on the market. Because of our models, we might see perhaps more value or less value in portfolios because of our analysis of the data, which is unique due to our investment in data analytics.
PH: This data-driven strategy is an embedded part of our investment strategies and how we think we’re going to differentiate ourselves from our peer group. However, you can’t do this without our people across the platform, across the world. So, it’s not just Marcelo’s team, but the wider innovation and tech group and that’s all part of a really big and knowledgeable group of people.
Asset focus: Nike HQ, Warschauerstrasse, Berlin
An 8,600-square-meter former industrial building, damaged in the Second World War, has been revitalized by Patrizia and chosen by sportswear firm Nike as its German headquarters
Paul Hampton, head of international funds, says: “We saw an opportunity to buy a building of tremendous character, with the most wonderful industrial facade and to add a modern twist, with the ESG specification required by tenants.
“For example, to avoid piping and reduce energy consumption, the building breathes naturally and contains no active ventilation system. Every desk group has a large openable window and at night windows open automatically to control climate. The thermal mass of the concrete structure and automatic exterior sun shading keeps the need for cooling to a minimum, while the transparent, high-efficiency facade significantly reduces heating energy in winter.
“The building’s position, the ceiling heights and natural light enabled us to create the sort of building which tenants feel will help them attract and retain staff.”