Data intelligence offers dynamic insights that guide investment strategy
27 / 06 / 22 - 5 minute read
The reason was the view: the property overlooked a park where flowers bloomed spectacularly in the summer. This attracted tenants who were more than willing to pay steep rental prices. The PATRIZIA Amenities Magnet Report had noted the park’s location but not the type of flowers inside.
PATRIZIA relies increasingly on artificial intelligence (AI) to help inform its investment decisions. It also boasts one of the largest operating platforms in Europe, with more than 900 experts on the ground, 200 of them in residential. This unique combination of data obtained by artificial intelligence and local market knowledge provided by human fund managers enables PATRIZIA to develop a knowledge-based investment strategy and identify anomalies.
“A data-driven strategy is an embedded part of our investment strategy – we believe that technology is here to help us and provide us with recommendations,” says Dr Marcelo Cajias, PATRIZIA’s Head of Data Intelligence. “But we also need local knowledge to understand what is happening on the streets to corroborate our strategy. It’s a combination – there are always peculiarities in the market that we’re not aware of from the data perspective.”
Table of content
Amenities make a location
For the last couple of years, PATRIZIA has benefited from the use of the Amenities Magnet Report to evaluate the attractiveness of locations based on the access to nearby amenities, or so-called Points of Interest (POI) across Europe and Japan. The Amenities Magnet Report accesses a database of more than 25 million POIs, categorised to allow the attractiveness of a location to be measured, based on residential, modern urban living, senior housing and office requirements.
When given a geo-location – a street name or address – the digital tool provides a score ranging from 0 to 100 according to the quality of amenities in and around that location. The higher the score, the greater the supply of positive amenities and, therefore, the more attractive the location. Good amenities might include a school, green space or transport links. Negative amenities could include a prison, motorway or wastewater plant.
After producing a score, the next step is to analyse the results geographically with a heat map. The brighter the yellow scores at the grid locations displayed in the heat map, the higher the score. The darker the green patches, the lower the score. The Amenities Magnet allows PATRIZIA to acquire a transparent opinion of the market and effectively rank locations, says Cajias.
“We now know the difference between yellow, green and dark locations. This is like going to the bank and asking for different interest rates, depending on your default risk. The best locations in Germany, for example, tend to be near a city’s central main station because you have lots of good amenities there.”
Dr Marcelo Cajias, Head of Data Intelligence, PATRIZIA
Understanding the urban footprint over time: the PATRIZIA Amenities Magnet Dynamic produces green patches in locations that have increased their attractiveness as measured by the supply of amenities. White means consolidation and red means slower development and a weaker position. The heat map can help identify market opportunities. Here the city depicted is Brussels.
Dynamic data development
PATRIZIA has now taken the Amenities Magnet Report to the next level by introducing the Amenities Magnet Dynamic. This tool assesses whether amenities have changed over time, allowing PATRIZIA to compare relevant data across different years and then calculate the changes. With an overview of changes in locations’ scores, PATRIZIA can then identify those areas that have improved their supply of amenities and those that have decreased what is on offer.
“The Amenities Magnet Dynamic genuinely reflects how cities have evolved based on this algorithm and how they will evolve in future,” says Cajias. “This enables us to understand if we’re in the right location and if the location has evolved in the way we expected.”
This updated knowledge is then amalgamated with local knowledge from experts on the ground. “They may say, ‘Yes, I agree that’s a good location.’ For example, they’ve seen a new shopping centre opening nearby. Or they may disagree about what is happening in that location,” adds Cajias.
Data knowledge steers strategy
Machine learning creates knowledge at speed, scale and depth. Thanks to cloud computing, the Amenities Magnet’s calculation power is 70% faster: it now only takes seven minutes, not 20 minutes, to generate a report about any given location.
The amount of information is also increasing exponentially. For example, a few years ago, Vienna had 40,000 different amenities. This has now grown to 65,000 POIs.
Overall, values generated by the tool help PATRIZIA to identify opportunities that can change the conversation with a tenant or investor. For existing assets, the tool can confirm that PATRIZIA is in the right location with the right strategy. It can also identify the level of amenities in a potential investment location.
Is there an oversupply or undersupply of amenities, and if amenities are low, which are missing? After entering a new city area, the concentration of amenities should increase over time. Areas with lower ratings can also be attractive as an investment
location in the case of the development of new housing and associated amenities.
In future, data intelligence will play a critical role in identifying streets and districts with the best potential and in understanding how a city is evolving so we can further optimise the portfolios of clients.
“This kind of technological advantage is unique to PATRIZIA,” concludes Cajias. “It is something we are doing for our investment processes and offering to our clients to rebalance portfolios and to continue to recreate balance.”
Image credit: istock olrat. April 20, 2019: Passengers waiting on an underground platform in Brussels central station, the busiest railway station in Belgium