When we talk about Real Estate Data Management we most likely work with raw property and financial data. Data which needs to be interpreted in order to support smart and informed decision making.
On the 18th of June, we arranged our webinar related to Real Estate Data Management where we discussed exactly this topic a bit further. As guest speakers, we welcomed Erik Marienfeldt, CEO of HIH Real Estate GmbH, Thomas Veith, Partner Real Estate deals at PwC and René Richter, Managing director at CR Investment Management GmbH. Here are our key takeaways from our discussion:
Technology can easily solve Real Estate Data quality and management challenges
Most of the Real Estate Data are managed on spreadsheets that lack transparency and integrity necessary for them to be a reliable source for decision making. Besides that, data hierarchy (property, fund or company) is impossible to organise and maintain in spreadsheets. Present-day technology can easily solve data quality and management challenges. However, it is important to first define what data should be extracted and collated to be meaningful for decision making – therefore the role of the C-suite is to agree on a set of performance metrics based on their business goals.
These performance metrics should reflect not only one company’s business goals but also to be verified by other stakeholders such as investors and banks.
During our webinar we discussed the following topics with representatives of the C-suite of real estate companies, consultancy and technology firms:
- What real estate KPIs and underlying datasets drive strategic decision making
- How to build Real Estate Data Management practices and control the quality (transparency and integrity) of data
- How to decide on the right digital solution that brings the company to its strategic and financial goals
- What is an ecosystem and what is an approach to build it
As for the main indicators we could classify them into the following categories:
- Macroeconomic time series on local and country-level
- Tenant performance-related datasets
- Property user data (customers profiles, social & demographic datasets etc.)
Competitive benefits through incorporating big data
These indicators come on top of the traditional parameters used in real estate scenario analysis such as rental value, vacancy rate and inflation. But as more versatile data becomes available, it brings competitive benefits to those who factor it in the decision making process.
The demand for more accurate forecasts and predictions of future performance has increased. The recent global Covid-19 challenges depicted that relying on “good performance” in the past is not enough to predict future performance. A deeper understanding of underlying data correlation is required to build up multiple scenarios. As global markets can change rapidly, the winner is, as always, the one who spots new trends first.
Tenant performance is a good example of this. Before the major market disruptions of recent years, decision-makers could allow themselves to disregard tenants behaviour and simply assume that tenants will obey the situation. Fortunately or not, but measures imposed by politicians changed the balance of power towards the “tenant market”. As a consequence, landlords need to have a very thorough understanding of how strong and stable their tenants are.
The next question discussed in the webinar relates to the target property use. In the past, developers and city planners defined the target properties use. Nowadays, as customer data becomes more available: the question of use is transferred to the users – how they define the space in the building and what is the optimal way to maintain it. Space-as-a-service will gain ground across asset classes and property types.
Benchmarking shows what performance was achieved relative to the market. Portfolio analysis explains why and how. But also here, benchmarking is only possible when data is structured and consistent on a global scale.
One toolset that suits all?
The last question discussed was how to choose the right technology. We have a feeling that the industry comes to one conclusion: There is not that single one and only right technology. It should be a combination of solutions. Those linked to each other and allowing data to flow through all of them in order to make sure, the basis is the same. Developing, enabling and maintaining such ecosystems is possible with a team of internal and external professionals.
Assetti has been helping several organisations to improve their Real Estate Data Management, define KPIs for decision making and provide the technical support needed for implementing software solutions.
If you have any further questions, we are here to help.
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