Due to a growing real estate portfolio in recent years, Unistone lacked a clear, structured way of recording real estate information, making it difficult to exchange data. Diverse real estate data was recorded in various systems and applications. Managing data then became difficult, time-consuming, and it took a lot of energy to find the necessary information in this way. And that’s a waste and inefficient. Managing data with confidence, making informed decisions, and extracting value from real estate data was Unistone’s goal.
Inventory of available data
The very first step in this process was to gain insight into the available real estate data and cluster it into clearly structured (main) building components, including interior design, fire protection, exterior wall finishes, roofs, installations, central heating, etc. The data was recorded in a fragmented manner: fragmented across systems and applications, as well as fragmented in the way it was stored. Ultimately, some of the real estate data was always recoverable, and where necessary, Unistone and Oxand jointly inspected it to complete the condition of the properties.
Assessing conditions & risks
By recording all data and information in a uniform manner and storing it in a single, central location, insight and overview of the condition of the properties, as well as insights into the risks within the real estate portfolio, were created for each building component.
Enriching data
The next step in the process was to enrich the real estate data with predictions about obsolescence over time and predictions about associated maintenance costs and required investments in the properties. Oxand uses its database for this purpose, which has been collecting knowledge, experience, and asset data for over 20 years.
By adding this knowledge, Unistone was able to (more easily) look ahead and see how the condition, risks, and maintenance costs of the property would develop in the short and (medium) long term.
Simulating and analyzing various scenarios
The data obtained is accessed via online dashboards in Oxand’s Simeo application. This allows various maintenance scenarios to be simulated, compared, and analyzed. This provides much better insight into the effectiveness and impact of the various maintenance and investment scenarios, both in the short and long term.
The scenarios and analyses yielded very striking results for Unistone, for example, when replacement investments can be expected and how much they will cost; which maintenance scenario is the most expensive and which the least expensive; and their effect and impact on the portfolio’s risk profile; and the required maintenance and investment budget for the next 20 years and its breakdown by building component and property.
By comparing the various scenarios, Unistone gained insight into the differences in investments and risk profiles, both now and in the future. The real estate data is recorded uniformly and is accessible via a single application. This enables Unistone to make the right decisions about the real estate portfolio in a substantiated and data-driven manner.
