Vesteda is a Dutch residential investor focused on mid-segment rental housing in major urban regions. In doing so, the company invests funds on behalf of institutional investors, such as pension funds and insurers. Vesteda was looking for a way to make better use of the large amount of data at its disposal to improve its services. “By switching to TimeXtender, we were able to automate the manual work we were still doing across five different modules,” says Jelle Vegter, team lead BI & Data Science at Vesteda.
- Client: Vesteda
- Industry: Real Estate
- Product used: TimeXtender
The Result
Getting started independently
Vesteda's employees received TimeXtender training from E-mergo, so they can now work with TimeXtender themselves. This means they're no longer dependent on E-mergo consultants for changes.
Automated
TimeXtender has automated a number of processes that used to be manual and time-consuming. It acts as an "orchestrator" that now controls five of Vesteda's existing modules, making the turnaround time from request to go-live considerably shorter.
Data-driven
Vesteda now has better insight and can make better decisions by working in a data-driven way. The data warehouse plays a crucial role here, offering extensive insight into the data while meeting strict privacy and security requirements.
Vesteda makes better decisions through housing stock data analysis
By the end of 2020, Vesteda had invested a total of nearly €8.2 billion in Dutch residential real estate. Its rental portfolio comprises more than 27,400 homes, located mainly in economically strong areas and major urban regions. A portfolio of this size comes with a lot of data. By combining data from financial systems with data from all kinds of other sources, the residential investor can draw meaningful conclusions. Until a year ago, it did this through a manual process that was time-consuming, error-prone and spread across five modules. Jelle Vegter had therefore been searching for some time for a solution to replace the old data warehouse.
“My first impression was that TimeXtender could automate a number of processes that were time-consuming and error-prone.”
Jelle Vegter
Team Lead BI & Data Science
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