Vonovia SE is Germany’s largest residential property company with around 400,000 apartments in Germany, Austria and Sweden. Vonovia is committed to ensuring high quality and safe living environments for its tenants. In order to do so, it coordinates many service providers that perform tasks all year long, such as gardening, winter and cleaning services. Some of those services are even required by German law.
However, demand for some of the services is difficult to predict. For example, take winter road clearances: they may be required every day in case of continuous snowfall and ice, or only on a few days each month. Furthermore, there is a spatial component involved, so that some units may require a particular service whereas others do not. Either way, Vonovia needs to guarantee a safe and orderly environment around its housing units at all times.
This is where you can create great value to Vonovia. At the core of this challenge is the development of an application that provides an indication of the necessity of ice and snow control services. This would help Vonovia understand where and when services are needed, and whether service providers have issued accurate invoices. Vonovia provides plenty of data regarding its housing units, such as precise location, adjacent streets and pavements, and square meters of the units. Furthermore, all rendered services are tracked in terms of time, place and type.
It is your task to incorporate weather data and other data sources you think might be of value into the model. For example, publicly available video recordings could provide an indication of snowfall.
Besides the data points mentioned in the data sample, weather data of Deutscher Wetterdienst (CDC) is used: https://www.dwd.de/EN/climate_environment/cdc/cdc.html
This data can be accessed for free.
If startups have ideas or requirements for additional weather data sources, they shall be mentioned in the application documents