The housing market in Germany is under pressure. Flats are in short supply, especially in metropolitan areas. According to the GdW, the umbrella association of the housing industry in Germany, 360,000 new flats need to be built nationwide – every year! However, this absolute figure is only one side of the coin. To solve the problem of supply and demand, the flats also have to be built in line with actual need. This is where real-time demand data comes into play.
The German housing industry has a strong regional character: developers and project developers therefore often have extensive local knowledge, which they use to build in line with the market. Nevertheless, even new-build projects in the most sought-after regions usually have vacancies after completion. Surveys among customers of Hamburg-based Immomio GmbH, the leading proptech for digital letting, show that it generally takes between 3 and 12 months for new-build projects to be fully let.
On completion, often only 50 to 75 per cent of the flats are let. One reason for this is the classic challenges of letting new builds: an above-average number of viewings, because most applicants register their interest in several flats. Marketing is time-consuming and the communication and coordination effort is enormous. Our letting solution helps to speed up these processes, but vacancies are nevertheless unavoidable.
The dynamics of supply and demand
The most common reason for vacancies in new builds is flat types that are difficult to let. This is where the dynamics of supply and demand become apparent: if too many flats of a type without sufficient demand are built, marketing can drag on for months. This can quickly become expensive, as the following sample calculation shows: for a new-build project with 150 rental flats averaging 68 square metres each and an assumed net cold rent of €15.50 per square metre, the project’s monthly net cold rent amounts to €158,100. With an occupancy rate of 65 per cent on completion and 6 months until the project is fully let, the lost rental income amounts to €193,673. This corresponds to a loss of more than 10 per cent of the return in the first year.
The problem of forecasting different flat types
This inevitably raises the question of how demand for different flat types is forecast in the planning phase today. First, the price level of a new-build project is determined. To do this, the asking rents for new-build flats in the relevant neighbourhood are analysed. This is where a first distortion occurs, because the flats published on property portals are used to calculate the asking rents. However, property portals often only list show flats, while the individual flats in a project are offered via a separate project website – and there are significant price differences depending on the flat’s position within the building. A further price distortion arises from the fact that a disproportionate number of hard-to-shift flats are offered on property portals, as flats in high demand are let quickly even without being advertised. In this respect, relying on portal asking rents to set the price level is risky.
Determining which flat types should be built is even more difficult. This requires demand to be determined. Often, the number of people moving into the neighbourhood is analysed. A high number of new arrivals is taken to indicate high demand. However, this conclusion is only half the truth. People move in partly because of new construction, but largely because of natural turnover in the existing housing stock. High turnover is not the same as high demand. In addition, the disposable household income in the neighbourhood in question is usually examined in order to draw conclusions about flat sizes. The age structure of the neighbourhood also plays a role – particularly when planning the fittings of the new flats. The problem is that the current income level and age structure in a neighbourhood often say little about the demand to be expected. Neighbourhoods are constantly changing, so the true need can differ significantly from the current resident structure of the area.
Existing potential is not being exploited
Once the price level and demand have been forecast, a flat mix is set for the building. However, this planned flat mix contains many uncertainties, as the planning was based on imprecise price points on the one hand and on a demand forecast based purely on the status quo in the neighbourhood on the other. To achieve an optimal balance between supply and demand, genuine demand data at the location must be analysed – ideally real-time data rather than historical data. The reason this does not happen for most projects is that this data is often not available. Yet it is precisely the housing companies, which are responsible for a large proportion of new rental housing construction in Germany, that hold all this data. Last year, for example, GdW member companies created 34 per cent of all new rental flats in Germany. Unfortunately, however, this data has so far not been collected and used holistically.
Making real-time demand data usable
Our letting platform now makes it possible to put this data to use. Portfolio holders and property managers with more than 500,000 residential units in their portfolios let their flats via Immomio – both existing and new-build flats. Unlike property portals, we do not just handle the first contact between provider and prospective tenant, but digitalise the entire letting process right through to the digital signature of the tenancy agreement. The demand data gathered in this way from all landlords on the platform helps to make precise statements about the need for flat sizes and types. This enables developers to put together their flat mix on the basis of real-time demand data, ensuring that there is actually demand for the flats that are built. This avoids vacancies and shortens marketing times. The demand data can also be used to analyse different price levels per flat type in order to determine the optimal rent. From 2021, Immomio will make this data available to its portfolio holders free of charge in a new module, thereby helping to ease pressure on housing markets.
In our Topic Council at the REAL Proptech Conference our Managing Director Nicolas Jacobi will present market analysis using real-time demand data. Together with property expert and proptech investor Rolf Elgeti, Nicolas Jacobi will discuss untapped potential in the property industry and the true value of data.