How data science could change the decision-making process in the architecture field.

Nowadays more and more industries are improving their products and services thanks to data science. But what would it be its impact if it was to be integrated within the Design & Build Process?

The first step of data science is essentially collecting data about individuals such as what they like or dislike, what their habits are, what they are interested in, what makes them happy and more. This data can be obtained by sending questionnaires to people, by analysing their behaviour on social media platform or online, and even by conducting a simple survey. Thanks to this information it is possible to map out people and sort them according to 5 behaviour categories.

The second step is to translate these data points into an algorithm and be able to predict people’s future behaviour patterns. This ability is an extremely powerful tool for Marketing and Propaganda purposes as well as for tailoring a product to a specific audience.

Now what does this technology could mean for the architecture field?

Imagine being able to map out the client’s requirements

If we were able to collect the data of all the requirements given by clients and turn them into algorithms, we would be able to predict what they wish for the next tender. For example, if we were to analyse past projects from one single client (a government, a private developer, a single investor ecc..) we could probably identify some similarities between all of them in terms of program, but also, we would be able to collect data about the way he has organised the tender and how he took his design decisions.

From this data, it would then be possible to generate an algorithm and apply it to future tenders in order to determine design options which would be more likely to be validated by the client. This would mean not only a shorter design process than what we are used to, but we would also be able to beat potential competitors according to the algorithm accuracy. The downside would be, however, that on a longer timeline, some projects may start to look-a-like and lack in innovative prospective and there would also be a risk of a monopolised market.

Imagine being able to map out the users’ needs and feedbacks

If we were able to collect data points on the users we would be able to predict their future behaviour thanks to algorithms. This would mean that the architect would be able to anticipate the user’s preferences and integrate them directly within the design. It would enhance the quality of architecture as spaces would be shaped according to the different needs of the stakeholders. Furthermore, it would result in a considerable optimization of the design and decision-making process that architects have to go through as well as the quality of the design itself.

In conclusion, if data science was to be applied in the architecture field it could really change the process, by shrinking timelapse but also by generating design tailored to the client’s requirements and the user’s needs. This could be the future.