Interview with Isabel Herranz

An example would be one that we, the European School of Business & innovation, have developed recently. We have created a prototype for textile corporations to incorporate digital and intelligent tags in their clothes so the companies could know: how their clothes are being used, how many times they are being worn, what time of the day or year they are used, what type of colours or clothing people are combining, who has bought the piece of clothing and that person's profile. This will produce a huge amount of data that will allow companies to have a deep knowledge of how pieces of clothing are being used in order to tailor and optimise products according to customer behaviour and needs.

Researches and educators are constantly working on developing a better environment to create a more technological approach of fashion education. There is still a long way to go, but fashion educators are now realising how important are the new concepts of IoT, AI and gig data in every link in the chain and they are also becoming aware that they need to constantly reinvent themselves to be competitive with other industries.

The Internet of thing (IoT) is another concept that has earned a place in retail; knowing and managing  product status in real time, connecting things that beforehand would not be connected as a piece of clothing have become subjects of immense interest for textile players. IoT is already delivering an ideal scenario for textile corporations and at the moment no limitations are foreseen. The end goal is to bring the things we use in day-to-day life over a network that can be accessed across the world over the internet. This means every piece of clothing or gadget will be connected without human interaction.

Our school is focusing on deep learning, which is a class of AI that involves feeding into a computer system a lot of data, creating algorithms in neuronal networks. It can be used to make decisions about other data in an autonomous way. We are using deep learning to focus on customers. The customer-centric model is at the core of our research across industries, especially in the textiles industry where competitiveness is wild. It is fundamental knowing about customer behaviour. We use neuromarketing techniques such as galvanic skin response, electroencephalography or eye tracking to study and understand customers mind process and be able to impact in the right moment (moments of truth) where the customer is taking a decision to like or dislike something in the customer journey.

Our approach is innovative from an educational point of view. We have broken the barriers between traditional education and the business world. Our students work closely with companies helping them to give a solution to their problems, like if our students were members of the business team and using different methodologies for the approach as design thinking, lean start up, etc. We run labs and master classes with recognised professionals and researchers, where students have the opportunity to interact, experiment and discover trends, technologies or methodologies. Esbiedu, offers the opportunity to go on a trip and explore the innovative network of a country and discover relevant work. We strongly believe that the best way to learn is by experiencing.

Creativity is the only barrier for IoT. There are multiple uses in this field and it is an area that offers huge opportunities to explore. Business-wise there are new ways of working that will lead to more business knowledge. Intelligent tagging in pieces of clothing to discover customer behaviour is an example of how companies will understand customers and will take better business decisions. Interaction between clothes and us is another use of IoT as a body regulator. Clothes can monitor the user's body and be adjusted to the body's needs. Even interaction between pieces of clothing can be addressed as an example of use of IoT. Clothes could communicate with other clothes or even clothes that are worn by someone else and take automated decisions without involving people.