Digital hybrid systems for innovation

Digital hybrid systems for innovation

Digitalisation is the strongest transformative force in today's society and it is making large amounts of data available in the retail business industry. One consequence of the rapid growth of data is that the opportunities for innovation are improved, which in turn increases the need for new innovation systems that support a data-driven decision-making process. However, the market's existing data-driven innovation systems have often been developed from a strictly technical perspective and not from an organisational perspective in which human expertise and skills have been at the forefront. Several research studies show the risks of relying solely on digital technology and its complex algorithms. These studies, in contrast, point to the importance of utilising human experiences and cognitive abilities to a greater extent.

To improve the ability to innovate and its associated decision-making elements, future innovation systems need to be developed based on knowledge that combines digital technology with human experience-based knowledge and cognitive processes. We call this combination hybrid systems. A hybrid system is defined as a specific subclass of innovation systems and combines artificial intelligence (AI) with human knowledge, abilities, and experiences in order to create valuable innovations. The project thus challenges traditional innovation models and perspectives.

Purpose and goal

The aim of the project is to create better opportunities for the retail business industry in Sweden to increase its competitiveness through new knowledge that describes how hybrid systems can support a data-driven innovation process and the various decisions that need to be made during the work.

The goal of the project is to deliver three results that will promote both the research community and the retail business industry and contribute to a fulfilled project purpose. The first result consists of design principles that aim to develop recommendations for how hybrid systems can be developed that combine automatic analyses with human knowledge and abilities. The second result is a prototype that aims to be a simple example of a hybrid system. The prototype will contain some functionality that can be used by the retail business industry and which, together with the design principles, forms a basis for the development of full-scale hybrid systems. The third result is a design theory for hybrid systems for improved innovation ability.