The Faste Laboratory - a leading innovation environment
The Faste laboratory is a leading inter-disciplinary innovation environment where researchers collaborate with industries to derive solutions for performance based business models. The research has a close link to global sustainability challenges where economic growth is expected while the population is increasing and natural resources are finite.
Performance-based circular business models create incentives for sustainability and resource efficiency - while companies can be successful. Ten years of research at the Faste Laboratory have shown significant improvements in sustainability when companies develop solutions they retain the ownership and responsibility for during the entire life cycle. In traditional business customers are charged for the hardware and services, i.e for both accessibility and inaccessibility. But the customer who buys functional products only pays for the availability of the function.
New methods for circular transactions
Our research has shown that this type of circular business models provides an increased resource efficiency compared to linear models. The Faste Laboratory is working to develop new methods and tools for innovation based on functional products with optimized life cycle cost. The objective is that the industry partners involved should take the lead in performance-based business models and that the society thereby becomes more sustainable. The basis is a completely new theory which includes a definition of a life cycle that looks different for functional products compared with traditional products and services.
Need for research and knowledge
Several companies have already taken significant steps towards providing performance instead of products. But there is still a great need for more knowledge in areas related to organizational issues, law, contracts, design and social aspects to move towards more performance-based way of doing business. Future research also needs to focus on the processes for the development, operation and recycling, including the prediction of key properties.