Personalization of products and services entails not only risks but also potentials for sustainability. During the product development process, it is crucial to take into account future usage patterns and their variability. Even if the product itself is not personalized, a user-centered approach during the entire life cycle can unlock many potentials. Avoiding unnecessary functions and tailoring a product precisely to its user’s needs can lead to optimized sustainability performance during its use. Moreover, by developing and offering personalizable products that meet the requirements of the respective user, companies can tap into new market opportunities and increase their competitiveness. As a methodological basis, we introduce a combination of the Stuttgart models of personalization and personalized product development with life cycle thinking aspects and circularity strategies. In an interactive workshop the integrated model is discussed and participants can locate their own work and perspective within the broader personalization scheme. Different opportunities of personalization are highlighted from an environmental point of view.

Individualization is considered a megatrend in postmodern societies. The markets react with the individualization of products. However, many approaches fail after considerable sums have already been invested. Therefore, this paper presents a benefit-oriented method to identify potentials for the personalization of products. It first accompanies the product through its life cycle (product journey) in order to identify various users and then these users on their user journey in order to observe the product experience. From these observations, a set of ideas for personalization is derived, which together with the associated benefits represent the personalization potential. The method has successfully been tested by individuals and teams in face-to-face workshops and online events using scenarios from the mobility, construction and service sectors. The learning effort is low. The personnel input per analysis amounts to approx. 150 hours. The method is to be further evaluated using concrete use cases in industrial practice.