Introduction The SKIN model (Simulating Knowledge dynamics in Innovation Networks; for a detailed introduction see Ahrweiler et al. 2004) is a multi-agent simulation of firms that try to optimize their innovation performance in order to respond to the requirements of a constantly changing environment. Simulated scenarios can inform decision makers about the chances and risks of investing in different learning activities while taking into account the firm’s markets, its clients, competitors and partners, its external and internal resources, and its strategic policies. In this chapter, we suggest that the SKIN model can be linked to the body of literature on ‘organizational learning’ (OL) (for an early overview, see Dodgson 1993 and for later surveys, Amable 2003, Bahlmann 1990, Lam 2003). Following Garvin’s statement (Garvin 1993) that only learning that can be measured will be useful to managers, the SKIN simulation shows the outcome of different learning activities. The model embodies some theoretical ideas from the OL literature and implements many OL concepts (e.g. from Argyris and Schön 1996, Levinthal and March 1993, March and Olsen 1975, Senge 1990). Thus, the SKIN model is not only interesting for managers and other practitioners responsible for empirical learning processes within firms but also for scientists testing theories from the body of research on organizational learning.