Business model innovation is a process that allows firms to build and maintain competitive advantages. However, it imposes major challenges to managers who rely on incomplete cognitive representations while attempting to understand the environmental dynamics that determine a business model's prospective performance. System Dynamics is a computational approach potentially useful in enhancing managerial understanding and decision-making during business model innovation, yet its effects lack sound empirical evidence. This study of five cases inside BMW assesses the usefulness of System Dynamics along the different phases of business model innovation processes. In order to develop a nuanced understanding we triangulate insights from the multiple-case study approach with results from a Q-Sort exercise. Our emergent theory highlights that System Dynamics enables managers to develop more accurate cognitive representations about their business models. Unexpectedly, we find that this process leads to a cognition gap apparent in the communication with managers not involved in the modelling process. We observe two strategies to overcome this gap. A second key insight is that System Dynamics has a tendency to consolidate mental models by different managers that need to be managed cautiously. We develop a set of 11 propositions that represents the core of our theoretical insights.