We examine how firms discover effective competitive positions in worlds that are both novel and complex. In such settings, neither rational deduction nor local search is likely to lead a firm to a successful array of choices. Analogical reasoning, however, may be helpful, allowing managers to transfer useful wisdom from similar settings they have experienced in the past. From a long list of observable industry characteristics, analogizing managers choose a subset they believe distinguishes similar industries from different ones. Faced with a novel industry, they seek a familiar industry which matches the novel one along that subset of characteristics. They transfer from the matching industry high-level policies that guide search in the novel industry. We embody this conceptualization of analogy in an agent-based simulation model. The model allows us to examine the impact of managerial and structural characteristics on the effectiveness of analogical reasoning. With respect to managerial characteristics, we find, not surprisingly, that analogical reasoning is especially powerful when managers pay attention to characteristics that truly distinguish similar industries from different ones. More surprisingly, we find that the marginal returns to depth of experience diminish rapidly while greater breadth of experience steadily improves performance. Both depth and breadth of experience are useful only when one accurately understands what distinguishes similar industries from different ones. We also discover that following an analogy in too orthodox a manner—strictly constraining search efforts to what the analogy suggests—can be dysfunctional. With regard to structural characteristics, we find that a well-informed analogy is particularly powerful when interactions among decisions cross policy boundaries so that the underlying decision problem is not easily decomposed. Overall, the results shed light on a form of managerial reasoning that we believe is prevalent among practicing strategists yet is largely absent from scholarly analysis of strategy.