• Another example of the difficulty of learning from defeat. “When a party loses there are two reform factions — the We Were Wrong faction and the Double Down faction. And obviously the Double Dow faction won in 2008, because the Republican base really believed that it lost power because it failed to cut taxes and spending.” Or as David Frum puts it, “This failure of governance seems to demand some rethinking. ‘Say it louder,’ at least in my book, does not qualify as rethinking.”
  • “For a long time, scientists and science-fiction writers alike have pursued the question whether you can accurately predict the future from the past given sufficiently large groups, historical information and computational power. … As our world becomes increasingly integrated, fast changing and unpredictable, we expect large improbably disturbances – black swans – to occur more frequently, not only in finance but across business, government and society in general. Mathematical models, information analysis and fast computers will continue to be extremely valuable tools, critical to the smooth functioning of our complex systems. But, when the going gets really rough, no machine or model can ever make up for the wisdom that only comes from human judgment and experience.”
  • “Organizations that go through rare and unusual events, whether they are costly or beneficial, face the challenge of inter- preting and learning from these experiences. Although research suggests that organizations respond to this challenge in a variety of ways, we lack a framework for comparing and analyzing how organizational learning is affected by rare events. This paper develops such a framework. We begin by first outlining two views of rare events. The first view defines rare events as probability estimates, usually calculated from the frequency of the event. The second view defines rare events as opportunities for unique sensemaking based on the enacted salience of specific features of the rare events. We next use these definitions to explore how rare events trigger learning, and then examine the kind of learning processes that are triggered by rare events. We conclude with a discussion of promising areas of research on learning from rare events.”
  • Years ago, I believed that rationality could manufacture understanding. I lived in physical and social environments that were real and I wanted to understand the social realities. I wanted to create a genuine ‘behavioral science’ based on mathematical models, computer simulation, and systematic experiments. Various experiences over the years have challenged these beliefs. I discovered that rationality can not only be a deceptive tool but a potentially dangerous one, and I learned a few techniques to help me challenge my rational thought….
  • In forecasting, simplicity usually works better than complexity. Complex forecasting methods mistake random noise for information. Moderate expertise proves as effective as great expertise. Linear functions make better judgments than people. Analogous principles probably apply to research. Three common myths do not stand up to scrutiny: One, using fewer categories does not reduce the effects of observational errors. Two, least-squares regression does not produce reliable findings. Three, better fitting models do not predict better, even in the very short run, if researchers use squared errors to measure fits to historical data and forecasting accuracies. However, better fitting models would predict better if researchers would replace squared-error criteria with more reliable measures.
    (tags: forecasting)
  • Managers and management researchers tend to assume that learning from strategic events yields benefits. Although some firms have gained competitive advantages from learning, instances are infrequent, and firms that have gained persistent advantages through learning are probably quite unusual. Learning from successes has short-run benefits but eventually makes firms less capable of surviving, whereas learning from failures disappears in clouds of rationalization and defensive behavior. Noisy feedback about results causes people to develop very heterogeneous and often highly erroneous perceptions of firms and their environments, so it should not be surprising that strategizing is harmful as often as it is helpful.
  • “This study analyzes the outcomes of fourteen strategic failures in a very large European telecommunication firm. The study asks what the company learned from these failures. Does learning from failure differ from learning from success? How does the learning from large failures differ from learning from small failures? Rather disappointingly, the company learned little from its experiences. Why is learning from failures so difficult? What were the key impediments to learning?”
  • “All learning has uncertain consequences, but learning from rare events is especially problematic. Learners see many idiosyncrasies and exogenous interference, tendencies that suppress learning on an organizational scale. Rare events also rouse uncertainty and bring on reactions to uncertainty such as wishful thinking, reliance on prior beliefs, biased probabilities, a search for more data, cautious action, and playing to audiences. The most important contingencies affecting these reactions are the content and strength of prior beliefs: people are unlikely to learn if they think they have nothing to learn. Although learning from rare events is statistically unusual, and effective learning from rare events is rare, both individuals and organizations can benefit significantly from active efforts to learn from rare events.”
  • Applies Fred Emery’s typology to a study of leadership and accountability. “In Type 4 environments, it is not acceptable for leaders to claim that successes are due to them and failures are due to factors beyond their control. The important forces will always be beyond their control in these environments. It is how the leader helps us to learn about ourselves and others and the world around us and build our capability to live with uncertainty and diversity that is, in today’s world, the real test of leadership.”
  • The importance of the exploratory front-end of strategy is well established in fields such as foresight and knowledge management. However, it has received little consideration by roadmapping practitioners and researchers. This is partly explained by the fact that roadmaps are traditionally a convergent, goal-oriented outline of a sequence of activities and actions. It can also be attributed to the fact that knowledge exploitation tends to dominate over knowledge exploration, as the former delivers clearer and more tangible returns. This paper investigates how roadmapping may be applied for knowledge exploration, considering the conceptual underpinnings and a practical example in which an exploratory roadmap was developed for foresight in the packaging sector
  • This study provides an organizational perspective on roadmapping as currently practiced, presents the experience of several organizations that have implemented it, and evaluates the results. Using a case-based, exploratory method the author addresses several practical questions, such as: What are the effects of roadmapping? How are they measured? Is roadmapping always appropriate? How would an organization know if it was roadmapping well? What are the various kinds of roadmaps and how do they relate to each other? In addition, some more general lessons about organizational behavior emerge from the case data. Cases were selected from several large industrial firms participating in a research consortium exploring the modern challenges and tools of technology management.