In my previous post, I showed you two sets of choices. If you are like most people, you would have chosen answer A in first choice set and answer B in second choice set. In other words, you would have chosen to receive a sure shot $100 but would have chosen a coin toss when giving me $100.
Thousands of people have chosen the same answers and this provides us a deep insight into human fallibility. In first choice you are choosing between a sure gain of $100 versus a probability adjusted gain of $100 ($200 X 0.5 the probability of losing the toss). In the second choice set, you are choosing between a sure loss of $100 versus a probability adjusted loss of $100. From a rational perspective, you should be indifferent between the two choices. Moreover, when thousands of people choose between two options in these choice sets, we should see no systematic patterns. Approximately half the people should choose either answer in each choice set. Why then do people show a preference for a sure gain over a probabilistic gain and a preference for probabilistic loss over a sure loss? What does it tell us about human nature?
Other than the fact the we are not truly rational beings, it shows another important fact. People systematically overestimate the true probability of winning when choosing between a sure loss and a probabilistic loss. In other words, they become risk seeking. More specifically, if someone believes that the probability of head in a coin toss is 0.5 then he or she believes that the probability of winning a coin toss is more than 0.5 when choosing between a sure loss and a probabilistic loss.
Although the coin toss probabilities do not change in reality, they do change in a person’s mind. This systematic anomaly in humans is an example of several decision making biases we are prone to. These results came out of research by Daniel Kahneman and Amos Tversky. This experiment has been replicated in more ways that you can imagine and the results are always the same. In some cases, the problem was worded as saving some ships in other cases the problem was worded as a money problem. The responses demonstrated the same patterns.
This behavior pattern has a direct implication for managers facing a rogue innovation. Embracing a rogue innovation is a path to sure shot loss of profits. Avoiding the rogue innovation is a path to probabilistic loss – if the innovation fails the incumbent firm loses nothing but if the innovation succeeds the incumbent firm may lose most of its business. This choice between a sure loss and a probabilistic loss is the same choice as I showed in my previous post. This choice set could make firms systematically underestimate the probability of success of the innovation. This is another important challenge facing an incumbent firm that faces a rogue innovation.
Managers of incumbent firms have to deal with a basic human flaw in decision making when dealing with rogue innovations. This makes rogue innovations particularly challenging. Stay tuned for more on rogue innovations.
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