What is more likely to kill you:
A shark?
Or a cow?
Most people would be much more afraid of a shark. After all, they are known to be an alpha predator, and many movies show how easily they will kill anyone that comes to close. Indeed, a 2010 survey conducted in the USA found that shark attacks were one of the top 6 most feared ways to die.
However, in the last 500 years only 1,909 confirmed shark attacks occurred worldwide (as of the 2015 research paper); of the 737 that happened in the United States, only 38 people died in total.
Whereas also in the USA, cows kill around 22 people every year. Cows are far more deadly than sharks.
So why do we appear to think that sharks are more likely to kill you?
Because of a very common bias we all suffer from, known as the availability heuristic.
Originally popularised by Daniel Kahneman and Amos Tversky, the availability heuristic is a mental shortcut that means the easier a person can remember examples of something (like an event happening), the more likely or impactful the person will think that thing is compared to examples which are harder to remember.
On the flip side, research has shown that the harder it was for people to think of an example of an event, the less likely they thought it would happen again in the future.
How easy it is to think of “available” memories is often strongly influenced by the media around us. The media, and especially the internet and television news, know that negative news and events has a much stronger emotional reaction than positive news. Fear, tragedy and anger are especially likely to have people engaged and watching. As a result, there is a phrase used in media called “If it bleeds, it leads“, meaning the worst, most tragic news is often given the most time and attention available, and talked about long after it really happened. More common incidences are less likely to get the equivalent media attention, especially if they stoke less fear in individuals.
That is the reason why TV stations can have a whole week devoted to sharks every year. But I have never seen a “cow week” get primetime TV slots.
Other examples of the availability heuristic affecting people’s perceptions and fears is people being afraid of their airplane crashing (even though they are much more likely to be killed driving a car than flying) or being killed by terrorists (which is apparently as rare as dying in an avalanche). But because of the type of media coverage these rare events get, people have stories of them available in their memories, and therefore think they are more likely to happen.
As a result, things which are easy to remember, because they are in the media or news more often, are likely to be considered as more likely than they are in reality. And also these events where there are more “available” examples in the media are likely to be considered more likely than the events which may be more boring, get less availability and news coverage, but in reality are more likely.
Other research has found that how easy or difficult people experienced being asked to think of examples from their own lives made them feel differently about themselves. In a series of experiments, some people were asked to think of six examples (which was easy) of when they had been assertive, and then were asked to rate their overall assertiveness. Other people were asked to think of 12 examples of when they were assertive (which was much harder), and because they found it challenging, they ended up rating themselves as less assertive than the “think of 6” group for whom it was easier.
Interestingly, this is just as likely for real events as it is for events which people were asked to imagine happening. Participants who spent time imagining a future event thought that event was more likely compared to another event which they had not spent time imagining.
This is where the availability heuristic can become a real problem for innovation teams.
Because these innovation teams spend so much time thinking about their own innovation, and imagining how it can be successful in the future, it can cloud their judgement and make them think that it really is likely to be successful. After all, they may also suffer from confirmation bias and survivorship bias which leads them to see examples of other startups and innovation teams which went on to be wildly successful and worth billions.
That is because the media does not talk as much about the huge numbers of startups which end up failing as they do about the small proportion which end up succeeding.
If they spend more time thinking it will be successful than what could be a challenge or go wrong, they may also think that the issues with it not going to plan are less likely than the successes.
As a result, they may then be surprised when the reaction from customers is not as enthusiastic as they imagined it to be.
So in order for innovation teams to improve their actual likelihood of success, it makes sense for them to also spend time imagining how and why things might not go to plan.
For example: why might our customers end up not buying our innovation even though it is great?
That way, the team will slowly consider the dangers and risks to be more likely as well, find them easier to recall, and begin working on ways to address those challenges before they become reality.
Nick Skillicorn
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