What would you prefer:
- Partially cleaning up two nuclear waste sites, saving 50 lives in the first and 40 in the second every year
- With the same amount of effort, completely cleaning up one of the two sites, saving 70 lives a year
While you might not be aware of it, you are likely to choose option 2, because it reduces a certain problem down to zero.
Even though if you had focused on improving several problems partially, you would have actually had a much larger overall impact (in this case, saving 90 lives a year compared to 70).
This is known as the Zero Risk bias.
It is a form of unconscious bias which shows that people prefer to completely eliminate a specific risk in a sub-part of a problem, rather than alternative options where some risks are reduced (but not eliminated) but which have a much larger overall impact.
It stems from our basic desire to reduce risk and increase stability and safety.
As a result, people overweigh and favour complete certainty and opt for “zero risk solutions”, even when other solutions would be more beneficial.
The impact of this in innovation programmes can be challenging. Decision makers are naturally biased towards solutions that feel lower risk to them, or even no-risk. However, since innovation projects undoubtedly bring a degree of risk in their very nature, the bias can influence the decision-maker when faced with an option of a highly creative but risky innovation, compared to a less creative, less risky option.
In most cases, the biological response of the decision maker will be to prefer the lower risk, less creative option.
Even if the more creative option could bring significant benefits in the future.
So what can we do to reduce the impact of the Zero Risk Bias?
Lower the perceived risk of the innovation and project.
Firstly, set up frameworks and processes to bring confidence in the management of the portfolio of projects.
Then, communicate often and clearly. The more often someone is exposed to an idea, the more favourably they will perceive it.
You might not be able to completely eliminate the bias. But you can reduce it.
Nick Skillicorn
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