The human brain is wired to have bias. Our pre-conceptions, built from experience and education, allow us to avoid having to re-evaluate every piece of information we come across; we can make decisions quickly and with a relatively high degree of accuracy. Biases are normal, and helpful – until they’re not. When used in substitute of facts, and especially in changing circumstances, they can be detrimental to accurate decision-making and can actually prevent the generation of new ideas and theories.
Bias in Biochemistry
Kevin Dunbar studied four biochemistry labs to examine how scientists learn and make discoveries. He believed that the real process is messier than the “scientific process” would have us believe – and he was right. His research on the way that scientists dealt with dissonant data reinforced previous psychological research that found that people are naturally resistant to new information; we search for evidence that confirms what we already believe. For this, you can thank the combined workings of the anterior cingulate cortex (ACC) – what scientists call the “Oh shit!” circuit, triggered when you see something wrong – and the dorsolateral prefrontal cortex (DLPFC) – our brain’s “delete key” that suppresses contradictory evidence. Combined, they allow us to identify and overlook “wrong” information.
What counteracts the delete key? Open discussion and debate. Studying lab researchers, Dunbar found that the best new ideas didn’t come from the laboratory, but from the weekly discussions where researchers presented their work – where their pre-conceptions were tested and pushed by their colleagues.
The Market Research Equivalent
This dynamic is no different for market researchers when it comes to insight generation; insight requires discussion and debate of even those observations which seem anomalous. The task for market research leaders: to create an open environment that welcomes new ideas for discussion. Failing to do so can limit insight to the realm of conventional wisdom.
No matter what insight generation method you use, you need to make sure to follow three key steps to remove bias:
1) Separate the activities of observation and hypothesis generation
2) Create team support for new ideas
3) Evaluate all ideas
MREB members, access best-in-class practices for avoiding bias, and other advice on insight generation methods.