Confirmation bias: we believe what we want to believe by favoring information that confirms preexisting beliefs or preconceptions. This results in looking for creative solutions that confirm our beliefs rather than challenge them, making us closed to new possibilities.

Conformity bias: choices of mass populations influence how we think, even if against independent personal judgments. This can result in poor decision making and lead to groupthink which is particularly detrimental to creativity as outside opinions can become suppressed leading to self-censorship and loss of independent thought.

Authority bias: favoring authority figure opinions ideas within innovation teams. This means that innovative ideas coming from senior team members trump or better all others, even if other concepts, ideas, and inputs could be more creative and relevant to problem-solving.

Loss-aversion bias: once a decision has been made, sticking to it rather than taking risks due to the fear of losing what you gained in starting something and wishing to see it finished. We also attach more value to something once we have made an emotional investment in it. A consequence of effort, time and energy put into creative thinking, team members can become biased and become emotionally attached to their outcomes. To remedy this, the 11th commandment: “thou shalt not fall in love with thy solutions”.

False causality bias: citing sequential events as evidence the first caused the second. This can occur within the Design Thinking empathize phase where you are intentionally seeking confirmation of causality between what people say vs. what they do, leading to taking the wrong problems or needs forward to solve.

Action bias: when faced with ambiguity (creative fuzzy-front-end) favoring doing something or anything without any prior analysis even if it is counterproductive: “I have to do something, even if I don’t know what to do”. Team members can feel that they need to take action regardless of whether it is a good idea or not. This can be an issue when under time pressure in strict design sprint workshops for example.

Self-serving bias: favoring decisions that enhance self-esteem. This results in attributing positive events to oneself and conversely negative events as blame on oneself. Within innovation workshops, this can mean that decisions made can be loaded with personal agendas rather than customer and business logic for the company.

Framing bias: being influenced by the way in which information is presented rather than the information itself. We see this one all the time, particularly when developing prototypes for pitching as well as in presenting polished slides. People will avoid risk if presented well and seek risk if presented poorly meaning that decision making logic can easily be skewed.

Ambiguity bias: favoring options where the outcome is more knowable over those which it is not. This bias has dire impacts innovation outcomes because the process is fundamentally risky and unknown process. If team members sub consciously favors known known’s, you will most likely follow know knowns and previously trodden paths.

Strategic misrepresentation: knowingly understating the costs and overstating the benefits. When developing innovative concepts, ballpark figures and business model prototypes, teams are prone to understating the true costs and overstating the likely benefits in order to get a project approved (which happens all the time in large governmental contracting). Over-optimism is then spotted and challenged by managers assessing how truly innovative team outcomes are.

Bandwagon bias: a commonly known bias favoring ideas already adopted by others.This is especially influential when linked to authority bias. The bandwagon effect is a common occurrence we see in workshops. The rate and speed at which ideas are adopted by others (through discussion, the rate of silent dot voting etc) can significantly influence the likelihood of those ideas and concepts being selected by the group and taken forward.

Projection bias: from behavioral economics, over-predicting future tastes or preferences will match current tastes or preferences. This bias has particular influence as new innovations are conceived in the now and are projected into the future when they enter markets resulting in over value-appreciation of consumer preferences.

Pro-innovation bias: new innovations should be adopted by all members society (regardless of the wider needs) and are pushed-out and accepted regardless. Novelty and ‘newness’ are seen as inherently good, regardless of potential negative impacts (inequality, elitism, environmental damage etc) resulting in new ideas and concepts generated being judged through somewhat rose tinted spectacles.

Anchoring bias: being influenced by information that is already known or that is first shown. This causes pre-loaded and determined tunnel vision and influences final decision making. We deliberately manipulate team members’ minds by ‘pre-loading’ them one of our warm-up exercises to demonstrate this bias at play. The impact is highly-significant on creative thinking and outcomes.

Status-quo bias: favoring the current situation or status quo and maintaining it due to loss aversion (or fear of losing it) and do nothing as a result. This is a subtle bias on an emotional level that makes us reduce risk and prefer what is familiar or “the way we do things around here” as it is known. It has severe consequences when seeking out new ways to creatively solve needs and problems.

Feature positive effect (close links with optimism bias): due to limited time or resources, people tend to focus on the ‘good’ benefits whilst ignoring negative effects even when the negative effects are significant. This is influential when deep-diving into specific new feature sets for new concepts (especially when coupled with loss aversion bias) because it means that teams will overlook missing information especially when it is outside expertise resulting taking ideas forward with critical flaws.


16 types of cognitive bias
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