This article reveals the essence of cognitive distortions and the importance of critical thinking when working on product design, value propositions, customer experience changes, and other areas related to product or service design and development.
Cognitive biases (distortions) are changes and deviations in human perception, behavior, and thinking caused by subjective beliefs, stereotypes, social, informational, emotional, environmental factors, and the peculiarities of the structure of the human brain.
If you know these distortions, you can reduce their impact on work or use them for business purposes to increase profit.
Types of cognitive biases
1. Group Thinking – making rational decisions based on a common group opinion to avoid conflict. It occurs in teams working together for a long time, with pronounced informal leaders, and in the culture, where is a practice of shifting responsibility.
It leads to narrowing the number of options to choose “safe” strategies, reducing the probability of creating breakthrough products and lacking a critical view of the problem.
2. The Halo effect – the transfer of certain qualities (good or bad) of a person to other aspects of life, interactions, etc. This distortion can lead to a biased attitude toward information or decisions from a particular person, based on exaggerating or undervaluing them based on characteristics you have previously assigned to that person (wise, expert, buffoon, etc.).
The critical question is whether the person has the objective experience, decision-making competencies, hypothesis making, and evaluation.
3. The Dunning-Kruger Effect – the less we know, the more confident we feel about solving the problem. The project framework is often expressed by underestimating the task complexity, the timing of implementation, and the resources required.
It can be compensated by the involvement of experts and the complex evaluation of risks at each stage of project implementation.
4. Confirmation Bias – a tendency to see, remember, and interpret external factors as confirming your opinion/decision. It leads to underestimation of project risks, and overconfidence, as a consequence of ignoring signals in the early stages that the decision is wrong. It is leveled out by qualitative research and tests at each critical point of the project.
5. Belief Bias – is similar to Confirmation Bias, the effect of accepting and giving more weight and credibility to arguments that confirm your personal internal beliefs. The consequences and countermeasures are identical to the previous effect. You can also add the involvement of experts and the creation of a qualitative criteria matrix for decision-making.
You can see the difference between Confirmation and Belief Bias as follows:
- I have an idea to start an electric scooter rental startup. Whenever I see someone on an electric scooter, I am convinced that this is the right decision because of Confirmation Bias.
- Two friends, Max and Alex, have opposing views on my idea, each with their own arguments. I believe Max more because he has an electric scooter.
6. Status quo Bias – is a preference for maintaining the status quo as the most advantageous. Changes are perceived as a loss. It is characteristic of constant processes, approaches to work, and products in companies. It affects the ability and speed of the team to adapt to market opportunities. The effect is counterbalanced by launching pilot projects, an iterative approach, and hypothesis testing.
7. Sunk-Cost Effect – overestimating the costs already incurred on new opportunities. “We’ve already had enough of this software; let’s not invest again.” At the decision point, we ignore the new features and try to “protect” the decisions made in the past.
This effect influences the ability to quickly relaunch products or discard past choices to obtain new opportunities. It is counterbalanced by pilot projects, tests, and financial model calculations.
8. Framing Effect – we tend to have different perceptions and make different appraisals of the same information, depending on whom and under what conditions it was obtained. In product development, the presentation of information can strongly influence the perception of research results, the selection and prioritization of concepts, and future product features.
It is possible to fight against this warning using maximum rationalization of information presentation and differentiation of quantitative and qualitative influence factors.
9. Co-creation effect – we attach more value to the idea, solution, or product to the creation of which we belong. On the one hand, this effect may reduce the probability of an objective assessment of various product concepts by the “stakeholders.” If they are a participant in the process, on the other hand, it increases the probability of adopting and maintaining the innovation within the company (group). The creation of a matrix with selection criteria reduces the risk of bias.
10. The Survivorship bias – we try to focus on successful examples, ignoring the analysis of cases that were not successful. For instance, we will create a new social network like FB, Linkedin, and TikTok! They have succeeded. We are not analyzing the experience of thousands of other startups that have gone bankrupt in this segment. This bias leads to ignoring or preliminary assessment of the causal factors and erroneous decisions.
11. The Blind-spot Bias effect – we are confident that we have no bias and that our decisions are correct and unbiased.
Craft Innovations provides services to companies and product teams to facilitate product innovation development. We will be happy to help you validate and implement your hypotheses. Contact us via email at email@example.com