Startups: Confidence vs. Knowledge
What is the Dunning Kruger Effect?
Social psychology calls it The Dunning Kruger effect. It is a form of cognitive bias that has devastating effects on startup businesses – a mirage that kills time, money, and dreams. It happens to first time entrepreneurs that are enthusiastic about starting a business venture but have no knowledge or business experience. This is when entrepreneurs are likely to make poor decisions and reach erroneous conclusions, but their lack of experience denies them the conscient ability to recognize their gaps. Simply put, they are not aware of what they do not know.
The less experienced entrepreneurs fall to illusory superiority, rating their knowledge level way higher than it is. Sometimes we see the opposite – when more experienced entrepreneurs underrate their own level of knowledge and go down the slope of illusory inferiority.
Why it happens?
It all happens because of the way we perceive the future, in a mix of knowns and unknowns, and not entirely making sense of it. When starting a business venture, we translate the future in terms of outcomes; literally imagining that the business will start, pick up, and be successful. But the success of a business is driven less by a dream and more by data, research, analysis, by a customer-oriented strategy and a precise business plan.
What is the impact?
When we are overconfident that the business will succeed, without understanding how it will happen, we fail to objectively evaluate our level of competence. Overconfidence is blurring the rational decision-making process and we are therefore more likely to make decisions that are based entirely on our opinions.
How to avoid it?
Confidence is a “must have” as a startup business but there is a very fine line between confidence and overconfidence. We should be driven by both our dreams and knowledge to achieve our goals.
To ensure a balanced start of the business, one of the main questions we must ask ourselves is: How am I going to do it?
A successful business is not an expensive trial-and-error exercise but an extension of data-based and unbiased decisions.