Sometimes, professionals rely on their intuition; their experience mixed with their "gut feeling" on a situation. In a data driven environment, this can be dangerous. Read the article "What is wrong with intuition?" noted in this week's module. When done, give an example in your professional career or someone using intuition to make a decision. What data would you have leaned on to make a more data-minded decision in that person's position?

What is Wrong with Intuition (Part 1)

Estimates based on intuition are wrong because humans are not good at mathematics without the aid of computers.

Ex-

In a group of 23 people, what are the odds that two of them share the same birthday (day and month)?

1. 5%
2. 10%
3. 20%
4. 50%

What is Wrong with Intuition? (Part 2)

Intuition is biased

Biases include but are not limited to:

1. Self-serving bias (to make us look as good as possible)
2. Escalation of commitment (we do not know when to quit)
3. Confirmation bias (we seek out information that supports our pre-existing beliefs)

What is Wrong the Intuition (Part 3)

We are overconfident in our ability to make decisions. This overconfidence increases with experience.

Ex-

We think we are good lie detectors. But our average accuracy rate, where 50% would be chance, is

1. 44%
2. 54%
3. 64%
4. 74%

What is Wrong with Intuition? (Part 4)

Human intuition does not improve over time.

We think we learn from experience, but we rarely know what would have happened if we had made different decisions.

Ex-

Would our sales have increased if we purchased a different CRM system? We do not know.

What is Wrong with Intuition? (Part 5)

Intuition is unreliable (unreliability is a serious problem)

Two people can examine the same set of facts, and their intuition can lead them to make opposite decisions.

Ex -

Should we hire a job candidate who was president of his college fraternity? Some would say yes, some would say no.