The 7 cognitive biases sabotaging your decisions every day

The human brain doesn't work like a calculator. It works like a survival system designed to save energy. To do this, it uses shortcuts — cognitive biases — that work in most everyday situations but produce systematic errors in important decisions.

1. Anchoring effect

The first piece of information you receive about a topic becomes the reference point for everything else. If you see a house at 500,000 euros then one at 350,000, the second seems like a bargain — even if it's worth 250,000. The anchor distorts judgment without you noticing.

2. Loss aversion

Losing 100 euros hurts more than gaining 100 euros feels good. This imbalance leads you to avoid reasonable risks and to cling to situations that are costing you, just to avoid "realizing" the loss.

3. Confirmation bias

You seek information that confirms what you've already decided. You ignore contrary signals. You interpret ambiguous data in your favor. The result: decisions that seem informed but are merely reassured.

4. Dunning-Kruger effect

The less you know about a subject, the more confident you are that you know enough. This leads you to underestimate the complexity of decisions in areas where you have little experience — often precisely where the risk is greatest.

5. Status quo bias

Change requires energy and risk. Not changing seems safe. But as we've seen discussing slow damage, the status quo isn't neutral: it has a cost that grows over time.

6. Framing effect

The same information, presented differently, produces different decisions. "This procedure has a 90% success rate" sounds very different from "this procedure fails in 10% of cases." Same data, opposite emotional reaction.

7. Sunk cost fallacy

"I've already invested too much to quit now." This sentence has caused more damage than market crashes. The money, time, and energy already spent won't come back. The right question isn't "how much have I invested?" but "does this decision still make sense going forward?".

How DAMM neutralizes biases

The DAMM framework doesn't eliminate biases — no tool can do that completely. But the Delimitation-Asymmetry-Margin-Minimum Move sequence creates mandatory stop points where biases get exposed. Delimitation forces you to look at real losses (neutralizes anchoring). Asymmetry forces you to compare gain and loss on the same scale (neutralizes framing). Margin shows you the real cost of the status quo.