Structuring data for executive impact

Read recently: 65% of execs ignore analyses because they didn't fit their intuition. This is huge.

Confirmation bias is powerful. And humans struggle with probabilistic thinking. If presented with mixed evidence, we will force it into clear categories. We have a bias towards binary conclusions. With complex data, we default to black and white interpretations. We treat probabilities as absolutes (60% = it will succeed). We then ignore contradictory but important details.

We will also favor the quantity of judgements over the strength of any single judgement. We prioritize consensus over evidence quality.

This all matters because execs rely on data to make decisions, but biases distort how we interpret it. And together, these two biases reinforce each other: if I already believe in a certain strategy, I may also demand a clear-cut yes or no answer from the data, even when the reality is more complex.

For storytellers, this means presenting a detailed, evidence-based story that makes complex ideas easy to understand without oversimplifying. It also involves encouraging decision-makers to consider different viewpoints.

Remember: people will instinctively seek data that validates their expectations. To counter this, highlight anomalies, trends that challenge assumptions, or alternative interpretations. And to combat black and white thinking, use confidence intervals, trend gradients, and probabilistic forecasting (vs. pass/fail).

Intentionally structuring how data is displayed and interacted with shapes better decision-making and ultimately, increases impact and influence.