Data-driven goal setting vs. confirmation bias

Start with insights. Real data-driven teams begin with accessible data to uncover bottlenecks before defining objectives, ensuring that goals reflect actual performance gaps (David Pereira from Untrapping Product Teams). This approach prioritizes identifying where a team is bleeding value, such as high churn rates or poor onboarding success, to establish targets that address the primary blockers to growth (David Pereira from Untrapping Product Teams).

Avoid confirmation bias. Many executives adopt the opposite strategy by setting goals first and then using data to validate their pre-existing ideas, a practice David Pereira labels as the data illusion. This top-down process often results in teams building features demanded by boards or leadership that customers ignore because the underlying metrics never supported the initiative in the first place.

Aligning strategy. The conflict between these approaches highlights a fundamental tension in organizational management where leaders must choose between pursuing prescriptive outputs to satisfy investors and conducting rigorous analysis to drive genuine impact. While the former provides immediate clarity for boards, the latter remains the only path to identifying the most relevant opportunities for long-term success.