What we are trying to do is reach theoretical saturation, the point where additional research doesn’t give us new insights.

The image pictures it well: https://swipefile.com/from-data-to-impact and creates a consistent pattern.

A exercice of thought:
Raw data points is random and inconclusive. Information makes them consistent. Knowledge (or Findings) describe emerging patterns in data but aren't actionable. Insights reveal opportunities in this knowledge. Wisdom emerges from insights. Impact is reached while taking action with these insights and wisdom.

Hindsights are reflections of past actions and outcomes.
Foresights are informed projections, insights with extrapolation.

Here’s what it then looks like in real life:
Data ↓
Six users were looking for ”Money transfer” in “Payments”, and 4 users discovered the feature in their personal dashboard.
Finding ↓
60% of users struggled to find the “Money transfer” feature on a dashboard, often confusing it with the “Payments” section.
Insight ↓
Navigation doesn’t match users’ mental models for money transfers, causing confusion and delays. We recommend renaming sections or reorganizing the dashboard to prioritize “Transfer Money”. It could make task completion more intuitive and efficient.
Hindsight ↓
After renaming the section to “Transfer Money” and moving it to the main dashboard, task success increased by 12%. User confusion dropped in follow-up tests. It proved to be an effective solution.
Foresight ↓
As our financial products become more complex, users will expect simpler task-oriented navigation (e.g., “Send Money”, “Pay Bills“) instead of categories like “Payments”. We should evolve the dashboard towards action-driven IA to meet user expectation.