Explore the Principles
Segment Before You Aggregate
Don't rely on totals or averages alone—break your data down by relevant subgroups to uncover hidden insights.
Smooth the Noise, Reveal the Signal
When data fluctuates rapidly, use smoothing techniques like rolling averages to make patterns clearer.
Ask What 'Good' Looks Like
Don't just chart what happened—compare it to what should happen with benchmarks, goals, or standards.
Treat Variability as a Signal
Don't hide variation behind averages—differences often reveal valuable patterns or inconsistencies.
Contextual Events Matter
Data doesn't exist in a vacuum—major events can shift patterns in ways the chart alone won't explain.
Outliers Deserve Attention
Outliers may represent important signals—extreme success, failure, or exception cases worth investigating.
Comparisons Are More Powerful
A single number means little without something to compare it to—comparative framing adds meaning.
Don't Assume Aggregates Tell the Whole Story
Averages and totals can be misleading—they flatten the data and hide important differences.
Watch for Confounding Variables
When two things appear related, a third factor might be influencing both—correlation isn't causation.