What it means

When facts and measurements conflict with beliefs, the facts win. Data are observations you can verify. Opinions are interpretations that may be useful, but they must bend to what reality shows.

Why it works

• Reality is consistent
  Careful measurements anchor choices to how the world actually behaves.
• Prediction beats persuasion
  Data let you forecast outcomes. Opinion only argues.
• Bias gets corrected
  Numbers expose blind spots that stories can hide.
• Repeatability builds trust
  If others can get the same result, the explanation is more likely true.

How to apply it

1. Define the question clearly
   Write a testable question with a measurable outcome. Example: Will a 20 minute walk after dinner improve my sleep quality within 2 weeks
2. Choose the metric
   Pick a simple measure that reflects success. Examples: hours slept, heart rate, time to task completion, cost per meal.
3. Collect a baseline
   Measure before you change anything so you know your starting point.
4. Run a small test
   Change one thing, keep the rest stable, and track the metric for a set time window.
5. Compare against the baseline
   Look for size and direction of change, plus variability. Graph if possible.
6. Decide by rule
   Write the decision rule in advance. Example: If average sleep increases by 30 minutes or more, keep the walk for another month.
7. Log and iterate
   Record what you tried, what the data showed, and your next step.

Everyday life examples

Health and fitness

• Strength
  You believe high reps are best. You test 8 weeks of low reps, log weight lifted and progress. The low rep cycle adds more total strength. Keep what works.
• Nutrition
  Friend says late eating ruins sleep. You track meal timing and sleep score for 21 days. Data show no effect for you. Drop the rule.

Money and work

• Budgeting
  You feel groceries are the problem. A 30 day expense log shows takeout is twice the grocery spend. Redirect effort to home cooking and see the next month’s totals fall.
• Productivity
  You think multitasking saves time. Time tracking shows tasks take longer with more context switches. You adopt 60 minute focus blocks and watch cycle time shrink.

Home and routines

• Thermostat setting
  Room “feels” fine at 23°C. Energy bills and a thermometer show large cost for a tiny comfort gain. You lower to 21°C and track comfort plus savings.
• Cleaning products
  A popular spray seems strongest. A simple stain test on scrap fabric shows a cheaper product works better. You switch.

Learning and skill building

• Guitar practice
  Opinion says longer sessions are better. A month of 20 minute daily sessions vs a month of weekly marathons shows more songs learned with the daily plan.
• Language study
  You assume flashcards are enough. A weekly speaking log shows conversation minutes correlate with fluency gains. You add two short speaking calls per week.

Relationships and communication

• Conflict repair
  You believe long talks fix everything. After tracking outcomes, quick check-ins plus a written summary resolve issues faster. Keep the brief format.
• Team meetings
  Opinion says more meetings create alignment. Shipping metrics and survey data show fewer, clearer meetings raise output. You remove one standing meeting and recheck.

Good vs bad practice

Good

• Start with a clear question and metric
• Track before and after
• Keep tests small and time bound
• Share raw numbers or a simple chart
• Change your mind when the data say so

Bad

• Cherry pick only supportive numbers
• Change goals after seeing results
• Measure too many things at once
• Rely on “it felt better” when a measure exists
• Treat one anecdote as proof

Common pitfalls and fixes

• Small samples
  Early swings can mislead. Fix: extend the test window or increase the sample size.
• Confounders
  More than one thing changed. Fix: change one variable per test.
• No baseline
  You cannot tell if anything improved. Fix: measure a week before starting.
• Vanity metrics
  Tracking what is easy, not what matters. Fix: pick outcomes tied to real goals.

Simple tools that help

• Notebook or notes app for a decision log
• Spreadsheet for totals and averages
• Kitchen scale, thermometer, timer, pedometer
• Calendar reminders to start and stop tests

A 7 day starter experiment

• Day 1: pick one area and define the question and metric
• Days 2 to 3: collect baseline
• Days 4 to 6: run one change
• Day 7: compare, decide, and log the next step

Closing

Opinions can inspire, but data decide. When you ask clear questions, measure what matters, and let results lead, you get better predictions, less drama, and steady progress in health, work, and life.