Who This Helps
You're a Junior Analyst. You have data, but you're not sure which experiment to run next. You want to ship clean analysis with clear recommendations. The Data Reliability Leadership course shows you how to build trust in your numbers so your recommendations stick.
Mini Case
Mei, a Junior Analyst at a fast-growing startup, had three experiment ideas. She used a simple prioritization framework from the course. She scored each idea on impact (1-10) and effort (1-10). The first idea scored 8 impact, 3 effort. The second scored 6 impact, 7 effort. The third scored 4 impact, 2 effort. Mei picked the first one. She ran the experiment in 7 days. Her recommendation was clear. The team loved it. Her win? A 12% lift in user retention.
Do This Now (5 Steps)
- List your next three experiment ideas. Write them down. No judgment yet.
- Score each on impact. Ask: If this works, how much does it move the needle? Use a scale of 1 to 10.
- Score each on effort. Ask: How many hours, people, or resources does this need? Again, 1 to 10.
- Divide impact by effort. The highest number is your priority. That's your highest-impact move.
- Write one clear recommendation. One sentence. Example: "Run experiment A because it has the highest impact-to-effort ratio."
Avoid These Traps
- Picking the fun idea first. Fun doesn't equal impact. Use the score, not your gut.
- Overthinking the scores. A rough 1-10 is fine. Don't spend an hour on one score.
- Skipping the recommendation. Analysis without a recommendation is just noise. Ship it with a clear next step.
Your Win by Friday
By Friday, you'll have one experiment prioritized and one recommendation ready to share. Your team will see you as the analyst who ships clean, actionable work. That's a win. And hey, you might even get a high-five from your manager.