Who This Helps
Hey there, Junior Analyst. You’re staring at a list of potential data fixes, but you’re not sure where to start. This is for you. It’s a quick way to cut through the noise from the Data Reliability Leadership course and focus your effort where it matters most.
Mini Case
Mei, a data lead, had 14 potential reliability issues on her list. She scored each one on two simple factors: how often it broke (frequency) and how many people complained when it did (impact). One metric, the daily active user (DAU) count, scored a 9 out of 10. It broke 3 times last month, and each time, 5 different teams were blocked. She made that her top priority.
Do This Now (5 Steps)
- Grab your list of known data issues or shaky metrics. If you don’t have one, write down the top 3 metrics you report on.
- For each item, give it two scores from 1 (low) to 5 (high). First, how often does it fail or cause confusion? Second, how many people or decisions are impacted when it’s wrong?
- Add the two scores together. The item with the highest total is your winner. That’s your next experiment.
- Now, define a contract for that winning metric. Borrow from the Data Reliability Leadership mission: write down its exact source, calculation, and who owns it. Keep it to one sentence per part.
- Share that simple contract with one stakeholder who uses the metric. Just say, “Hey, aligning on how we define [Metric X] – does this match your understanding?”
Avoid These Traps
- Don’t try to boil the ocean. Picking one thing is a win. You can’t fix all 14 issues at once.
- Don’t get lost in perfect scoring. Your 3s and 5s are good enough. The goal is direction, not precision.
- Don’t skip the stakeholder chat. The contract is useless if it only lives in your head. A quick sync prevents future definition drift.
- Avoid prioritizing what’s easiest to fix. A low-impact, easy win is still a low-impact win. Focus on the high scores.
- Don’t forget the human element. That ‘impact’ score is about people being blocked or making bad calls.
Your Win by Friday
By the end of the week, you’ll have one clearly prioritized experiment. You’ll have a basic contract for your most problematic metric, stopping those definition debates before they start. You’ll ship a cleaner analysis because you’re building on a solid foundation. And you’ll look like a pro who focuses on what moves the needle. Go nail it.