Week 1 · The Bullseye
Nobody trusts the number
Find the real problem before you touch a query.
The brief
Monday, 9:05. Your laptop is still provisioning when Dana Whitfield walks into the room without knocking.
"The dashboard says our conversion rate is 61%. It is not 61%. My reps would be swimming in commission. Can you make it right by Friday?"
Ten minutes later Raj Patel messages you: "Heads up, Dana thinks the numbers are wrong. All three pipelines have been green for months. Happy to walk you through them." Lena Fischer from RevOps adds you to a channel called #crm-hygiene with no explanation.
This is the moment the Four Key Shifts become real. A general PM would ship a fix. A Data PM asks: which number, defined how, trusted by whom, used for what decision?
Your job this week is discovery, not SQL. Meet the people, map how they use data today, and pin down the North Star, functional, and granular metrics for a Sales domain. The warm-up exercises let you touch the data so you know what exists, but the real deliverable is a problem statement Dana and Sofia both sign.
Lessons
Read
What is a Data Product Manager?
A DPM sits at the intersection of data, technology, and business, managing data warehouses, platforms, pipelines, and ML models the way a PM manages a product.
The Four Key Shifts (Data PM vs. General PM)
Risk profile, success metrics, customer journey, and team dynamic all invert when you move from general PM to data PM.
The Bullseye: Data Product-Market Fit (Week 1)
Before building anything: retrieve requirements from real end users, map their existing journey, and identify North Star/functional/granular metrics.
North Star, Functional, and Granular Metrics
North Star = the domain's leading business metric. Functional = the leading metric for a sub-area. Granular = an indicator of effectiveness.
Data Product Journey: Four Maturity Stages
Most orgs sit in Ad-hoc or Reactive. The goal is Purpose-Driven: initiatives measured by clear North Star, functional, and granular metrics.