How have you empowered your PMs to be their own analyst? Any tips for getting PMs up to speed on running their own queries?

I do not expect PMs to be analysts, but I do expect them to be data fluent. They should be able to self-serve, interpret results, and use data to make confident product decisions without always relying on a data scientist. At Atlassian, PMs are expected to be comfortable using analytics dashboards, building Amplitude charts, running experiments, and conducting pre- and post-analysis. When deeper statistical or modelling work is needed, they collaborate with data scientists, but the day-to-day pr ...Read More

“Data depth” is a core competency for any PM and unlocks “data informed’ strategy.  However, how much data analysis a PM will need to do will depend on the maturity of the organization & available resourcing. At the core, every PM must know where the data is logged and in what format. In organizations, where there is an organization wide data platform that democratizes data access & there are analysts on the teams, every PM should still be trained on using this platform and run lightweig ...Read More

5 steps to go from data curious to data confident Ask before you analyze – Define the hypothesis and success metric clearly. Start small – Use prebuilt dashboards before jumping into SQL. Validate often – Cross-check your findings with a peer or analyst. Document everything – Save queries and insights in a shared library. Tell the story – Translate numbers into narratives that drive action. Empowering PMs to be their own analysts accelerates decision-making and strengthens product intuition. The ...Read More

I would strongly recommend the below approach: Proactive: in their product requirements document, PMs need to clearly lay out the success metrics and hypotheses to test, and work with engineering to implement product tagging that will allow them to compute these metrics and in/validate the hypotheses Reactive: first, start by leveraging central data teams: ask them clear questions and have them get back to you with reasonable SLAs If there is no central data team or if the SLAs are too long, inv ...Read More