ProductOps

WHAT IT IS ProductOps is the operational function supporting product management: routing customer feedback so it reaches the people making decisions, running the logistics of research, coordinating launches across the functions a launch touches, and governing product analytics instrumentation so the data can answer the questions product managers ask of it. **Not this:** ProductOps is not BizOps: it owns the systems and rituals that let product management work — feedback, research, launch and instrumentation — not the company-wide planning and cross-functional process. WHY IT EXISTS Product managers spend a surprising share of their time on logistics: chasing feedback scattered across support tickets, sales calls and chat; scheduling research; assembling launch checklists; and asking engineers to add an event because the funnel cannot be measured. None of that is product judgment, and all of it scales badly with the number of product managers. ProductOps exists to industrialise the logistics so the judgment has room. WHEN TO USE IT Adopt it at roughly the point where product managers stop being able to keep the whole feedback picture in their heads — commonly around a handful of product teams. Earlier than that it is overhead; later than that the symptoms are obvious, chiefly launches that surprise support and analytics that cannot answer basic questions. WHO OWNS IT A ProductOps function owns the systems, the taxonomy and the rituals. Product managers own the decisions — ProductOps that starts prioritising has replaced the function it supports. Engineering owns implementing instrumentation to an agreed specification. Support, sales and success own feeding the feedback pipeline, which requires that they see something come back or they stop. WHAT GOOD LOOKS LIKE Feedback arrives through defined channels into one place with a shared taxonomy, and contributors can see what happened to it. Research has repeatable logistics — recruitment, consent, scheduling, a searchable repository — so a study is days of setup rather than weeks. Launches follow a tier-appropriate checklist and the functions that need warning get it. Product analytics has a documented event taxonomy, instrumentation is reviewed before release, and the funnel questions can actually be answered. Privacy is handled deliberately, because feedback and research data is personal data — see /privacyops. HOW TO IMPLEMENT Consolidate feedback first: pick one destination, define a coarse taxonomy, and close the loop back to contributors so the pipeline keeps flowing. Write the launch checklist with tiers, since applying full launch ceremony to a minor change trains people to skip it. Document the event taxonomy and put instrumentation review into the release path, which stops the slow decay that makes analytics unanswerable. Build research logistics once the first two are stable. The instrumentation governance overlaps /analyticsops and benefits from the same definition discipline. HOW TO ASSESS YOURSELF Ask where a piece of customer feedback goes and who sees it. Ask whether last month's launch surprised anyone who needed to know. Try to answer a basic funnel question from your product analytics and time it. Take the scored self-assessment at /assess and plan with /roadmaps.