A mayor asks when 100% of citizen requests will be online, but request types still vary widely and discovery is incomplete. How should the Product Owner reframe the forecast?
Select an answer to reveal the explanation.
Short Explanation
One hundred percent of every citizen request is a horizon, not a release. Pick a slice that actually helps people — say, the top request types — and forecast the next Increment that proves it. Completeness myths make great speeches and terrible go-live dates.
Full Explanation
Advanced Product Ownership forecasts toward valuable outcomes and Product Goals, not exhaustive completeness that discovery has not even bounded. When a mayor asks when 100% of citizen requests will be online while request types still vary widely, the Product Owner should reframe to a valuable Product Goal slice and forecast the next validated Increment that proves meaningful online coverage. Quoting a date for total coverage so the mayor can announce complete digital transformation converts an unbounded horizon into a political promise the backlog cannot yet support. Waiting until every request type is documented before offering any forecast withholds useful empiricism the city could already use from a thin vertical of high-demand types. Converting the 100% target into a year-long Gantt of request types and committing each month's bar recreates the completeness myth in chart form. Exam caveat: PSPO II rewards slicing for value and inspecting learning; completeness can remain a later hypothesis without being the near-term forecast. Operational check: name the top request types by citizen volume or harm reduction, forecast the Increment that delivers those types Done, and schedule a Sprint Review checkpoint before any speech implies citywide coverage.