Crystal Ball PM · delivery forecasting
Software delivery estimation framework using historical completion data
Hallway estimates collapse because they hide distribution and scope fuzz. This workspace refines scope, pulls ranges from Jira history or offline modeling, and drafts tickets you can hand to engineering—so “two days” has to defend itself against data.
History beats heroics
Weighted averages from similar done work anchor optimism. When history is missing, the model still returns an explicit range with confidence you can debate.
Enterprise readiness without theater
Pair estimates with the Predictive Delivery Tracker and governance cadence from advisory when your bottleneck is system-wide, not a single ticket.