Quantify delivery risk before you commit the roadmap
Software projects overrun budgets and miss scope at high rates. Incertive models the uncertainty in your plan and returns a success probability, the risks that most threaten delivery, and where to focus to improve your odds.
of software projects fully succeed (on time, on budget, full scope); ~31% are cancelled outright
Source: Standish Group, CHAOS Reportaverage final cost vs. the original estimate on challenged and failed software projects
Source: Standish Group, CHAOS ReportWhat Incertive quantifies for these projects
Scope and requirements volatility
Undefined or shifting requirements are a leading cause of overruns. Incertive models scope creep as a quantified uncertainty, not a fixed assumption.
Estimation and dependency risk
Optimistic estimates and hidden dependencies compound. A sensitivity analysis ranks which ones most threaten your delivery date.
Integration and third-party risk
Integrations and external APIs are frequent failure points. The analysis quantifies how much they widen the range of outcomes.
Team capacity and ramp
New teams and unfamiliar tech raise failure rates. Incertive shows how capacity assumptions affect your real odds.
A worked example
Platform rebuild with a fixed launch date
A team commits to rebuilding a core platform in nine months with a fixed launch date, partially defined requirements, and two critical third-party integrations.
Takeaway: Undefined requirements and the two integrations drive most of the risk. Firming up the hardest requirements first and de-risking the integrations early lifts the probability of hitting the date without cutting scope.
Illustrative example. Sign up to run a real analysis on your own project.
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