Use Case
Delivery Forecasting
When will this actually ship?
The Problem
Stakeholders want delivery dates, but engineering gives ranges that executives do not trust and PMs give single-point estimates that are wrong. Without probabilistic modeling, every date is either aspirational or sandbagged.
How CohesionXL Helps
CohesionXL runs Monte Carlo simulations against your scope breakdown and capacity data to produce probability-weighted delivery forecasts. P50 for likely, P85 for committed, P95 for worst-case. A data quality score tells you how much to trust the forecast, so you can invest in improving inputs where it matters most.
Outcome
Delivery dates with confidence intervals that stakeholders understand and engineering trusts.
Key Features Used
Forecasting
Monte Carlo simulations with P10–P95 confidence intervals, scope-based and empirical modes.
Capacity & Resource Management
Employee skills, availability calendars, PTO tracking, utilization dashboards, and auto-allocate.
Initiative Management
Structured lifecycle from intake to delivery with health tracking, CSV import/export, and bulk operations.
Scenario Planning
What-if modeling with drag-and-drop priority ranking, allocation management, and scenario comparison.
Ready to solve this for your team?
See how CohesionXL addresses your specific planning challenges.