reference-class-forecaster

# Reference Class Forecaster ## Overview The Reference Class Forecaster skill implements reference class forecasting methodology to counter optimism bias and the planning fallacy. It uses historical data from comparable projects or decisions to generate empirically-grounded forecasts, providing an "outside view" to complement internal estimates. ## Capabilities - Reference class selection and validation - Distribution fitting from historical data - Adjustment factor calculation - Uncertainty quantification - Bias correction for planning fallacy - Documentation of reference class rationale - Comparison with inside view estimates - Reconciliation guidance ## Used By Processes - Cognitive Bias Debiasing Process - Decision Quality Assessment - Strategic Scenario Development ## Usage ### Reference Class Definition ```python # Define reference class reference_class = { "name": "Enterprise Software Implementations", "description": "Large-scale ERP implementations in manufacturing companies", "criteria": { "project_type": "ERP implementation", "industry": "manufacturing", "company_size": {"min": 1000, "max": 10000, "metric": "employees"}, "project_budget": {"min": 5000000, "max": 20000000}, "time_period": {"start": "2015", "end": "2023"} }, "sample_size": 47, "data_source": "industry_benchmark_database" } ``` ### Historical Data ```python # Reference class outcomes historical_outcomes = { "cost_overrun": {...