Scenario Analysis vs. Predictions
Making predictions is currently in vogue yet most real world futures are unpredictable. Human behavior, social life, biology, government and business occur in high causal density environments. Complex pathogens like COVID19 are unpredictable yet both trained epidemiologists and amateurs attempt to predict and advocate policies to achieve vague goals. They mostly fail and look foolish.
Professional data scientists NEVER make predictions. The professional employs high quality descriptive and real time data, critical thinking, logic, historical precedent, evidence and probability theory to analyze a number of potential scenarios and weigh probabilities along with balance of upside and downside risks.
Professional data scientists explain to the client/employer likely scenarios and help plan to navigate using real time data to achieve specific goals. Using high quality real time data to calibrate tactics and strategy in near real time, in complex, fluid environments, creates a higher probability of achieving those goals.
I suggest a pragmatic concept of scenario analysis and planning, and near real time calibration using high quality data and probability theory, is optimal strategy and more valuable than making speculative predictions.