Optimization, simulation, and decision frameworks that recommend feasible actions, quantify trade-offs, and surface the value of additional information.
A practical, step-by-step calculator and worksheet to estimate the expected value of additional information, decide whether an analysis or experiment is worth its cost, and prioritize analytics and experiments by net expected decision value and time-to-deliver.
Practical, repeatable recipes for turning forecasts into recommended actions. Includes step‑by‑step problem templates (inventory reorder, routing, staffing), modeling patterns (objectives, variables, constraints, solver options), simulation and sensitivity templates (Monte Carlo, scenario analysis, value of information), and communication templates that make trade‑offs clear for stakeholders.
Concise, runnable recipes for common prescriptive analytics tasks (scheduling, routing, inventory, allocation). Each recipe offers problem framing, required inputs, minimal model or heuristic, evaluation checks, deployment notes, a quick test case, and a short checklist to move from prototype to reliable operation.
A practical, step-by-step template for mapping alternatives, defining uncertain parameters, running simple Monte Carlo or scenario simulations, performing sensitivity analysis, computing expected value, and packaging results for decision discussions.