Build an interactive business forecasting application that lets users reconstruct historical demand and test how different decisions might have changed the outcome.
Users can import sales records, product availability, prices, promotions, holidays, marketing activity, and customer orders. Display demand over time and identify periods where stockouts or missing data may have distorted observed sales.
Let users simulate alternate decisions, such as ordering more inventory, launching a promotion earlier, changing prices, or introducing a replacement product. Compare hypothetical outcomes with the historical record using transparent assumptions.
Include product-level timelines, scenario comparisons, forecast uncertainty ranges, and a list of additional data that would improve the model.
Clearly distinguish actual sales from estimated unmet demand and hypothetical counterfactuals. Do not claim to know what customers would have purchased under a different scenario. Provide editable assumptions, validation metrics, and downloadable analysis reports.
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