Amazon’s official model card introduces that Chronos-2 supports univariate, multivariate, and time series forecasting with covariates. This article discusses methods, does not conduct independent backtesting, and does not claim the model to be a universal answer capable of predicting any business changes.
First fix the information that can be known at that time
To simulate and predict sales for next week, you can only use the historical data and determined arrangements that are already available at the time of prediction. The actual promotion results for next week, back-up orders or subsequent corrections cannot be input in advance, otherwise the evaluation will overestimate the effect.
Use the same time window as the simple baseline
You can compare the model results with simple methods such as the previous cycle and historical average, and record the difference in errors during off-peak seasons and out-of-stock periods. Low sales due to stockouts do not necessarily represent a drop in demand, and input instructions should retain this business context.
Forecasting is only a basis for replenishment decisions
The procurement cycle, minimum order quantity, inventory space and funding arrangements still require judgment by business personnel. The output should retain the forecast time, input version and uncertainty range, and should not automatically trigger irreversible procurement. This article is intended for testing purposes only and does not provide financial forecasts or promises of operating results.
Extended reading: AI model.