How do you debug a forecasting model today when the error is quite bad?

This is for a personal study that will end up becoming an in-depth article and possibly a fully open source solution ideally without the AI slop that we see these days. Let's say you’ve trained a model and the result is worse than the business wants. What do you check next? Do you break the error down by customer, product, location, or individual series? Check if it gets worse at longer horizons? Look for bias, volatility, intermittent demand or outliers? Go back to the backtesting setup, metric, or baseline? Or do you usually start trying other models? Also do the tools you use make this easy