How do you handle data quality and consistency issues in rolling forecasts?
Rolling forecasts are a powerful tool for agile and adaptive planning, but they also require careful data management to ensure accuracy and consistency. Data quality and consistency issues can undermine the credibility and usefulness of your forecasts, leading to poor decisions and missed opportunities. How do you handle these challenges and ensure that your rolling forecasts are reliable and aligned with your strategic goals? Here are some tips and best practices to follow.