For causation, you need A/B testing -- real A/B testing (randomized controlled experiments). Not everyone understands the need for A/B testing and not everyone

For causation, you need A/B testing -- real A/B testing (randomized controlled experiments). Not everyone understands the need for A/B testing and not everyone understands how to do A/B testing. I recently worked on modeling to forecast revenues for a large multinational. One of the variables that was essential for an accurate model was whether prior data came from before or after the company hired their current A/B testing guru. With the new guru, revenues rose every week. With the previous "guru", changes by Engineering had no impact on revenues.