It's not just data format changes; model accuracy can be impacted by changes in the distributions of values, even if their types remain the same.

That's why production ML systems should monitor for data drift, model accuracy, and a host of other factors that may not be obvious at first. That's part of what TensorFlow Extended does.

See also: "What’s your ML Test Score? A rubric for ML production systems" https://ai.google/research/pubs/pub45742