After changing influencer variables and running models for a couple of years, a modeler was informed by a data team that the central bank is planning to stop providing granular data for one of the modeling variables and that the metric would still be published but in an aggregated manner. This may impact the usability of such data for modeling purposes. A change in a variable in a regulatory environment has multiple overheads. In this scenario, the modeler would have to engage with the data team to understand which variable can be used as a substitute. The IT team would then have to ensure that variable (if not already available as a regular feed) is made available to the data team and the modeler. The material impact of the change in the variable on the modeling output would also have to be studied and documented. There might be an instance where a modeling governance team has to be notified of changes in the model. In an ideal governance environment, if code changes are to accommodate a new variable, testing would be undertaken before any change is implemented. A simple change in variable granularity can trigger the need for multiple subsequent tasks.