TAE recommends controlled change management to isolate causes when multiple changes are introduced. When you apply more than one change at once, diagnosing failures becomes harder because you cannot easily attribute effects to a specific change. The best practice is to implement changes incrementally, validating automation and system behavior after each change using a representative subset of tests (e.g., smoke/build verification or targeted regression) to quickly detect issues. Because the system is business-critical, risk mitigation is stronger: you want early detection and clear attribution. After each change is validated with a subset, you then execute the full updated regression suite to ensure overall coverage and confidence. Options A and C apply two changes before running tests, which reduces diagnostic clarity and increases the risk of late discovery. Option D describes incremental changes with subset testing but omits the final full-suite run, which TAE would recommend to ensure broad coverage after all changes have been applied. Therefore, the best sequence is: change one item, run a subset, repeat for the next change, then run all updated scripts.