Answer
A concrete signal to watch for is how often someone has to intervene manually to keep an overnight or batch cycle moving, whether that means restarting a job after a file arrives late, manually checking whether an FTP transfer completed before releasing a downstream job, or calling a colleague at home because a scheduled job failed silently. Native IBM i scheduling handles time-based and simple sequential triggers well, but it was never designed to evaluate conditions like file existence, API response codes, or cross-platform job status, which is exactly where growing integration complexity tends to expose it.
The other signal worth taking seriously is documentation risk: if the true dependency chain for a critical nightly cycle exists mainly in one or two people's heads rather than in a system that enforces and displays it, the organization has already outgrown native scheduling, even if nothing has broken yet. Buyers evaluating workload automation should look for real dependency modeling across IBM i and non-IBM i systems, built-in exception handling that can retry, reroute, or alert based on defined rules, and an audit trail that shows exactly what ran, when, and why, since that visibility is usually the actual return on the investment, not just fewer manual restarts.