Automation in Enterprise Operations

Putting Capability Where Knowledge Lives

Automation in Enterprise Operations: Putting Capability Where Knowledge Lives

There is a pattern we have seen repeat itself across enterprise operations teams, in organizations large and small, across industries and across the region.

A senior network operations engineer has spent years managing incidents. She knows every symptom, every pattern, every exception. When a specific combination of alerts appears at two in the morning, she knows exactly what it means and exactly what needs to happen — before the system has finished correlating the events.

When her organization decides to automate that knowledge, what happens? A requirements document is written. A developer translates it. A workflow is built. Weeks later, it handles the predictable cases. Everything else still needs her.

The knowledge stayed in her head. The automation missed the point.

The Automation Ownership Problem

For decades, automation in IT operations has lived in one place: the development team. There is a practical reason for this. Building automation has historically meant writing scripts, understanding system architectures, and managing complex dependencies across platforms. The work demanded technical expertise that most operations professionals were never trained for.

But this arrangement creates a deep structural problem. The people who understand the operations — who have seen every failure mode, who carry years of institutional knowledge about what to do when — are not the people building the automation.

What the operations engineer knows instinctively never fully makes it into the requirements document. Edge cases that seem obvious to her are almost impossible to document completely. The judgment built over years of pattern recognition gets reduced to a simplified workflow that covers the standard path and breaks the moment anything deviates.

We have heard this from operations leaders across our region. One head of IT operations at a large financial institution put it plainly: there are far more operations team members than automation developers. Why do we keep asking developers to automate what operations already understands?

Why Low-Code and No-Code Did Not Solve This?

The industry recognized the problem early. The response was low-code and no-code platforms — reduce the technical barrier, make automation accessible to the people who actually understand the processes. It was the right instinct. But the execution fell short.

Low-code solutions reduced complexity without eliminating technical thinking. Operations teams could go further than before, but they still hit walls when workflows became sophisticated. No-code alternatives simplified the interface by limiting capability — adequate for routine tasks, inadequate for the complex operational scenarios that actually matter.