During almost every ServiceNow implementation, there is a moment where someone says, usually with good intentions, “We’ll optimize this later.”
It comes up when timelines tighten, and the business needs something live by the end of the quarter. The focus shifts, understandably, to getting the core capability in place and making sure it works.
And most of the time, that is the right call. Delivery matters. Momentum matters. Getting value into the hands of users matters. The problem is assuming that optimization will naturally happen on its own once things settle down.
(In my experience, it rarely does.)
Why Optimization Gets Pushed Aside
After go-live, the organization exhales for a week or two. Then the backlog starts to grow. Yes, that quickly.
Users have enhancement requests. Leadership asks for an expanded scope now that they can see what is possible. Another module gets added to the roadmap. A regulatory update shifts focus.
I could go on. Just know that there is always something.
Optimization requires time that feels discretionary. It requires stepping back and asking whether the workflows behave the way they should, whether data structures are still clean, and whether roles and permissions reflect how the organization operates today.
That kind of reflection is difficult to justify when new requests are arriving daily. So, optimization becomes a standing item that never quite makes it to the top of the agenda.
The Cost of Leaving It Undefined
When optimization is not defined as a concrete objective with ownership, it turns into a vague aspiration. Everyone agrees it is important. No one is accountable for it.
Over time, small compromises accumulate. A workflow that was meant to be temporary stays in place. A report that was manually adjusted every month becomes the accepted version of truth. A configuration that worked for the initial rollout is stretched to accommodate new use cases without being redesigned.
The platform continues to function, and value continues to be delivered. Yet there is a growing sense that the system could be easier to operate.
That gap between what the platform is and what it could be tends to widen, not narrow, when there is no structured plan to revisit it.
Optimization is a Discipline
True optimization means defining what good looks like beyond basic functionality. It means setting measurable standards for data quality, performance, and adoption. It means periodically reviewing configuration decisions, considering how the business has evolved.
In short, being good enough never gets companies very far. Optimization is a continuous process because ServiceNow can’t be treated as a “set it and forget it” offering. (With apologies to that guy who sold rotisseries back in the day.)
Most organizations can do this work. The question is whether they have carved out the capacity and governance to do it consistently. In many cases, internal teams are already operating at full speed just maintaining stability and responding to demand.
Expecting them to also lead a structured optimization effort without adjusting responsibilities is optimistic. And, like my father once told me, hope is not a strategy.
Where Managed Services Fits
This is where a mature managed services model can provide real value when it is designed correctly.
Optimization should be embedded into the operating rhythm of the platform. Regular health reviews. Roadmap alignment sessions that look at architecture as well as features. Transparent metrics around performance and usage trends. Clear documentation of why certain design decisions were made and whether they still serve the organization.
CoreXtend was shaped around this idea. The goal is move beyond “keeping the lights on” to create space for thoughtful improvement while the business continues to move.
That structure makes it much more likely that optimization happens, because it is planned, owned, and measured rather than deferred.
A More Honest Question
If you look at your current ServiceNow environment, it is worth asking a simple question: If nothing changed in your operating model over the next 12 months, would the platform become cleaner and more efficient, or would it gradually become more complex?
The answer to that question usually tells you whether “we’ll optimize later” is a realistic expectation or just a comforting phrase. And committing to iterative reviews usually eliminates the panic about optimization.
Optimization does not require a massive reinvention. It requires commitment and clarity around responsibility. When that structure exists, improvement becomes steady and manageable. When it does not, the platform drifts, even when everyone involved is talented and well-intentioned.
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