To paraphrase Winston Churchill, if you don’t learn from history,
you’re doomed to repeat it. That may sound a bit apocalyptic, but
here’s the point: To make well-informed, well-judged decisions, you
need historical context. That’s why we get better at doing things over
time. Expertise doesn’t just instantly happen—it’s a combination of
intelligence and experience.
What’s this got to do with IT Operations Management (ITOM) and IT
Service Management (ITSM)? It’s one of the main reasons they belong
together. ITSM provides historical operational context for IT
operations. It’s a rich treasure trove of information that you can
mine and analyze to fix service issues faster and more
accurately—learning from previous successes and avoiding past mistakes.
Here’s a simple example—changes. Changes are one of the most common
reasons for service issues, and recent changes are probably one of the
first things you look at when you’re trying to diagnose an outage.
And, of course, changes straddle ITOM and ITSM. Discovery in ITOM
gives you visibility of actual changes, while change management in
ITSM shows you the associated change process.
Put the two together and now you know who, what, where, when, and
why. That’s crucial information when you’re trying to restore a
mission-critical service. And, it’s why we’ve integrated change
information directly into ServiceNow Event Management.
If you know which configuration items (CIs) are affected by an
outage, it’s easy to retrieve recent changes to the same CIs, provided
you have ITOM and ITSM on the same platform. But think about those
true “eureka!” moments when you remember a similar incident that
happened somewhere else in your IT environment. Now you’ve got a
potential shortcut to fixing the current issue, complete with root
cause and remediation steps.
Unfortunately, making these associations isn’t just a simple
database query on specific CIs. It takes significant brainpower and a
phenomenal memory.
The case for AIOps
That’s the problem. With
digitalization and the cloud, IT environments are becoming too vast,
dynamic, and complex for any one person to have that level of
knowledge. There’s no way to keep up with the sheer amount of
historical operational information—let alone correlate it in real time
when your e-commerce portal is down and everyone is screaming. Sure,
historical ITSM data may hold the answer, but that’s no use if you
spend days looking for the proverbial needle in a haystack.
Which brings me to AIOps. AIOps isn’t just about applying machine
learning to monitoring data, although that’s incredibly important.
It’s also about delivering continuous operational insights—analyzing
ITSM data to provide targeted, actionable information when and where
you need it.
Imagine if you could get a real-time list of similar incidents and
problems whenever you have a service issue, along with relevant
knowledge base articles and other information. What would that mean
for your mean time to resolution (MTTR) and for your business?
Augmenting, not replacing, human experience
That’s
exactly what AIOps can deliver, and it’s what we’re already building
into ServiceNow.
Here’s the best part: AIOps isn’t about replacing human intelligence
and experience. It’s about augmenting it—working hand-in-hand with you
to resolve service issues. AIOps (and machine learning in general) is
great at analyzing vast amounts of data to pinpoint correlations,
whether that’s identifying potentially similar incidents or
correlating alerts. And it does it in real time.
Humans, on the other hand, are great at critical assessment and
decision-making involving small data sets—for example, deciding
whether a similar incident or specific knowledge base article
highlighted by AIOps is actually relevant. It’s a match made in
heaven, with machines and humans each doing what they do best.
The result? Improved service quality, less service downtime, vastly
increased operational efficiency, and, ultimately, sustainable
business advantage. That’s the reason why ITOM, ITSM, and AIOps belong together.
