Time
3 hours 49 minutes
Difficulty
Beginner
CEU/CPE
3

Video Transcription

00:00
Welcome to the idol framework. Updated course from Cyber Eri i d.
00:05
My name is Daniel Riley. I'm your subject matter expert on the idol framework.
00:10
In this video, we're gonna talk about the service operation phase key performance indicators.
00:18
Now, this is kind of Ah, short. One more only gonna talk about two of the processes from the service operation phase. The 1st 1 of those is the incident management phase. And in that we're going to keep account of the incidents that we've detected.
00:36
And we're going to keep an overall count as well as divided out
00:41
by each incident, type or category. Eso if it's, ah, warning or something of that nature.
00:50
Oh,
00:51
and then we're gonna keep a count of those incidents that we've actually been able to resolve.
00:58
Ah, and with the ones that we've, uh, got reports on, we're going to take a measurement of our time to first response, and then we're going to some of all of those up and divide across the number of incidents that we've detected
01:15
on that will give us our mean first response time. And this really is a way of
01:19
describing are monitoring how quick it was
01:25
we are able to triage
01:27
on incident. In our environment,
01:32
we're going to keep a percentage of the first tribe resolutions. These are incidents that were able to be resolved by the help desk or by the first year, support people.
01:42
We're gonna find this by taking the count of incidents that we were able to resolve in that first year on. We're going to divide it with the total incidents that we've got.
01:56
Ah, and this is also one that could be broken out across the different incident categories. And that's going to be true for most of these incident management KP eyes.
02:07
And we're gonna want to keep account of the detected incidents which we've had to escalate. And we might have to escalate due to technical difficulties in the tier one not being able to complete the task or just because of our time constraints. A lot of
02:28
Tier one support
02:29
has to be completed within a certain amount of time, and if that time had lapses, then they have toe automatically escalate it to the next year.
02:42
We're going to keep account of the incidents that we've been able to resolve within our service level agreements on. Then we can also find a percentage of the resolved service level agreements. Basically, by taking the count of the incidents over the total
03:01
account
03:02
or the count of incidents that have been resolved within the S L a time over the count of total incidences.
03:14
So we're gonna take the mean incident resolution time, which is the time from reporting oven incident up until we are satisfied with our resolution of it that the amount of time that that takes were going to some all of those up for each instance.
03:32
And again, we're gonna divide it
03:35
by the number of incidents that we've been able to resolve
03:39
for the mean incident resolution labor. This is similar.
03:46
You'll also hear this called effort Sometimes, however, I don't like that. I think effort is kind of a subjective term, whereas thesame of the dollar amount spent two to acquire some amount of labor. That's that's objective
04:03
s. So we're going to take this some of our dollar amounts of labor
04:08
that we've spent resolving incidents and then we're going to divide that across the number of incidents that we have had. And again, this is one of those where you're gonna want to get a more detailed view by splitting it out and figuring out how much labor you're spending on critical
04:27
vs
04:29
warning type incidents
04:32
Now under the problem management KP eyes. The 1st 1 we're going to talk about is the count of problems registered to our problem management group.
04:42
Um, and if you were called from our discussion of the processes, incidents that we weren't able to find an adequate resolution for can be escalated up to the problem management.
04:56
Now we're going to keep account of the outstanding problems. Those are those problems which we still don't have a rib
05:05
of resolution forth.
05:08
So we're going to keep account of the time before problem identification. This is the amount of time that we can determine a problem existed before we were made aware of the problem. Obviously, we're gonna have to figure this out retroactively because we can't
05:26
start measuring time before we're aware
05:30
of something.
05:31
We're gonna keep a meantime that the problems are open on. And to do that, we're going to keep a count of each time that a problem has been open. We're going to some all those times on we're gonna divide by the number of problems that we still have opened,
05:51
and then we're going to keep account of the incidents per problem. Um, since a problem might be an instant that doesn't have a resolution, we're going to keep a number account of the number of times that an incident occurs
06:10
under that problem. And there might be several incidences related
06:15
to a single problem.
06:17
We're going to keep a mean number of the incidents, which is the sum of all of those counts of the incidents divided by the number of problems that we've been able to solve.
06:33
With that, we've come to the end of this video. I'd like to thank you for watching. And as always, if you have any questions, you can contact me on cyber harry dot i t my user name ist warder. T w a r T e r

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