Performance Analytics for Incidents

Community Alums · ‎10-07-2016

Hello, How are you using Performance Analytics for Incidents? PS. What's the difference (technical view) between Performance Analystics and normal Reporting module available OOTB?

Chuck Tomasi · ‎10-07-2016

Hi Rafael,

Most customers are using PA for incident management with OOB indicators to determine where they can improve the process. Some have gone further and added additional leading and lagging indicators for additional information. For example, how many times has an incident been escalated from L1 support to L2 support over the last month? Is this trend increasing or decreasing? Once you know that, you can start to look at root causes like staff turnover, training, new technologies implemented, etc.

Technically, reporting is a current view of how the data is today based on live data. It represents the live data. In some cases, that's too late to do anything about.

Performance Analytics takes snapshots to save meta data (scores) that you define. Using this information you can start to gain insights to how your data is changing over time and where you can make performance optimizations based on decision points (or indicators.) You define the indicator sources, indicators, of what data you want to see and breakdowns (e.g. by category, assignment group, etc) how you want to see it.

Let me know if you need more detail than that.

https://docs.servicenow.com/bundle/helsinki-performance-analytics-and-reporting

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Uncle Rob · ‎01-18-2018

So if a ticket was created in August and then cancelled or somehow deleted in a couple of days, we won't see that in a report (made with OOB functionality)?

If it was deleted its definitely gone. "We won't see it" really depends on the question. In PA you're typically building an Indicator... something you know about a ticket (or group of tickets) at that point in time. OOB you *only* know what's true *now*... but every time we ask in the *now* the answer could have changed.

Those top three boxes are showing change over time for the given indicator. In each case you couldn't go back and retroactively figure out what "Average last update age" was ... say... a week ago. You can ONLY make that comparison if you saved the Indicator's value at that time.

Now lets amp it up a level. For each indicator you might want to see the same indicator, but broken down by a different element... like Priority, assignment group, category, or whatever.

Would it be correct to say that the whole thing is that the data in the tables can be changed. Reporting relies on that data, which is why one and the same report will show different things today and tomorrow (like in the example). And PA stores the data as it was at some point in time so that the needed 'pieces' are not lost?

That's definitely one way of describing it. But its not just about "storing all past data". Its more about determining Indicators that hint at performance and measuring that performance regularly and comparing past performance against present performance.

If you've got it turned on in your instance, I'd be happy to tour you around.

Zanna · ‎01-18-2018

Oh, thank you even more now!)

No more questions from me, I guess.

I'd actually like a tour but I haven't got it tuned. Tried to but failed

Had to find my way around through videos)

dangrady510 · ‎10-07-2016

Performance Analytics allows you to increase the value of the data by adding more context to it. Context in terms of time, influence, and target audience.

The ability to capture historical point in time data and trend it helps you better understand whether the actions you are taking are making an impact. I had a colleague use the example of a scoreboard in sports. Reporting is like the scoreboard it tells you the score, the time left, number of timeouts at that current point in time. But if you were managing or coaching that game you're understanding of you got to that point and the momentum in the game will make a significant impact on the decisions you make.

From an influence standpoint - Performance Analytics gives you the ability to build relationships between metrics in certain visualizations so you can see how one metric is influencing another over time. This allows you to create leading and lagging indicator relationships which will help guide the actions you take and adjustments you make. I put together a blog post on this topic. Moneyball for Enterprise Service Management (ServiceNow)

From a target audience standpoint - you can use provide more contextual information for people. Specifically using the In-Form Analytics capabilities. So details on that here Welcome to Reporting and Performance Analytics on Helsinki!

Uncle Rob · ‎10-11-2016

OOB Reporting - What does the data look like right now?

Good for:

- Listing records

- Static graphical representation of current data

Performance Analytics - What does the data look like when compared to how it looked in previous periods.

Good for:

- Measuring things over time

- Establishing KPIs (since KPI's are useless unless measured over time)

- Removing work from historic analysis

- Establishing true performance data.

"How are you using Performance Analytics for Incidents?"

- Establishing universal definitions for success, and getting the system to measure it constantly and automatically. Previously, customers had multiple managers running and archiving their own reports... maybe.

- *Actually* driving performance against *actual* measurable goals. "We need to improve response times!" Great, I fire up PA dashboard and find out 1st whether I'm getting better or worse at it, and how far I am from my goal.

- Deconstructing trends in a fraction of the time. Previously I was comparing multiple periods worth of excel sheets. Now I'm eyeballing a chart.

- Using industry data to convert KPI performance into a financial model. If I drive performance to meeting KPI's measuring Incident performance, I can actually attribute that to dollars.