While Performance Analytics has been around for a couple of years, a lot of ServiceNow users and administrators might not be fully aware of what exactly it is and what it can be used for. Some might know that it is related to reporting. Some might have seen images of nice dashboards or heard that it has something to do with tracking performance.
But there’s already a reporting module in ServiceNow, so why would you need another one?
Table of Contents
What Performance Analytics is
- Automated Indicators – The measurements
- Formula Indicators – Metrics calculated using measurements
- Breakdowns – The dimensions
- Targets and Thresholds – Providing context and driving action
- Widgets Types In Performance Analytics
- Use cases for Performance Analytics by Persona
- Performance Analytics vs Reporting
- Performance Analytics vs Separate BI tools
What Performance Analytics is
Performance Analytics (PA) is an application in ServiceNow used for measuring performance over time. It works by letting us to set up metrics, referred to as “indicators” and regularly collect data snapshots of the records matching the indicator’s definition. This snapshot functionality is the main feature of PA. The collected data can then be broken down by different elements (called breakdowns) and visualized in dashboards using widgets. Different time series can be applied to the collected values to analyze them by different intervals.
Performance Analytics is not restricted to any application, record type or table. Anything in the platform can be measured!
Snapshots are arguably the most important and distinctive functionality provided by Performance Analytics. They enable us to save a view of the state and values of our records at a certain point in time. The information saved in a snapshot would otherwise be lost due to constant changes overwriting the data. For example, it becomes possible to see how many records were open on a certain day, how many of those records had less than 10% of their SLAs time remaining at that time, or what the average age of open incidents were at the end of last month. This is information that we would have no way of getting in a graph without PA.
Not only does the snapshot contain the score, but also references to each of the records that make up the score. This enables us to see, for example, how many incidents were open at a past date, but also exactly which incidents were.
Automated Indicators – The measurements
An automated indicator is essentially a user defined filter on a ServiceNow table or database view, combined with an aggregation method. We could for example count the number of open incidents, average the reassignment counts of closed incidents or sum the elapsed SLA percentage in closed SLA:s.
The indicators are collected by scheduled jobs that runs according to a user-defined interval and time. When this collection happens, the score of the indicator is saved for that day, as well as a reference to all the records that contributed to that score. These scores, and the underlying data, are then available to analyze.
Formula Indicators – Metrics calculated using measurements
Examples of potential formula indicators include:
- Percentage of Incidents Resolved Within SLA
- Average Age of Open Tasks
- Average Duration of a Task Assignment
- Average Customer Satisfaction Survey Score
- Relative and Absolute Change of Incident Backlog
- Average Cost of Resolving an Incident
Formula indicators can also be created based on other formulas, for example a formula calculating an index score based on multiple weighted key performance indicators and other formulas. Starting with the Madrid release it is also possible to create derivative formulas like the distance between a formula’s current result and the target result, expressed as a percentage.
Breakdowns – The dimensions
A breakdown is an element for which data in indicators and formula indicators can be grouped. These elements can be field values in the record, such as priority, state or category, or other records referenced from the form like assignment groups or business services.
Breakdowns can also be scripted. For example, open incidents can be grouped into intervals of “number of days open”. This lets us collect scores for not just the total number of open incidents, but also:
- The number of open incidents assigned to every group.
- The number of open incidents that have been open 0-5 days, 5-10 days, 10-20 days etc.
The scores, like all scores, are saved daily so we can look at how they change over time.
Targets and Thresholds – Providing context and driving action
For each indicator, both formula and automated, targets can be specified on global and personal levels. These targets can the be used as values in other formulas, or to create visualizations showing by how much a target was exceeded or missed. The targets can also be used to change visualization, for example turning a number in a report red if it is below the set target.
Thresholds can also be set that trigger events and send notifications to specified users. This means the person who is responsible for acting to rectify or in some other ways act on the trend of a metric will quickly receive the information needed to do this.
Widgets Types In Performance Analytics
Performance Analytics also comes with a number of additional widgets types:
Shows a one or more indicator’s value over time. Can be of type: area, line, spline, step, column or stacked column.
Shows an indicator’s value by breakdown element, including data such as distance to target, change from previous score and trend. Can be of type: scorecard, column, pie, donut, semi-donut, funnel, pyramid, pivot, line etc.
Shows a single score of an indicator. Can be of type: latest score, speedometer, dial or real-time score.
Displays the score of multiple indicators in the same widget. Can be of type: list or spider.
Text analytics analyzes unstructured data like incident descriptions, and visualizes it in a word cloud in which the user can drill down on word or phrases to see which records contain them. It’s a very useful tool for finding patterns in records.
A workbench widget is a special widget that groups an indicator into tabs based on a breakdown, for example state or age-group. For each tabs multiple contextualized supporting visualizations can be viewed. This widget is great for analyzing processes or workflows.
Dashboards are the modern versions of homepages. A dashboard is a tabbed canvas onto which widgets can be added, both reporting widgets and PA widgets. Dashboards can be used even if Performance Analytics is not activated, but will then be lacking functionality, such as filters.
The dashboard can be set up with a dashboard filter based on a breakdown common to the widgets. This allows the dashboard, and all widgets on it, to be filtered to data for a specific breakdown element. This filter can apply to both reporting and PA widgets.
For example, a filter can be used to select different assignment groups, incident priorities, categories or business services and have all the widgets on the dashboard display only data related to this element. This makes dashboard highly dynamic, and gives users the ability to drill down into the data. You can create one single dashboard, and difference groups will be able to filter it to only include their tasks.
This short video demonstrates how a dashboard filter is applied to all widgets on the dashboard in order to filter the widgets to show only data for a specific incident category:
Apart from tracking values over time, Performance Analytics also provides a forecasting function that predicts future trends of metrics based on past data. This enables us to predict and proactively address problems before they occur.
Spotlight is an application in Performance Analytics used to evaluate records using on weighted criteria, and rank them based on the sum of their scores. This score can then be used for work prioritization.
Use cases for Performance Analytics by Persona
Performance Analytics lets us track trends, set targets, calculate advanced KPI:s using formulas and save snapshots of scores and records for past periods. Depending on a user’s role and position, Performance Analytics provide different value.
An executive user is most likely interested in viewing high-level KPI:s the track the overall performance of the organization and its business goals. Areas of focus could be the quality and cost of services provided and how they measures against targets. The overall responsibility of an executive means they cannot view every single detailed indicator.
For this purpose, index metrics regarding service quality, customer satisfaction and costs can be set up and tracked over time. These index KPI:s are based on multiple metrics. As the value of the index exceeds or dips below a target, the visualizations indicate what to focus on by providing color signals.
This gives a strategic performance overview. The index value can be broken down to a customer, service or business unit level, showing the executive which part of the organization or what service is underperforming, and which customers are affected.
A service owner will be able to use Performance Analytics to monitor the quality and cost of the service they are responsible for. This can include metrics tracked over time for incident resolution, service level compliance adherence, customer satisfaction and the stability and availability of the service.
By using breakdown, a service owner will be able to see their metrics broken down by assignment group, process, customer, applications and CI:s as well as service level. If there is a problem, this will enable the service owner to identify it and find its source. This leads to increased quality and a more attractive and affordable service offering.
A process manager will be able to use Performance Analytics to monitor the KPI:s of the process they manage. This could include metrics for average handling time, average assignment time per group, SLA compliance, number of open process tasks, knowledge usage, reopened tasks, self service usage and average reassignment counts. All these metrics can be tracked over time and against targets, giving the process manager insights into performance, improvements and potential bottlenecks.
A manager of a team or assignment group will be able to view metrics regarding case loads, average handling times and SLA progression, backlog change and open tasks by type, priority and category. These metrics can be viewed over time and broken down by team member. This allows the manager to predict challenges, schedule staff efficiently and enhance team competence.
Fulfillers, technicians and agents
Workers handling tasks will be able to use PA and Spotlight to identify tasks that require action, and better prioritize work in order to achieve the targets of the organization. Since each indicator includes references to the underlying data, every widget can be clicked in order to show a list of records making up, for example, the “Incidents not updated in 5 days” score. This makes it easy to understand what work should be performed to improve a result.
Performance Analytics vs Reporting
Performance Analytics and Reporting are not mutually exclusive. In fact they are complementary. Reporting widgets are used to show current scores from table by using queries and simple aggregations and record groupings based on current values.
Performance Analytics widgets are used to show historical scores, the trend of metrics over time and the set of records that made up past scores. Performance Analytics can also break down records and aggregate scores using advanced scripted logic, even by fields not on the record itself or directly referenced by the record.
The formula function of PA lets us calculate scores, creating more meaningful and strategic key performance indicators that track multiple aspects of importance. We can derivate metrics from things like the score’s distance to a set target.
Finally, whether using Reports or PA widgets, the dashboard filter functionality of PA makes data visualizations much more powerful and dynamic. It gives the users the ability to drill down into data and gain insights, instead of just looking at static graphs.
Performance Analytics vs Separate BI tools
A lot of organizations use external Business Intelligence tools like Power BI, Qlik or Tableu. While these tools might have more functionality than Performance Analytics, they cannot offer some of the things PA can.
- Performance Analytics does not require us to set up and maintain an external data warehouse or configure an extract-transform-load process: the data already resides in the platform.
- There is no need for additional servers or application installations with PA, all you need to do is activate a plugin.
- Having the data and the reporting in the same system makes it easier to go from insight to action. Just click a value and you’ll be taken directly to a list of records, ready to be edited.
- No need for additional access setup, use the roles and groups in ServiceNow.
- Integrate data visualizations and metrics in other ServiceNow applications like Service Portal and Workspaces.
- Performance Analytics uses the familiar ServiceNow user interface, meaning less training for users.
If you want to report on data from outside the ServiceNow platform, you can import it into ServiceNow in multiple ways:
- Scheduled data import job using FTP/HTTP to get excel, CSV-files, JSON or XML.
- Scheduled data import jobs that query database servers using SQL.
- Query a REST API using integrationhub.
- Even more options
Data can also be imported by manual file uploads. Importing external data into ServiceNow lets you run transform functions to relate it to ServiceNow data, like system users. I’ve personally done this with call data from a company’s contact center system, allowing servicedesk managers to see call data and ServiceNow task data in the same report, filtered by servicenow users and assignment groups. It was not very difficult, but provided great value!
But if for some reason the data cannot be loaded into ServiceNow, Performance Analytics supports external indicators based on SQL queries, executed each time the widgets are loaded. For more information, click here.
It used to be that Performance Analytics required a separate license. But nowadays, PA is include in the Professional and Enterprise versions of CSM, HR and ITSM, as well as all ITBM packages. So chances are you already have access.
I believe that Performance Analytics is not just a useful tool, but a necessity for any organization using ServiceNow.
Any organization that wants to improve their processes and by extension, business, should be using it to some extent. The regular reporting module is good for finding out basic quantities, but not enough to actually gain insights and track performance.
With reports, you might be able to get a basic understanding where you are, but with PA you’ll know how you got there and what you should focus on to be where you want to be in the future. Performance Analytics is the tool for any business looking to deliver quality using a data-driven approach.