ITSM Success Dashboard indicators KPI definitions and formulas

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Enable ITSM Success Dashboard and configure settings to understand and use the Key Performance Indicators (KPIs) and formulas.

Performance overview ITSM Success Dashboard uses the following KPIs and definitions: Self-solved percentage: Calculated from the daily average number of times your users achieved a resolution without intervention from Tier 1 Agents in the report range. Includes numbers from Self-solved using Virtual Agent, Self-solved using Knowledge and Automated resolutions (For example, Incident auto-resolution via Virtual Agent). See the formula: [Self-solved using Virtual Agent + Self-solved using Knowledge + Automated resolutions] / [Total ticket resolutions + Self-solved (VA) + Self-solved (KB)] x 100 Self-solved using Virtual Agent: Number of automated conversations that helped the user solve their problem. In the base system, this is determined by the ITSM-self-resolving deflection pattern instrumented in the Virtual Agent topic and recorded in the Deflection Metrics table. The topics shipped with ITSM VA Conversations already have these nodes instrumented but must be instrumented in all other topics. Note: To use a different method to determine this KPI, see Configure Success Dashboard indicators KPIs . Self-solved using NOW Assist: Number of automated conversations that helped the user solve their problem. In the base system, this is determined by the ITSM-self-resolving deflection pattern instrumented in the NOW Assist topic and recorded in the Deflection Metrics table. The topics shipped with ITSM NOW Assist Conversations already have these nodes instrumented but must be instrumented in all other topics. Self-solved using Knowledge: Number of times users were able to solve their problems by reading knowledge articles. In the base system, this is determined when users read the knowledge articles and do not create an incident in a 24-hour window. Note: To use a different method to determine this KPI, see Configure Success Dashboard indicators KPIs . Automated Resolutions: Number of times the ticket was resolved automatically. In the base system, the indicators contributing to this metric are Incident Auto Resolution and Request Fulfilled Automatically. The Incident Auto Resolution value is determined by the deflection node configured in the Issue Auto Resolution Virtual Agent topic. The Request Fulfilled Automatically value is the number of requested items that are fulfilled using automated workflows. When the catalog item uses an automated workflow, the Fulfillment automation level field of the catalog item must be set to Fully-automated for it to be included in this metric. Accounts unlocked using Password Reset apps : Number of times users were able to unlock their accounts successfully using Password Reset apps. Passwords updated using Password Reset apps : Number of times users were able to update their account passwords using the Password Reset apps.

Note: To use a different method to determine this KPI or add more sources (for example, automated catalog workflows), see Configure Success Dashboard indicators KPIs . Total ticket resolutions: Number of incidents resolved + Number of requested items closed. Call deflection: Calculated from the number of times per day requesters performed the actions, Ticket submissions using Service Catalog, Ticket submissions using Virtual Agent, Self-solved using Virtual Agent and Self-solved using Knowledge without Tier 1 agent intervention. See the formula: [Catalog ticket submissions + VA ticket submissions + Self-solved (VA) + Self-solved (KB)]/ [Total tickets submitted + Self-solved (VA) + Self-solved (KB)] x 100 Catalog ticket submissions: Incidents and requested items submitted using Service Catalog in Service Portal or Now Mobile app . VA ticket submissions: Number of times the ticket was submitted using Virtual Agent. In the base system, this is determined by the ITSM - Triage & Created deflection pattern instrumented in the Virtual Agent topic. The topics shipped with ITSM VA Conversations already have these nodes instrumented but must be instrumented in all other topics that create incidents. Note: If you use a different method to determine this KPI or add more sources (for example, automated catalog workflows), you can use the steps described in Configure Success Dashboard indicators KPIs . NOW Assist ticket submissions: Number of times the ticket was submitted using NOW Assist. In the base system, this is determined by the ITSM - Triage & Created deflection pattern instrumented in the NOW Assist topic. The topics shipped with NOW Assist Conversations already have these nodes instrumented but must be instrumented in all other topics that create incidents. Total tickets submitted: Incidents created + RITMs created. Structured tickets: Total number of requested items completed successfully in the report range. Productivity moments per user: Productivity Moment is calculated when the ServiceNow products helped a user to be more productive while working in their day to day operations. Productivity in search per user : The number of times the NLU prediction model accurately understood the intent of the user's conversation or auto-selected a topic. Productivity in routing per user : Successful predictions of incident fields such as assignment group, or category by Predictive Intelligence solutions, counted when the prediction made by the solution is the same as final value when the incident was closed. Productivity in fulfilment per user : Includes any productivity gains achieved where ServiceNow is helping the employees to save time to resolve a ticket

Note: If you use a different method to determine this KPI, you can do so using the steps described in Configure Success Dashboard indicators KPIs .

Service Quality Customer Satisfaction Score: Calculated from the daily average score of the surveys conducted after an issue was resolved through a ticket or through virtual agent. Mean-time to resolve: Calculated from the daily average of the time between the ticket creation and ticket closure. % Breached SLAs: Calculated from the daily average number of issues that were closed after having breached an SLA. % First assignment resolution : Calculated as the percentage of tickets that were resolved without having to reassign the ticket to a different group. % Reopened tickets: Calculated from the percentage of resolved tickets that were reopened during a specified period.

Operational Success An operational KPI is a quantifiable measure that tracks the efficiency and effectiveness of day-to-day operations in your organization. The KPIs can be organized in a dashboard that highlights the areas that are running efficiently and the areas that need attention.

By monitoring operational KPIs, you can identify areas for improvement, optimize processes, and ultimately achieve their strategic goals. Here are some techniques to use the operational KPIs: Ensure your KPIs match your organization’s business goals. Define your KPIs that contribute to achieving those objectives. Focus on the most critical KPIs that add value to the organization’s growth. Track and review KPIs regularly. Monitor your progress and modify the KPIs as required by the organization’s goals. Use data to drive decisions: Identify trends, uncover root causes, and use insights to improve processes and performance. Use the data to identify trends and use insights to improve processes and performance.

To create a new operational dashboard, refer Create an operational success dashboard .

Table 1. Incident KPI Description Overdue incidents Number of open incidents that are pass the due date. Incidents nearing SLA Percentage of the incidents nearing the SLA threshold. This is based on the percentage of SLA elapsed where the elapsed percentage is between 50-75%,76- 85%, 86-95%, above 95%. Open incidents not updated Number of open incidents that aren't updated as per the age. This is categorized as per the age of an incident that are between 1-5, 6-10, 10-30, and greater than 30 days. Incidents created (by priority) Distribution of the Incidents created priority wise Incidents by activity channel Total number of closed incidents created from different sources. Mean time to resolve an incident (by priority) Mean time to resolve the incidents priority wise Average incident reassignment Average number of times that incidents were reassigned. % high priority incidents Percentage of P1 and P2 incidents that are successfully closed Average number of incidents created per user Average number of the incidents that are created by a specific user % Incidents associated with Problem Percentage of the incidents that are associated with problem Total outages due to incidents Total outages in hours because of incidents.

KPIs for Major Incident .

Table 2. Major incident KPI Description Overdue major incidents Number of the major incidents that have breached the SLA. Open major incidents (by age and assignment) Total number of open major incidents assigned/not assigned distributed over the age. Open major incidents (by services and state) Distribution of major incidents between various services and state. Major incidents nearing resolution SLA Percentage of the major incidents nearing the SLA. This is based on the percentage of SLA elapsed where the elapsed percentage is between 50-75%,76- 85%, 86-95%, above 95%. Closed major incidents (by services) Distribution of closed major incidents between various services. Mean time to take actions on a major incident Average time taken for a major incident to be proposed, acknowledged and resolved. % Major incidents breached SLA Percentage of major incidents that breached SLA. % Major incidents closed without post incident report Number of major incidents that are closed without having a post incident report (PIR). % Major incidents associated with problems Percentage of the major incidents associated with problems. Outages due to major incidents Total outages (in hours) caused due to major incidents.

KPIs for Change.

Table 3. Change KPIs KPI Description Open changes (by age and priority) Priority wise distribution of the open change requests priority wise. This is categorized in days between 0-1, 2-5, 6-30, 31-90, and above 90 days. Open emergency changes (by age and priority) Priority wise distribution of the emergency change requests that are still open. This is categorized in days between 0-1, 2-5, 6-30, 31-90, and above 90 days. New change request (by risk) Distribution of the new change requests by risk. Average age of open changes (by risk) Average age of a change requests based on risk. Change success score (by assignment group) Distribution of the change requests by assignment group. Closed changes (by priority) Priority wise distribution of the changes requests that are successfully closed. Mean time to close a change (by priority) Mean time to close the change request priority wise. % Successful change with issues (by model and type) Distribution of the change requests closed with issues distributed by change model and change type. % Successful change without issues (by model and type) Distribution of the change requests that are successfully closed with some issues by change model and change type. Incidents caused by change requests Total number of incidents that are created because of a change request. % Failed changes Percentage of the change requests that are not successfully completed. % Unauthorized changes Percentage of the unauthorized change requests that are created. Outages due to change Total outages in hours because of change.

KPIs for Request.

Table 4. Request KPI Description Open requested items (by stages) Distribution of the requested items that are open by stages. Open requested items (by states) Distribution of the requested items by state. Active requested items due within 5 days Total number of open requested items that are due in 5 days. Open requested items (by age) Distribution of the requested items in open state. This is categorized in days between 0-1, 2-5, 6-30, 31-90, and above 90 days. Mean time to fulfill a requested item Average time taken to fulfill a requested item. Mean time to fulfill a requested item (by category and catalog items) Mean time to fulfill a requested item for different catalog categories and catalog items. Closed requested items (by states) Distribution of the requested items by their closed state i.e. Skipped, Complete, Incomplete. Request items created from various channels Distribution of the requested items created from different sources. Requested items from incidents (by category and catalog items) Requested items created from incidents for different catalog categories and catalog items.

KPIs for Service Catalog .

Table 5. Service Catalog KPIs KPI Description Catalog Item best practice deviations Number of deviations from the best practices for active catalog items. Catalog item VA render type Catalog items distributed by how they will be rendered on a Virtual Agent bot. Catalog item fulfilment automation level distribution Distribution of the catalog items that are fulfilled automatically. Catalog item translation coverage Language wise distribution of the catalog items that are translated.

KPIs for Interaction.

Table 6. Interaction KPIs KPI Description Interactions with task associated (by task type) Number of interactions that are associated with a task and are distributed by task type. % First call resolution Percentage of the interactions that are closed in the first call and no tasks are created. Closed interaction (by channel) Distribution of the closed interactions created from different channel.

KPIs for Problem.

Table 7. Problem KPIs KPI Description Open problems (by age and priority) Problems currently open distributed over age and priority. Open problems (by state and age) Problems currently open distributed over age and state. % open critical problems (by state) Percentage of critical problem that are categorized by state. % open problems classified as known error Percentage of problem with associated Known Error articles. Average reassignment of open problems (by category) This is the average number of times problems have been reassigned. Closed problems (by age and priority) Closed problems by age and priority. Mean time to close a problem Average time taken to close a problem.

KPIs for On-Call Scheduling .

Table 8. On-Call Scheduling KPIs KPI Description Active escalations (by priority and acknowledgement status) Priority wise distribution of on-call escalations based on their escalation status. Acknowledged escalations (by level, shift and groups) Distribution of acknowledged escalations based on level/shift/groups. Escalations not acknowledged (by level, shift and groups) Distribution of escalations that are not acknowledged by level/shift/groups. Contact attempts acknowledged Total count of contact attempts acknowledged based on level and contact attempts. % Escalations acknowledged (by groups) Percentage of the escalations that are acknowledged. % Escalations not acknowledged (by groups) Percentage of the escalations that are not acknowledged. Mean time to acknowledge an escalation (by group) Mean time to acknowledge an escalation based on escalation level. Mean time to acknowledge an escalation (by level) Mean time to acknowledge an escalation based on escalation level. Total On-call hours (by user) Total number of hours the user was available for On-call.

Parent Topic: ITSM Success Dashboard indicators reference