Elevate Efficiency with ServiceNow’s Task Intelligence

ServiceNow continues to push the boundaries of innovation, particularly in the areas of Machine Learning and Predictive Intelligence. The focus lies on enhancing the overall experience for agents and boosting operational efficiency within the dynamic landscape of enterprise service management.

AI, Machine Learning, and statistical modeling prove to be powerful assets, empowering organizations to enhance the accuracy and completeness of record data. These technologies allow users to concentrate on processes without the fear of incorrect categorization or repetitive reassignments, proving invaluable for teams and agents in sizable companies.

What is Task Intelligence for ITSM?

Task Intelligence for ITSM is an intelligent AI solution that leverages existing data in ServiceNow to speed up task categorisation and group assignment (routing).

The functionality can be trained on filtered data sets to learn patterns between past user input and agent decisions. By utilising Machine Learning algorithms, it then analyses historical data to provide real-time suggestions for incident categorisation and assignment of new records. There is complete flexibility in configuring which attributes it learns from or provides guidance on.

The true value proposition of Task Intelligence for ITSM lies in its potential to accelerate the resolution process and to ensure greater accuracy and consistency in handling incidents. By expediting the categorisation and routing of incidents, it significantly reduces resolution times, thereby enhancing operational efficiency. On the other hand, its predictive capabilities contribute to a statistical improvement in the accuracy of categorisation and assignment decisions. This combination of speed and precision not only streamlines workflows but also ensures that resources are allocated effectively.

Fine-Tuning for Optimal Performance

Task Intelligence for ITSM provides the capability to create, train, review and fine tune models based on statistical hard data from previously closed Incident records. This enables the generation of recommendations for ITSM Agents regarding categorisation or group assignment when they first view a new incident.

Based on previously encountered combinations, such as keywords in Short Description or Description fields on the Incident form, Task Intelligence models can be trained to offer recommendations for additional fields like Assignment Group or CMDB (CSDM) Service.

With a minimum of 10,000 records required for training, feeding more data into the model enhances the accuracy of predictions. Targeting specific fields as inputs (e.g., Short Description/Description) allows matching with outputs (e.g., Category/Subcategory/Service/Assignment Group).

As certain combinations reoccur, the statistical probability of their correctness increases. These choices are then recommended to the ITSM Agent who is interacting with the Incident record via ServiceNow’s intuitive Agent Workspace interface.

Even if the models occasionally provide incorrect recommendations, agents can disregard them. The incident record serves as valuable feedback for further training and refinement of the model.

Task Intelligence’s recommendation of values for crucial fields enhances overall accuracy and data correctness in incidents. This allows agents to prioritise the most important work of all – resolving incidents and restoring services to end users.

Leveraging ServiceNow’s Latest Capabilities

In the ever-evolving landscape of enterprise service management, ServiceNow continues to pioneer advancements aimed at enhancing agent experience and operational efficiency. Powered by AI and Machine Learning, Task Intelligence for ITSM unlocks new levels of efficiency and effectiveness.

We invite you to explore these exciting possibilities with our consulting team at ITCE. Reach out to us at info@itce.com to discover how Task Intelligence can transform your approach to incident management, bringing efficiency to the forefront of your organisation’s success story.

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