Top Five Hyperautomation Intelligence Use Cases for IT Service Desk

Hyperatomation Intelligence refers to the strategic approach of modernizing end-to-end business process workflows with the use of advanced AI capabilities. These advancements are embedded into ITSM operations, management and automation of tasks and processes, decision making and the use of low-code or no-code technologies.

 

The concept of intelligence is simple: it takes the existing automation tooling to the next level of intelligence. It enhances your decision-making and decision control capabilities by taking a holistic view of the end-to-end process pipeline and facilitates actionable intelligence.

 

Hyperautomation Intelligence therefore delivers more than automation to repetitive manual tasks that are otherwise suboptimal, even when automated.

 

So let’s review how you can use HyperAutomation Intelligence to gain operational efficiencies.
Here are the top 5 ways you can leverage HyperAutomation Intelligence in your business:

Reduce Technical Expertise

Talent gap is real – especially the IT skills void that prevents organizations from optimizing business processes and supporting customer requests.

This holds especially true for the IT Service Desk where the progress of support agents is determined by metrics such as First Response Time, Ticket Volume and Resolution Rate. The performance on these metrics depends on the technical experts available to handle ticketing requests and can be improved by employing more talent. Considering the growing talent shortage, HyperAutomation Intelligence can be used to reduce the burden on manual technical expertise in several ways: identifying the true issue associated with the service request, connecting with the right resolution teams and applying known resolution actions automatically.

Reducing IT Incidents

Extending the discussion on reducing workload for the limited technical expertise available in-house, HyperAutomation Intelligence plays an integral role in reducing ticketing volume by solving the underlying problem root cause. Although traditional ITSM tooling can help identify and resolve known issues at scale and help reduce ticketing volume, true insights on the underlying problem root cause often remain elusive. Complex IT network and application architectures have highly dependent components. A single issue can cascade through the network and impact (apparently) isolated areas of the network. These issues can be resolved without further investigation into the root cause, which often is the case considering the limited IT expertise available. By employing HyperAutomation Intelligence, the technology can analyze log metrics big data on the IT network and track performance on the extended network, understanding how the incidents cascade through the network and which configuration changes can ultimately resolve the problem at its root cause.

IT Service Desk Workflow Optimization

Your IT Service Desk follows a well-defined mechanism and workflows to effectively deliver support to end-users. In the real world, support requests and the performance of associated IT network and applications is dynamic in nature: it evolves and changes rapidly as new features are introduced or the services are scaled to reach a growing user base. The idea of HyperAutomation Intelligence is to optimize business process and workflows to meet the changing usage demands in context of the available expertise, knowledge, resources as well as business policies. HyperAutomation Intelligence can help optimize business operations on metrics that are most valuable to your business bottom line and customer experience. For instance, many IT Service Teams recognize that increasing ticketing volumes are caused due to unnecessary hops between resolution teams that work in isolation or are not best suited to address the support request at a given instant.

In order to identify the unnecessary hops, it’s important to first understand how the existing ITSM and Service Desk process workflows perform in response to IT incidents and support requests. Opportunities for improvement and bottlenecks are then identified based on big data analytics. The resulting insights then come into play as HyperAutomation Intelligence then facilitates corrective actions to optimize the workflows. The result is fewer hops of support requests between teams, a shift-left resolution process and improved customer satisfaction.

Intelligent Chatbots and Knowledge Management

Chatbots serve a valuable use case for the IT Service Desk: replacing a human agent as the first line of support to end-users while relieving the limited human resources to solve complex problems. In many cases, chatbots can help guide users to the right information, address a resolution that is already published on your support knowledge base and walk users through the resolution process.

The real challenge emerges when a service requires the attention of a real human agent and resolution teams, who then have to scour through the deluge of siloed knowledge base before providing actionable guidance to end-users. In this case, the chatbot service becomes ineffective, primarily due to lack of a well maintained and centralized knowledge repository, and inability to analyze vast pools of historical ticketing archives for a potential solution.

HyperAutomation Intelligence is a valuable use case in this scenario as the technology can maintain an up to date knowledge base, build upon new resolutions and help end-users with a truly intelligent self-service mechanism to resolve ticketing requests with minimal human intervention.

Customer Experience Decision Making

When users interact with the IT Service Desk, they provide an accurate demonstration of user sentiment and customer experience in correlation with various functions and features of the user-facing application interface. The traditional approach of using customer surveys, inapplicable market research and educated guesses fail to capture this information. By taking advantage of HyperAutomation Intelligence, the IT Service Desk can identify areas of improvement on every function and application component associated with the support request. These insights are often hidden in communications with the end-user and can be identified using advanced Natural Language Processing (NLP) capabilities that power the Hyperautomation Intelligence solution.

In essence, these use cases are applicable to IT Service Desk functions facing end-users as well as the internal workforce. The goal of a HyperAutomation Intelligence solution is to capture insights at scale with minimal human intervention. And in practice, this requires an end-to-end HyperAutomation Intelligence strategy and advanced AI capabilities to complement existing ITSM automation tooling.

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