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Finding Priorities: Which components of IT are prepared or need to be optimized to scale business operations without risking service disruptions?
Filling the Skills Void: How to leverage the vast knowledge base available to complement the limited skill set in solving current and expected IT issues based on?
Optimizing Resource Distribution and Cost Effectiveness: How to distribute time and HR resources in resolving mission-critical support issues while decoupling dependence on the limited personnel?
Intelligent load balancing between onshore, near shore and offshore teams depending on many parameters such as ticket complexity or severity, represents a significant source of improvement in efficiency and cost reduction.
Business IT Alignment: How to ensure that IT investments positively impact business revenue and operational excellence?
Automation and Shift Left Opportunities: How to optimize shift left ticket resolution?
The process of resolving tickets at initial support levels involves automating simple repetitive processes, offering self-serve capabilities to users and training Level-1 agents on resolving a variety of repetitive issues.
Service Availability and Reliability: A digital operating model requires IT systems to be dependable when organizations rapidly expose their services and products to a large user base across new markets and geographic locations. An intelligent IT Service Desk organization is not limited in time and HR resource availability to solve problems at scale. Intelligent service desk support is fully capable of resolving repetitive problems, and in fact, exposure to large data sets enable AI-based support solutions to deliver solutions with higher accuracy.
Data and Insights: Since critical data is hidden inside non-structured data , IT leaders struggle to properly leverage the huge source of knowledge and insights hidden within the vast deluge of information produced in the form of ticket requests and resolution activities. This information can help IT find prevalent challenges in their hardware and software deployments, identify solutions that generate a lot of tickets and therefore with a very high TCO; as well as identifying inefficient operational workflows and processes that require expensive upgrades to keep pace with digital transformation initiatives.
Intelligent Ticket Routing : Routing every ticket request to the appropriate resolution team and agent based on their skillset, availability and load can greatly positively impact KPIs such as Mean Time to Resolve (MTTR). Traditional technology solutions focus on categorizing ticket requests for accurate assignment using the “classifier” approach. In practice however, most ticket requests remain uncategorized because the number of existing categories is always limited. An unsupervised clustering approach, however solves this problem and creates an infinite number of clusters of similar tickets (based on structured and unstructured data), therefore creating a very granular skillsets mapping An intelligent solution connects the right team to the right request from both ends: the organization maps skills across the organization for optimal HR resource utilization; and the ticketing system maintains clusters of problem categories and the historical knowledge base.
The end result is that the IT Service Desk actively contributes to solving business problems associated with IT issues. Therefore, the modern IT Service Desk that leverages intelligent technology solutions is not limited to serving internal users, but actively contributes to continuously improving business operations in the digital age.
This is why we created Swish.ai.
