Aspire’s home grown Artificial Intelligence Service Optimizer is a diagnostic analytics framework in helpdesk automation and management. Be it reducing the ticketing cost by 30% or apply AI to predict the average resolution time of the tickets, our AI Service management enhances the Service improvement of your ticketing management system and helps in service desk automation. Before we dig deep, let’s address the elephant in the room.
32% reduction in cost and true segmentation of tickets
60% enhancement in productivity
Better SLAs and TAT
Bring greater transparency and better ticket assignment strategy
Optimum utilization of resources and ROI
Huge number tickets are created and are unexplored
Lack of bespoke solutions to measure metrics like average cost per request
Tickets SLAs needs to be updated regularly
Management expects 1 tool to solve all helpdesk problems
This leads to low workforce utilization and failure to rewrite ticket SLAs
Aspire AI Service Optimizer uses the ticket data extracted from diverse enterprise system of records and ingests into the Big data layer. Data from the Big data layer is used by machine learning layer for building predictive models. The predictive models involve ticket profiling, ticket assignment and reassignment efficiency, ticket volume management and trend analysis of cost and ROI.
Apply AI to profile past tickets, segment into similar groups. Predict the probability of a new ticket being assigned to a given segment by source of their tickets, and resolution time.
Apply predictive analytics (regression) to predict resolution time by leveraging ticket segment, past TAT(turnaround time), assigned team and business service.
Cost and ROI is predicted by using past data for average cost per ticket or through rule-based system to calculate the same.