1 research outputs found
Cognitive system to achieve human-level accuracy in automated assignment of helpdesk email tickets
Ticket assignment/dispatch is a crucial part of service delivery business
with lot of scope for automation and optimization. In this paper, we present an
end-to-end automated helpdesk email ticket assignment system, which is also
offered as a service. The objective of the system is to determine the nature of
the problem mentioned in an incoming email ticket and then automatically
dispatch it to an appropriate resolver group (or team) for resolution.
The proposed system uses an ensemble classifier augmented with a configurable
rule engine. While design of classifier that is accurate is one of the main
challenges, we also need to address the need of designing a system that is
robust and adaptive to changing business needs. We discuss some of the main
design challenges associated with email ticket assignment automation and how we
solve them. The design decisions for our system are driven by high accuracy,
coverage, business continuity, scalability and optimal usage of computational
resources.
Our system has been deployed in production of three major service providers
and currently assigning over 40,000 emails per month, on an average, with an
accuracy close to 90% and covering at least 90% of email tickets. This
translates to achieving human-level accuracy and results in a net saving of
about 23000 man-hours of effort per annum