Mining insights out of workflow data analysis

Customer support services such as IT helpdesk have to answer and fix a variety of issues for their customers. Implementing a highly efficient IT helpdesk is critical for an organization's daily operations. With an increasing number of issues, the IT helpdesk suffers from an overwhelming workload. However, non-transparency of workload and quality makes it hard to evaluate the performance of the IT helpdesk and the quality of services, affecting work productivity and service satisfaction. Thus, improving IT helpdesk operational management for higher issue resolution productivity is becoming nescessary. This thesis is focused on mining insights from Futurice IT helpdesk workflow data and providing AI and data solutions, for making its workflow follow lean production principles. The thesis research evaluates the current state of Futurice IT helpdesk, provides AI and data solutions through a design prototype and discusses possible future recommendations.