PROBLEM STATEMENT
A multi-billion dollar legal firm with offices across the country has an IT department that supports their critical information infrastructure including IT software systems, desktop support and operational issues such as virus attack etc. Downtime or delay can result in thousands of lost billable hours. They asked TeraCrunch to identify actionable patterns from their IT help desk ticketing system data that would contribute to optimal resource allocation, scheduling, training and other organizational optimization decisions surrounding demand for and successful provision of IT services.
STARTING POINT
TeraCrunch connected with the client's help desk ticketing system to extract regular updates of both structured and unstructured data. The structured data included the number of tickets, average time of resolution of tickets, and the type of tickets that took most time to resolve. The unstructured data included the email messages that users sent to the help desk support staff, the questions and answers involved, the connection between the education level of the users to the type of questions and difficulty of resolution of their issues and their ability to respond to the support staff. We combined those data with organizational structure, IT infrastructure and geographical distribution.
TEXT ANALYTICS
Much of the useful information within a ticketing system is in the free text fields describing problems and solutions. Our text analytics identifies and hierarchically categorizes the most important information and structures it for predictive analytics.
PROBLEM & SOLUTION SEGMENTATION
Each problem the Help Desk is confronted with has characteristic difficulties, requires a solution that effectively addresses those issues, and needs to be addressed by a technician with the requisite skill set. Our analytics isolate those defining properties and matches them accordingly.
PREDICTIVE TREND ANALYSIS
Segmented problems and solutions are optimally paired to maximize success and minimize labor and other resource expenditures. Ongoing data collection & interactive analytics allow for continuing process optimization. Pooled ticket outcomes are used for resource planning and assignment.
RESULTS
TeraCrunch solution allowed the department to pinpoint areas for improvement and is now a regular tool in their operations monitoring and planning. Predictive intelligence of their internal resources and projects supply & demand resulted:
Reduced call center operations cost by 9% because of better planning & and optimal use of resources
Monthly demand prediction helped reduce staff during downtime, which resulted a yearly cost savings of 3 resources out of a group of 19 resources
