With digitization efforts running across all industries, IT consulting firms have enjoyed ever-increasing demand for their services. To cope with this demand surge, long-term hiring decisions, as well as short-term capacity planning and staffing, are of crucial importance for business viability. Predictive analytics methods offer enormous potentials to support planning and staffing of IT service desks to ensure both high capacity utilization and service levels. Yet, the current state-of-the-art for these planning activities still relies on traditional statistical forecasting methods. We collaborated with an IT service management firm to develop and evaluate an IT service demand forecasting using machine learning techniques. This approach allows us to improve planning accuracy by more than 30% compared with standard approaches.
Stein, Nikolai; Flath, Christoph; and Boehm, Carsten, "Predictive Analytics for Application Management Services" (2018). Research Papers. 186.