UCL School of Management

Research project

Data analytics in service systems

Summary

The analysis of data orginating from service systems, such as hospitals or call centers, can be used to inform decision-making in a wide variety of ways. In some work, we use data to improve the forecasting of demand to call centers. In other work, we use data to improve operations in healthcare settings. For example, we use data to understand whether surgeons are good at predicting the durations of the surgeries that they will do in the future. This information is crucial in order to set schedules for surgeries in hospitals. 

Relevance

The findings of these projects are useful to inform the operational management of call centers and hospitals. The new models proposed can be used to guide a myriad of decisions in practice, including scheduling and staffing decisions. 

Selected publications

Ibrahim, R., R├ęgnard, N., L'Ecuyer, P., & Shen, H. (2012). On the modeling and forecasting of call center arrivals. Winter Simulation Conference, 23:1. WSC. [link]
Ibrahim, R., & L'Ecuyer, P. (2013). Forecasting call center arrivals: Fixed-effects, mixed-effects, and bivariate models. Manufacturing and Service Operations Management, 15 (1), 72-85. doi:10.1287/msom.1120.0405 [link]
Ibrahim, R., Verter, V., Kucukyazici, B., Gendreau, M., & Bolstein, M. (2016). Designing personalized Treatment: An Application to Anticoagulation Therapy. Production and Operations Management, 25 (5), 902-918. doi:10.1111/poms.12514 [link]
Ibrahim, R., L'Ecuyer, P., Shen, H., & Thiongane, M. (2015). Inter-Dependent, Heterogeneous, and Time-Varying Service-Time Distributions in Call Centers. European Journal of Operational Research. doi:10.1016/j.ejor.2015.10.017 [link]
Ibrahim, R., Kim, S. H., & Tong, J. (2021). Eliciting Human Judgment for Prediction Algorithms. Management Science. doi:10.1287/mnsc.2020.3856 [link]
Song-Hee Kim, & Rouba Ibrahim. (2019). Is Expert Input Valuable? The Case of Predicting Surgery Duration. Seoul Journal of Business, 25 (2), 1-34. doi:10.35152/snusjb.2019.25.2.001 [link]

Link to the publication’s UCL Discovery page

Last updated Saturday, 16 January 2021

Author

Research groups

Operations & Technology

Research areas

Management science; Operations management

Research topics

Applied probability; Applied statistics; Applied stochastic modelling