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DESCRIPTION:Opher Baron\n\nRotman School of Management\, University of Toro
 nto\n\nBusiness Process Intelligence in Congestion-Driven Systems: From Ev
 ent Logs to Real-Time Digital Twins\n\nDate: Friday\, April 10\, 2026\n	Tim
 e: 10:00 AM - 11:00 AM\n	Location: Bronfman Building\, Room 046\n\n\nAbstra
 ct\n\nMany modern business processes operate under congestion: stochastic 
 demand\, shared and limited resources\, complex routing\, and tight servic
 e-level constraints. From healthcare and public services to logistics\, fi
 nancial operations\, and large-scale customer support\, these systems exhi
 bit nonlinear behavior where small disruptions propagate quickly and perfo
 rmance deteriorates sharply.\n\nThis talk examines how Business Process Ma
 nagement can evolve to address congestion-driven environments by integrati
 ng process mining\, queueing theory\, simulation\, and machine learning in
 to AI-enabled digital twins.\n	Using large-scale event-log data from real d
 eployments\, we illustrate how descriptive analytics must move beyond stat
 ic dashboards toward data-driven process models that reveal how processes 
 actually unfold in practice—capturing routing variability\, rework loops\,
  synchronization delays\, and resource contention. Process mining provides
  structural visibility\; queueing-aware modeling explains performance\; ma
 chine learning supports prediction under uncertainty.\n\nBuilding on these
  foundations\, predictive and comparative analytics enable counterfactual 
 “what-if” evaluation of staffing\, routing\, prioritization\, and scheduli
 ng policies before implementation. Finally\, prescriptive analytics embedd
 ed within real-time digital twins allow organizations to intervene proacti
 vely—anticipating congestion\, reallocating capacity\, and mitigating casc
 ading delays.\n	\n	Drawing on industrial deployments through SiMLQ\, this ta
 lk demonstrates how combining process intelligence with congestion-aware o
 perational modeling transforms BPM from retrospective analysis into contin
 uous\, real-time decision support. The implications extend across service 
 industries where variability and resource contention define performance\, 
 resilience\, and competitiveness.\n
DTSTART:20260410T140000Z
DTEND:20260410T150000Z
LOCATION:Room 046\, Bronfman Building\, CA\, QC\, Montreal\, H3A 1G5\, 1001
  rue Sherbrooke Ouest
SUMMARY:Management Science Research Centre (MSRC) Seminar: Opher Baron
URL:/desautels/channels/event/management-science-resea
 rch-centre-msrc-seminar-opher-baron-372292
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