Discovery and Simulation of Business Processes with Probabilistic Resource Availability Calendars
In the field of business process simulation, the availability of resources is captured by assigning a calendar to each resource, e.g., Monday-Friday 9:00-18:00. Resources are assumed to be always available to perform activities during their calendar. This assumption often does not hold due to interruptions, breaks, or because resources time-share across multiple processes. A simulation model that captures availability via crisp time slots (a resource is either on or off during a slot) does not capture these behaviors, leading to inaccuracies in the simulation output. This paper presents a simulation approach wherein resource availability is modeled probabilistically. In this approach, each availability time slot is associated with a probability, allowing us to capture, for example, that a resource is available on Fridays between 14:00-15:00 with 90% probability and between 17:00-18:00 with 50% probability. The paper proposes an algorithm to discover probabilistic availability calendars from event logs. An empirical evaluation shows that simulation models with probabilistic calendars discovered from event logs, replicate the temporal distribution of activity instances and cycle times of a process more closely than simulation models with crisp calendars. This presentation was delivered at the 5th International Conference on Process Mining (ICPM'2023), Rome, Italy, October 2023. The paper is available at: https://easychair.org/publications/preprint/Rz9g
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Discovery and Simulation of Business Processes with Probabilistic Resource Availability Calendars
- 1. Discovery and Simulation of Business Processes with Probabilistic Resource Availability Calendars Orlenys López Pintado Marlon Dumas October 24, 2023 - ICPM’23 PIX Project
- 2. Business Process Simulation Simulation Model Event Log Metrics Waiting Time Processing Time Cycle Time Idle Time Resource Utilization 2 Change some resources from full-time to part-time? Simulation Engine Increase workload of some resources? Replace resource by another with lower performance?
- 3. Undifferentiated Resources Profiles 4 Clerks Same Availability Same Performance Differentiated Availability Differentiated Performance Senior Clerk Junior Clerk Pooled Allocation Unpooled Allocation 3
- 4. Resource Availability 4 08:00 12:00 13:00 17:00 Monday 08:00 12:00 13:00 17:00 Friday 30% 50% 90% 100% 100% 100% 100% 100% 08:00 12:00 13:00 17:00 Monday 90% 90% 90% 70% 50% 50% 5% 5% 08:00 12:00 13:00 17:00 Friday
- 5. And Now What ? … 5 1) Business Process Simulation approach in which resource availability is captured by probabilistic calendars Contributions: 2) Method to discover probabilistic resource availability calendars and performance from event logs 3) Empiric evaluation probabilistic vs crisp models
- 6. Discovering Probabilistic Availability 6 Probabilistic Granularity 00:00 01:00 02:00 03:00 … 21:00 22:00 23:00 Start Timestamp: 00:00, Interval Duration: 1 hour, # Granules: 24 Monday S0 S1 S2 S21 S22 S23 Sunday Recurring Slot: 7 Days (Weekly) P0 P1 P2 P21 P22 P23 Probabilistic Calendar For Each Resource in the event Log Operational? Required? 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 For each Activity Started Completed Enabled … …
- 7. 7 Discovering Probabilistic Availability Operational? Required? 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 Started Completed Enabled … … Trapezoidal Method 1.0 1.0 1.0 1.0 1.0 0.0 0.0 0.0 1.0 1.0 1.0 1.0 0.5 0.0 0.5 1.0 Angle: [0.0, 1.0] PABSOLUTE (Resource, Granule) = Operational (Resource, Granule) max Operational (Resource, Granule) PRELATIVE (Resource, Granule) = Operational (Resource, Granule) Required (Resource, Granule) V S Even (rotative) allocation? Higher workloads overruling?
- 8. Discovering Resource Performance 8 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 0.5 1.0 1.0 0.0 0.9 0.8 0.8 Activity – Duration in Event Log Processing Time Distribution For Each Resource in the event Log For Each 0.5 1.0 1.0 0.0 0.9 0.8 0.8 5 HOURS 3 HOURS, 24 MINUTES Best Fitted Distribution What if not enough Points (i.e., task instances processing times)? 2) Aggregated Distribution 1) Match Closest Resource
- 9. Probabilistic Resource Allocation 9 Activity (workitem) enabled_at: ET Resources (Priority Queue) IS AVAILABLE ? ( R ) NEXT AVAILABLE TIME ( R , ET) ST ADJUST PROCESSING TIME ( R , ST) CT NEXT AVAILABLE TIME ( R , CT) NON-DETERMINISTIC CALENDAR ET
- 10. Experimental Evaluation 10 PROSIMOS: https://github.com/AutomatedProcessImprovement/Prosimos SIMOD: https://github.com/AutomatedProcessImprovement/Simod Implementation Synthetic Real Processes Evaluation Setup 8 Synthetic Logs Loan-B: Balanced Workload (4) Loan-U: Unbalanced Workload (4) 4 Types of Calendars: 1) B-24, U-24: 24 hours, 7 days 2) B-8, U-8: 8 hours, Monday- Friday 3) B-8/4, U-8/4: 50% 8 hours, 50% 4 hours 4) B-24/A, U-24/A: 33%(2), 33% (3), 33% work 24-hour, rest 48 hour
- 11. Experimental Evaluation 11 Evaluation Metrics Cycle Time Distribution (CTD): Evaluates the simulation model’s capacity to replicate the overall cycle time of a process. Relative Event Distribution (RED): Evaluates the simulation model’s capacity to replicate the temporal distribution of events relative to the origin of each case. 0 100 0 100 Real Log Simulated-Log Earth Movers’ Distance metric (EMD) or 1-Wasserstein Distance (1WD) Mismatch Ratio (MMR): Evaluates resource discrepancy between the real and simulated logs. Split Real Log: Training and Testing (to avoid data leakage and overfitting). Crisp vs Probabilistic: Models from Bayesian Optimizer – (bayes_opt).
- 13. Business Process Simulation 13 Real Logs
- 14. Summary 14 Proposal: A business process simulation approach with probabilistic resource availability Discovery Differentiated Probabilistic Resource Calendars, Discovery Differentiated Probabilistic Resource Performance Functions Probabilistic Business Process Simulation Engine Empirical Evaluation: Probabilistic models are more accurate than crisp models Future Work 1) Probabilistic Multitasking 2) Discover Seasonal and Non-periodical Availability Patterns
- 15. Discovery and Simulation of Business Processes with Probabilistic Resource Availability Calendars Orlenys López Pintado Marlon Dumas October 24, 2023 - ICPM’23 PIX Project Emoticons courtesy of Skype (© Microsoft Corporation) Thanks!!!