A new research paper analyzes the inherent difficulty in detecting delays within business processes, a task crucial for organizations to avoid missed deadlines. The study reveals that remaining time predictions in business processes are typically right-skewed, with most models performing well on common delays but poorly on the critical, large-delay cases. The research also identifies increased predictive uncertainty correlating with larger delays, suggesting that uncertainty-aware modeling could be a promising avenue for future predictive process monitoring. AI
IMPACT Provides new insights into the sources of difficulty in delay detection and identifies uncertainty-aware modeling as a promising direction for future PPM research.
RANK_REASON Academic paper on a specific AI/ML research problem. [lever_c_demoted from research: ic=1 ai=1.0]
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