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Authors: Luis Galdo Seara and Renata Medeiros de Carvalho

Affiliation: Eindhoven University of Technology and The Netherlands

Keyword(s): Outcome Prediction, Time Remaining Prediction, Transition Systems, Process Mining, Data Mining.

Abstract: Some business processes are critical to organizations. The efficiency at which involved tasks are performed define the quality of the organization. Detecting where bottlenecks occur during the process and predicting when to dedicate more resources to a specific case can help to distribute the work load in a better way. In this paper we propose an approach to analyze a business process, predict the outcome of new cases and the time for its completion. The approach is based on a transition system. Two models are then developed for each state of the transition system, one to predict the outcome and another to predict the time remaining until completion. We experimented with a real life dataset from a financial department to demonstrate our approach.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Galdo Seara, L. and Medeiros de Carvalho, R. (2019). An Approach for Workflow Improvement based on Outcome and Time Remaining Prediction. In Proceedings of the 7th International Conference on Model-Driven Engineering and Software Development - MODELSWARD; ISBN 978-989-758-358-2; ISSN 2184-4348, SciTePress, pages 475-482. DOI: 10.5220/0007577504750482

@conference{modelsward19,
author={Luis {Galdo Seara}. and Renata {Medeiros de Carvalho}.},
title={An Approach for Workflow Improvement based on Outcome and Time Remaining Prediction},
booktitle={Proceedings of the 7th International Conference on Model-Driven Engineering and Software Development - MODELSWARD},
year={2019},
pages={475-482},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007577504750482},
isbn={978-989-758-358-2},
issn={2184-4348},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Model-Driven Engineering and Software Development - MODELSWARD
TI - An Approach for Workflow Improvement based on Outcome and Time Remaining Prediction
SN - 978-989-758-358-2
IS - 2184-4348
AU - Galdo Seara, L.
AU - Medeiros de Carvalho, R.
PY - 2019
SP - 475
EP - 482
DO - 10.5220/0007577504750482
PB - SciTePress