TY - GEN
T1 - Narrowing the business-IT gap in process performance measurement
AU - van der Aa, Han
AU - Del-Río-Ortega, Adela
AU - Resinas, Manuel
AU - Leopold, Henrik
AU - Ruiz-Cortés, Antonio
AU - Mendling, Jan
AU - Reijers, Hajo A.
PY - 2016
Y1 - 2016
N2 - To determine whether strategic goals are met, organizations must monitor how their business processes perform. Process Performance Indicators (PPIs) are used to specify relevant performance requirements. The formulation of PPIs is typically a managerial concern. Therefore, considerable effort has to be invested to relate PPIs, described by management, to the exact operational and technical characteristics of business processes. This work presents an approach to support this task, which would otherwise be a laborious and time-consuming endeavor. The presented approach can automatically establish links between PPIs, as formulated in natural language, with operational details, as described in process models. To do so, we employ machine learning and natural language processing techniques. A quantitative evaluation on the basis of a collection of 173 real-world PPIs demonstrates that the proposed approach works well.
AB - To determine whether strategic goals are met, organizations must monitor how their business processes perform. Process Performance Indicators (PPIs) are used to specify relevant performance requirements. The formulation of PPIs is typically a managerial concern. Therefore, considerable effort has to be invested to relate PPIs, described by management, to the exact operational and technical characteristics of business processes. This work presents an approach to support this task, which would otherwise be a laborious and time-consuming endeavor. The presented approach can automatically establish links between PPIs, as formulated in natural language, with operational details, as described in process models. To do so, we employ machine learning and natural language processing techniques. A quantitative evaluation on the basis of a collection of 173 real-world PPIs demonstrates that the proposed approach works well.
KW - Model alignment
KW - Natural language processing
KW - Performance measurement
KW - Process performance indicators
UR - http://www.scopus.com/inward/record.url?scp=84976640067&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84976640067&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-39696-533
DO - 10.1007/978-3-319-39696-533
M3 - Conference contribution
AN - SCOPUS:84976640067
SN - 9783319396958
VL - 9694
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 543
EP - 557
BT - Advanced Information Systems Engineering - 28th International Conference, CAiSE 2016, Proceedings
PB - Springer - Verlag
T2 - 28th International Conference on Advanced Information Systems Engineering, CAiSE 2016
Y2 - 13 June 2016 through 17 June 2016
ER -