Decision-Making Support for Input Data in Business Processes according to Former Instances
- NAVER LABS Europe
6 Chemin de Maupertuis, 38240 Meylan, France
jm.perez@naverlabs.com - Universidad Loyola Andalucı́a
Avda. de las Universidades s/n. 41704 Dos Hermanas (Sevilla), España
mlparody@uloyola.es - Universidad de Sevilla
Av. Reina Mercedes s/n, 41012 Sevilla, España
{maytegomez,gasca}@us.es - Universita’ degli Studi di Milano
Via Festa del Perdono, 7, 20122 Milano, Italy
paolo.ceravolo@unimi.it
Abstract
Business Processes facilitate the execution of a set of activities to achieve the strategic plans of a company. During the execution of a business process model, several decisions can be made that frequently involve the values of the input data of certain activities. The decision regarding the value of these input data concerns not only the correct execution of the business process in terms of consistency, but also the compliance with the strategic plans of the company. Smart decision-support systems provide information by analyzing the process model and the business rules to be satisfied, but other elements, such as the previous temporal variation of the data during the former executed instances of similar processes, can also be employed to guide the input data decisions at instantiation time. Our proposal consists of learning the evolution patterns of the temporal variation of the data values in a process model extracted from previous process instances by applying Constraint Programming techniques. The knowledge obtained is applied in a Decision Support System (DSS) which helps in the maintenance of the alignment of the process execution with the organizational strategic plans, through a framework and a methodology. Finally, to present a proof of concept, the proposal has been applied to a complete case study.
Key words
Business processes, Input Data, Decision-making support, Evolution Models of variables, Constraint Programming, Process Instance Compliance
Digital Object Identifier (DOI)
https://doi.org/10.2298/CSIS200522051P
Publication information
Volume 18, Issue 3 (June 2021)
Year of Publication: 2021
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium
Full text
Available in PDF
Portable Document Format
How to cite
4, J. M. P. Á. 1. ,. L. P. 2. ,. M. T. G. 3. ,. R. M. G. 3. ,. a. P. C.: Decision-Making Support for Input Data in Business Processes according to Former Instances. Computer Science and Information Systems, Vol. 18, No. 3, 835–865. (2021), https://doi.org/10.2298/CSIS200522051P