Publicação
Towards Improving Business Processes based on preconfigured KPI target values, Process Mining and Redesign Patterns
| dc.contributor.author | Cherni, Jihen | |
| dc.contributor.author | Martinho, Ricardo | |
| dc.contributor.author | Ghannouchi, Sonia Ayachi | |
| dc.date.accessioned | 2026-07-22T15:44:52Z | |
| dc.date.available | 2026-07-22T15:44:52Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | The Business Process Management (BPM) lifecycle includes a redesign phase, which is an important step for stakeholders while working on the improvement of their Business Processes. Some research approaches on process improvement involve Key Performance Indicators and Process Mining, but essentially using the latter to verify if improvement efforts have been successful. In this paper, we propose a different approach for process improvement by first defining and configuring, process KPI target values, and second using Process Mining techniques to discover and analyze deviations from those values. Then, for each deviation we propose improvement solutions based on Business Process redesign patterns. Since this encompasses also an improvement cycle, we present our approach as an extension of the well-known BPM cycle. With this approach, process stakeholders will be able to quickly identify process KPI deviations based on quality, cost, time and flexibility, and resolve them by automatically applying proven redesign patterns. | eng |
| dc.identifier.citation | Jihen Cherni, Ricardo Martinho, Sonia Ayachi Ghannouchi, Towards Improving Business Processes based on preconfigured KPI target values, Process Mining and Redesign Patterns, Procedia Computer Science, Volume 164, 2019, Pages 279-284, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2019.12.184. | |
| dc.identifier.doi | 10.1016/j.procs.2019.12.184 | |
| dc.identifier.issn | 1877-0509 | |
| dc.identifier.uri | http://hdl.handle.net/10400.8/16659 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.publisher | Elsevier BV | |
| dc.relation.hasversion | https://www.sciencedirect.com/science/article/pii/S1877050919322239 | |
| dc.relation.ispartof | Procedia Computer Science | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Process Mining | |
| dc.subject | Business Process Improvement Patterns | |
| dc.subject | Key Performance Indicators | |
| dc.title | Towards Improving Business Processes based on preconfigured KPI target values, Process Mining and Redesign Patterns | eng |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 284 | |
| oaire.citation.startPage | 279 | |
| oaire.citation.title | Procedia Computer Science | |
| oaire.citation.volume | 164 | |
| oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
| person.familyName | Martinho | |
| person.givenName | Ricardo | |
| person.identifier.ciencia-id | F51E-9BB5-EF92 | |
| person.identifier.orcid | 0000-0003-1157-7510 | |
| person.identifier.rid | K-8277-2013 | |
| person.identifier.scopus-author-id | 25823103700 | |
| relation.isAuthorOfPublication | b2a74e46-f06c-4dcd-8c64-8f78f1d55440 | |
| relation.isAuthorOfPublication.latestForDiscovery | b2a74e46-f06c-4dcd-8c64-8f78f1d55440 |