Zusammenfassung
Klassische Geschäftsprozess-Managementsysteme, wie sie seit den 1990er-Jahren als WfMS (Workflow-Management-System), später dann auch als BPMS (Business-Process-Management-System) eingeführt wurden, fokussieren auf die Automatisierung von Routine-Geschäftsprozessen, deren Ablaufverhalten schon zur Entwurfszeit vom Prozessdesigner vollständig festgelegt wird. Diese Systeme eignen sich gut für Abläufe, die entlang eines vordefinierten Kontrollflusses beliebig oft in gleicher Art und Weise durchgeführt werden. Im Unterschied hierzu folgen wissensintensive Geschäftsprozesse keinem durchgängigen, strikt vorgegebenen Ablaufschema, sondern entwickeln sich, zumindest phasenweise, dynamisch zur Laufzeit, getrieben durch Prozessziele und kontextbasierte Entscheidungen der beteiligten Wissensarbeiter. Zur Unterstützung derartiger wissensintensiver Geschäftsprozesse sind flexible Geschäftsprozess-Managementsysteme erforderlich, die neben Routineabläufen auch emergente, durch (dynamisch veränderliche) Kontextbedingungen und Zielvorgaben getriebene Prozesse unterstützen.
In diesem Buchkapitel diskutieren wir wesentliche Anforderungen an die systemtechnische Unterstützung wissensintensiver Geschäftsprozesse und zeigen mögliche Lösungskonzepte und Implementierungsansätze auf.
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Notes
- 1.
- 2.
- 3.
- 4.
Kombination von Geschäft-, Entscheidungs- und Prozesslogik in einem gemeinsamen Programm.
- 5.
Ergänzend bieten Standardsoftwarehersteller in der Regel zusätzliche WfM- oder BPM-Werkzeuge für die Definition und Ausführung unternehmensindividueller Workflows an.
- 6.
Die Arbeitsweise von Wissensarbeitern wird im nachfolgenden Kapitel genauer charakterisiert. Für eine Detaildiskussion sei z. B. auf Davenport [11] verwiesen.
- 7.
Unter Aktivitäten verstehen wir hier Arbeitseinheiten, die im Rahmen eines Geschäftsprozesses ausgeführt werden. Aktivitäten können elementare Ausführungseinheiten (Tasks) oder auch Kombinationen davon (Teilprozesse) sein.
- 8.
Weitere, neben ACM und DCM aktuell genutzte Begriffe und Abkürzungen zur systemtechnischen Unterstützung wissensintensiver Geschäftsprozesse werden in [32] detailliert dargestellt.
- 9.
Zur Vereinfachung unterscheiden wir in diesem Beitrag nur dann explizit zwischen Prozess und Prozessinstanz, wenn dies für das Verständnis zwingend erforderlich erscheint.
- 10.
Der Kontextbegriff wird in der wissenschaftlichen Literatur keineswegs einheitlich interpretiert. Bazire und Brézillon [87] haben 150 verschiedene Definitionen identifiziert. Ihr Fazit: „…context acts like a set of constraints that influence the behavior of a system (a user or a computer) embedded in a given task … There is no consensus about the following questions: Is context external or internal? Is context a set of information or processes? Is context static or dynamic? Is context a simple set of phenomenon or an organized network?“
- 11.
Die aktuelle Prototyp-Umsetzung von ProSyWis erfolgt als lokale Anwendung. Zu einem späteren Zeitpunkt ist auch eine Implementierung als Multi-Tenant-Lösung in der Cloud angedacht (siehe [89]).
- 12.
Wir fassen hier die Funktionen der Engine (Ausführung) und des Enactment Services (Instanziierung, Modellinterpretation, …) unter dem Begriff Process Engine zusammen.
- 13.
Außerdem verfügt BPMN mit der Call Activity über einen Mechanismus, um globale Prozesse oder Tasks aufzurufen. Camunda hat ihre BPMN-Engine so erweitert, dass über Call Activities auch CMMN -Fragmente in einen BPMN-Prozess eingebunden werden können [95] (wird in ProSyWis gegenwärtig nicht genutzt).
- 14.
Für Entscheidungen, die innerhalb einer Aktivität getroffen werden müssen, sind z. B. die weiter unten genannten Verfahren des Operations Research nützlich. Zur Entwicklung geeigneter mathematischer Optimierungsmodelle und deren Lösung wird im Rahmen von ProSyWis gegenwärtig IBMs ILOG CPLEX Optimization Studio [96] eingesetzt.
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Buck-Emden, R., Alda, S. (2017). Systemunterstützung für wissensintensive Geschäftsprozesse – Konzepte und Implementierungsansätze. In: Barton, T., Müller, C., Seel, C. (eds) Geschäftsprozesse. Angewandte Wirtschaftsinformatik. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-17297-8_6
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