On the Differences Between Process Models by Novice and Expert Modellers

Viimase kümnekonna aasta jooksul on äriprotsesside modelleerimine saanud järjest suurema tähelepanu osaliseks, kuna see võimaldab ettevõtetel analüüsida, täiustada ja seirata äriprotsesse. Niisiis võimaldavad kvaliteetsed äriprotsesside mudelid firma efektiivsust tõsta. Senised uuringud on aga näidanud, et äriringkonnas kasutatavate mudelite kvaliteet varieerub kõvasti. Need uuringud on peaasjalikult keskendunud kogenud äriprotsesside loojatele, samas kui algajate tüüpilised vead on jäänud tähelepanuta. Just algajate tavalisemate vigade uurimine on aga kasulik, et tõhustada õppematerjalide arendamist. Käesolev töö sisaldab kahte uuringut, mille eesmärk on pakkuda vastuseid nendele küsimustele. Esimene neist uurib algajate poolt tehtud äriprotsesside mudeleid ja selgitab välja, milliseid vigu nad kõige enam teevad. Teine uuring võrdleb algajate ja professionaalide poolt tehtud mudeleid ja toob välja erinevused nende vahel.During the last decade, business process modelling has gained popularity as a way to make the processes of a company explicit and to support the analysis, improvement, implementation and monitoring of business processes. High-quality business process models can therefore support an organization in its continuous improvement efforts. Previous research however has found that the quality of business process models in commercial use is highly heterogeneous. These previous studies have largely focused on models produced by expert users, while the question of what typical errors are made by novice modellers has thus far been left relatively unexplored. Yet, insights into the question of typical errors of novice users (relative to expert ones) can inform the design of process modelling learning material. This thesis contains two studies aimed at providing some answers to the above question. The first part of this thesis examines process models produced by novices and investigates typical errors in their syntax and style. The second part aims at identifying differences between models of the same business process produced by expert vs. novice modellers

MODELO BASADO EN SERVICIOS WEB PARA LA COMPARACIóN INTELIGENTE DE PROCESOS DE NEGOCIO

El objetivo principal del artículo es proponer un modelo inteligente de comparación de procesos de negocio, para la propagación de cambios en variantes de procesos. El sistema fue desarrollado teniendo en cuenta dos componentes: una plataforma tecnológica basada en servicios web soportada por un sistema multiagente y un mecanismo de inferencia sensible al contexto. La validación del sistema se realizó sobre un caso de estudio relacionado con el proceso de admisiones a programas de educación superior en la Universidad Nacional de Colombia. Se puede concluir que la comparación de variantes puede verse afectada por información del contexto y que un enfoque distribuido soportado por servicios web y agentes inteligentes, facilita el uso del mecanismo de inferencia.PALABRAS CLAVES: Procesos de negocio, variantes, Comparación inteligente, Arquitectura orientada a servicios web, Servicios Web

Semantic Model Alignment for Business Process Integration

Business process models describe an enterprise’s way of conducting business and in this form the basis for shaping the organization and engineering the appropriate supporting or even enabling IT. Thereby, a major task in working with models is their analysis and comparison for the purpose of aligning them. As models can differ semantically not only concerning the modeling languages used, but even more so in the way in which the natural language for labeling the model elements has been applied, the correct identification of the intended meaning of a legacy model is a non-trivial task that thus far has only been solved by humans. In particular at the time of reorganizations, the set-up of B2B-collaborations or mergers and acquisitions the semantic analysis of models of different origin that need to be consolidated is a manual effort that is not only tedious and error-prone but also time consuming and costly and often even repetitive. For facilitating automation of this task by means of IT, in this thesis the new method of Semantic Model Alignment is presented. Its application enables to extract and formalize the semantics of models for relating them based on the modeling language used and determining similarities based on the natural language used in model element labels. The resulting alignment supports model-based semantic business process integration. The research conducted is based on a design-science oriented approach and the method developed has been created together with all its enabling artifacts. These results have been published as the research progressed and are presented here in this thesis based on a selection of peer reviewed publications comprehensively describing the various aspects

Ähnlichkeitsbasierte Suche in Geschäftsprozessmodelldatenbanken

Die Wiederverwendung von Prozessmodellen bietet sich zur Reduzierung des hohen Modellierungsaufwands an. Allerdings ist das Auffinden von ähnlichen Modellen in großen Modellsammlungen manuell nicht effizient möglich. Hilfreich sind daher Suchmöglichkeiten nach relevanten Modellen, die als Vorlage zur Modellierung genutzt werden können. In dieser Arbeit werden Ansätze beschrieben, um innerhalb von Prozessmodellbibliotheken nach ähnlichen Modellen und Aktivitäten zu suchen