Printer Friendly

Dynamic aspects of business process modeling.

Introduction

Rolland et al. investigate the dynamic aspect of knowledge modeling (how enterprise knowledge models are generated and evolve and how reasoning about enterprise knowledge can guide the change process) and put forward an intentional framework known as the EKD-CMM approach (the confluence of two technologies: Enterprise Knowledge Modeling and Process Guidance). Koehler et al. write that the new languages make the communication and interaction structure of a business process explicit (WSFL and XLANG possess an operational semantics that enables the orchestration engine to directly execute the flow models specified in the language). A business process model is mapped into an IT flow model that can be regarded as a form of a high-level implementation language. The IT flow model provides a useful abstraction for business process mapping. Muehlen et al. investigate the representation capability of two rule modeling languages, viz., the Simple Rule Markup Language (SRML) and Semantics of Business Vocabulary and Business Rules (SBVR). Neiger et al. propose a conceptual framework that bridges the gap between the risk management and process management disciplines to provide business process analysts a foundation for their decisions regarding different process design scenarios. Hofferer focuses on the interoperability of business processes, and introduces the notion of a modeling technique that allows him to define the necessary components for the creation of models.

The use of an intentional framework for modeling organizational change

On Rolland et al.'s reading, the inter-connected set of EKD-CMM models describing an enterprise can be visualized in three levels of concern: Enterprise Goal Model, Enterprise Process Model and Enterprise Information System Model. Process guidance provides a set of applicable tasks that can be dynamically selected depending on the enactment context of the process. The decision to develop a software system forms part of the derived solution that meets stakeholder needs. Organizational stakeholders develop hypotheses as to the nature of the desired solution. The EKD-CMM enterprise goal model uses a 'network' of goals to express the causal structure of an enterprise. Change processes are intention-oriented (at any moment, change engineers act in order to fulfill an intention). Any reform requires a clear understanding (and a sharing of this understanding between many stakeholders) of the current enterprise situation. Rolland et al. identify the effect of future requirements on the current organizational structure thus providing a basis for a reasoned approach for future improvement, and alternative change scenarios indicating the type of organizational transformation necessary for satisfying future requirements. A major advantage of an iterative approach is the systematic way of dealing with change in terms of enterprise knowledge modeling used with a process guidance framework. The practical problems that Rolland et al. experience during the distribution application highlight significant issues that affect the application of a large number of knowledge modeling strategies. The route to be followed as well as its application in a particular change project is much dependent on the enactment context of the project. (1)

The representation of business process models

Koehler et al. discuss the representation of business process models and the need to make process requirements explicit, explore the pattern-based mapping of business models into automata-based IT models and the translation of process requirements into logical formulas, which can then be automatically verified using model checking techniques, and describe an iterative process of model correction/refinement and subsequent model checking until all process requirements have been verified. The various approaches for business process modeling and the tool sets implementing them have numerous features in common, and try to capture which business tasks are going to be automated, where the automating system is going to be deployed, who will use it, and how it will integrate with other systems.

Koehler et al. find the following typical elements in a business process modeling language: the organizational model describes the roles and areas of responsibilities within an organization with respect to the activities of a business process; the control flow describes the order of execution and the dependencies among the various activities; the data flow describes how the business entities are manipulated by the various activities; use cases describe the context of a business process and its externally visible behavior; collaboration diagrams can further document how business agents and artifacts work together to perform a function. The process requirements can usually only be described informally in the form of use cases or textual descriptions in some natural language. The process model must contain a specification of its requirements that includes the following properties: the requirement specification must be unambiguous; it must carry over to the IT model; it must be automatically verifiable in the IT model. Koehler et al. focus on typical structural patterns that occur frequently in business processes, map them to typical automata structures that provide the semantics of the IT model and the orchestration engine executing these models, and define typical properties of these patterns that are of particular interest and that are subject to an automatic verification. Many possible control patterns may be applicable in order to implement a business process. Providing pattern libraries extracted from best practices has the potential to facilitate and automate the difficult process of mapping a business model into an IT model. Koehler et al. choose a model based on two linked counting automata (Figure 1), using a general nondeterministic automata model with state variables and transition guards. The automaton interacts with the state variables in two ways: guards (a transition cannot occur unless a condition on one or more state variables holds) and assignments (a transition can modify the value of one or more state variables). Koehler et al. do not explicitly model the occurrence of external events, but capture their possible occurrence by the non-determinism in the automaton. The symbolic representation Koehler et al. use allows them to speak about sets of states instead of single states. The automaton in Figure 1 represents a refinement of the original business process model obtained by mapping the business pattern of two coupled, repetitive activities into the IT pattern of two linked counters.

[FIGURE 1 OMITTED]

Koehler et al. examine the possible traces of behavior implied by the model and verify global properties of the model: a reachability property states that a particular situation can sometimes be reached; a liveness property expresses that, under certain conditions, a situation will ultimately occur. Koehler et al. associate certain business process requirements with properties of the IT model that are subject to automatic verification. One can identify a property in the process, which can be described by a bounded and strictly monotonically decreasing function. (2)

Modeling languages for the specification of process models

Muehlen et al. assert that the modeling languages for the specification of process models can be classified according to their focal modeling construct: activity-centered (processes as a network of tasks or activities); process object centered (processes as the legal sequence of state changes of the process object), and resource centered (process as a network of processing stations that interact with each other). Muehlen et al. make use of the BWW representation model, together with the conduct of overlap analysis, in order to analyze the representational capabilities of SRML and SBVR, and focus on conceptual modeling languages rather than executable languages such as Business Process Execution Language (BPEL), and compare the representational capabilities of six languages, deriving a set of BWW representation model constructs that do not have a corresponding construct across the chosen languages. Muehlen et al. apply the process of overlap analysis in order to determine a pair of languages that provides the highest representation modeling power while having the lowest amount of construct overlap between the languages. The two chosen rule modeling languages are less expressive than their process modeling counterparts. Muehlen et al. show that the combination of BPMN with SRML provides users with the highest representation power while suffering an amount of construct overlap that is no higher than that of other language pairs. (3)

Integrating risk management practices into current business process management practices and methodologies

Neiger et al. emphasize that value-focused process engineering creates links between business processes and business objectives at the operational and strategic levels, and illustrate how Multiple Attribute Utility Theory can be used to address the need to document process-related risks and their relationships with goals, other risks, and other processes. The need for risk minimization should be expressed as one of the objectives contributing to the overall success of the relevant business process. Neiger et al.'s framework preserves the strengths of both the process engineering and decision sciences approaches to risk management, facilitating: (i) identification and representation of risks in a holistic business framework; (ii) articulation of the links between risk issues, business goals and business activities; and (iii) quantification and analysis of risk within the context of overall business objectives to facilitate "eyes-open" process design and evaluation. (4)

The combined use of metamodels and ontologies for achieving semantic interoperability of business processes

Hofferer claims that ontologies are a means to provide the vocabulary of an application domain that is then used for the creation of process models, and sees metamodels as provider of the syntax of a modeling language (all available modeling constructs are defined as well as valid ways to combine them). Ontologies can be used for the explication of both the semantics of activities in general as well as for describing the semantics of a specific activity. Semantic interoperability can only be achieved when both concepts (metamodels and ontologies) are used in combination. Metamodels and ontologies are different but complementary concepts. Hofferer see ontologies completely independent from the language concepts that are used to create the models that are to be integrated. Only a combination of metamodel type semantics together with inherent semantics from ontologies provides a means for semantically interoperable business process models. (5)

Conclusions

Rolland et al. reason that the change management process cannot be fully prescribed (in order to support the execution of change processes flexible guidelines are more relevant than rigid rules). Koehler et al. use a symbolic model checking procedure to enumerate exhaustively the set of possible reachable states underlying the process model. Muehlen et al. assume that each BWW representation model construct is equally important for the process modeling domain. Neiger et al. state that treating risks as business objectives allows for the direct application of the value-focused process engineering framework to the task of integration of risk and process management. Hofferer claims that the ontologies provide an external knowledge base that is basically completely independent from the metamodels.

REFERENCES

Hofferer, P. (2007), "Achieving Business Process Model Interoperability Using Metamodels and Ontologies," Proceedings of the 15th European Conference on Information Systems, St. Gallen: 1620-1631.

Koehler, J. et al., (2002), "From Business Process Model to Consistent Implementation: A Case for Formal Verification Methods," Proceedings of the 6th International Enterprise Distributed Object Computing Conference: 96-105.

Muehlen, M. (2007), "Business Process and Business Rule Modeling: A Representational Analysis," Proceedings of the 3rd International Workshop on Vocabularies, Ontologies and Rules for The Enterprise, IEEE, Baltimore: 127-132.

Neiger, D. et al. (2006), "Integrating Risks in Business Process Models with Value Focused Process Engineering," Proceedings of the 14th European Conference on Information Systems, AIS, Goteborg.

Rolland, C., et al. (1999), "Intention Based Modeling of Organizational Change: An Experience Report," 4th CAISE/IFIP 8.1 International Workshop on Evaluation of Modeling Methods in Systems Analysis and Design, Heidelberg.

DRAGOS MIHAI IPATE

dragos.ipate@spiruharet.ro

Spiru Haret University

IULIANA PARVU

iulia.parvu@yahoo.com

Spiru Haret University
COPYRIGHT 2011 Addleton Academic Publishers
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2011 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Title Annotation:PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON BUSINESS AND ECONOMY
Author:Ipate, Dragos Mihai; Parvu, Iuliana
Publication:Economics, Management, and Financial Markets
Date:Mar 1, 2011
Words:1910
Previous Article:Customers' satisfaction evaluation on quality of food services provided by the President Restaurant of the Black Sea Business Center Mangalia.
Next Article:Changes study in the electrical energy distribution branch.

Terms of use | Privacy policy | Copyright © 2019 Farlex, Inc. | Feedback | For webmasters