Elsevier

Expert Systems with Applications

Volume 38, Issue 10, 15 September 2011, Pages 12281-12292
Expert Systems with Applications

A fact-oriented ontological approach to human process modeling for knowledge-intensive business services

https://doi.org/10.1016/j.eswa.2011.04.006Get rights and content

Abstract

Modern business environment emphasizes the role of knowledge-intensive business services (KIBS). As well as the enterprises in any other kinds of industries, business process management (BPM) can be a source of core competency for the enterprises in KIBS industry. However, most of the business processes in KIBS are human processes which are collaborative, innovative, and dynamic, which cannot be supported well by current BPM technologies. Human interaction management (HIM) has emerged as an alternative theory to deal with human processes in KIBS. But, the current ways of process modeling and management in HIM have a problem of complexity, especially in terms of realizing its principle of ‘supportive activity management’. This research adopts fact-oriented ontological approach to address this problem. Based on fact-oriented approach, human-friendly condition modeling and state management during supportive activity management can be achieved.

Highlights

► Condition-based process modeling allows flexible execution of human processes. ► Suggested approach provides a human-friendly way for modeling conditions. ► Suggested approach provides a systematic way for state management in human processes.

Introduction

Modern business environment emphasizes the role of knowledge-intensive business services (KIBS) that promote the generation, diffusion and accumulation of knowledge within economic systems (Miles, Kastrinos, Flanagan, Bilderbeek, & den Hertog, 1995). In general terms, KIBS are mainly concerned with providing knowledge-intensive efforts to the business processes of other organizations, including clients of private and public sector (Muller & Doloreuz, 2007). Business consulting services, research and development services, marketing and communication services, software development services, legal services, human resource development services, and financing services are included as KIBS (Forssen, Keikkonen, Hietala, Hanninen, & Kontio, 2005).

Business process management (BPM) has emerged as a keyword to strengthen the capabilities of enterprises by organizing and managing business processes systematically (Pernici & Weske, 2006). As well as the enterprises in any other kinds of industries, BPM can be a source of core competency for the enterprises in KIBS industry, as they are integrated sets of knowledge-intensive business service processes. However, current BPM methodologies and solutions support the mechanistic, predetermined system-to-system scenarios with predefined workflow and inter-application transaction management only (Fingar, 2008), because current BPM techniques has traditionally focused on the automated coordination of business processes, examining how systems interact with each other and how the logic of business processes can be embedded into enterprise systems (Han, Kauranen, Kristola, & Merinen, 2007).

This is caused by ignoring human processes which require human creativeness such as researching, propositioning, negotiating, designing, scheduling, managing, analyzing and so on. These human processes are fundamentally collaborative, innovative, and dynamic unlike other mechanistic processes (Harrison-Broninski, 2005). In KIBS, most of business processes are such human processes. Because works for creating and dealing knowledge in KIBS are performed based on human creativeness, and the works requires human collaborations to share and deliver knowledge. Therefore, new theories of BPM which can adequately deal with human processes are required for managing and modeling processes in KIBS. An alternative to the requirement is human interaction management (HIM) (Harrison-Broninski, 2005).

HIM proposes variety of principles, features, concepts, and patterns which are specially devised for dealing with human processes. First of all, HIM adopts role-activity diagram (RAD) (Ould & Huckvale, 1995) for human-centered process modeling. And HIM suggests five key principles: (1) connection visibility, (2) structured messaging, (3) support mental work, (4) supportive (rather than prescriptive) activity management, and (5) processes change processes. Among them, this research focuses on ‘supportive activity management.’ Supportive activity management means that process models and process management should not restrict working activities of human processes rigidly. People do what they feel to be appropriate at the time, rather than sequence their activities as defined. So, sometimes they jump from one activity to another activity suddenly rather than go along the defined sequences. And human processes have dynamic feature and high changeability. Therefore, prescriptive and inflexible activity modeling and management are not appropriate for human processes. For supportive activity management, HIM suggests modeling activities in a declarative and flexible way, not a procedural way, using pre-conditions and post-conditions. Pre-conditions are used for enabling activities and post-conditions are used for checking completion of activities. And to support execution of processes, only enabled activities are notified to process participants based on the current state. Then, actual sequence of process execution is determined by participant at run-time.

However, current HIM theory provides only abstract ideas of using pre- and post-conditions for supportive activity management. That is, how the conditions are modeled for activities in process models and how the states of processes are managed for condition checking are not presented concretely. In HumanEdj, which is implemented for supportive activity management as an exemplary HIM System, pre- and post-conditions are modeled as attributes of activity elements of RADs using business rule technology. However, the rule scripts are too complex for business people, who are participants of human processes, to model conditions because they seems to be object-oriented programming codes. Moreover, the states of current process execution are managed manually by manipulating properties of modeling elements. Managing states in such way is not intuitive enough for process participants who change the states of their processes by executing the processes. Therefore, more human-friendly and easy ways of modeling conditions and managing states of processes to check the conditions are required to implement supportive activity management practically for modeling and managing human processes based on HIM. This research is to achieve this goal by adopting fact-oriented ontological approach to model and manage the conditions.

The objective of this research is to suggest the method of how pre-conditions and post-conditions can be modeled using fact-oriented ontological approach, especially using SBVR style ontologies, to support human-friendly condition modeling for supportive activity management of human processes. And this research deals with managing states of modeled processes based on the fact-oriented condition modeling.

In Section 2 of this paper, several related works are presented. In Section 3, current implementation of supportive activity management and the problems in it are shown. Then, a fact representation language used in this research is explained in Section 4. And a conceptual architecture of supportive activity management is provided in Section 5. In Section 6, state-transitions based on facts are discussed and illustrated with automatic state-transition mechanism based on derivation rules. Whole process modeling procedure based on fact-oriented ontologies is presented in Section 7 while Section 8 illustrates an exemplary scenario. Finally, this research is summarized and concluded in Section 9.

Section snippets

Related works

This research focuses on flexibility aspect of human process modeling and execution. Therefore, research works about declarative and flexible process modeling are presented as related works.

First of all, Goedertier and Vanthienen (2007) suggested a modeling approach for declarative business process modeling including vocabularies and execution models for it. In this work, processes are modeled as state spaces in terms of fact-types and rules that represent available trajectories in the spaces.

Supportive activity management of current HIM

As explained, current HIM theory recommend introducing pre-conditions and post-conditions for activity modeling to model activities declaratively for supportive activity management. A pre-condition of an activity means the state of affairs that is guaranteed to be the case for the activity to become available and a post-condition of an activity means the state of affairs that is guaranteed to be the case on completion of the activity (Harrison-Broninski, 2005). If activities are modeled with

Fact representation language based SBVR

As mentioned, this research suggests fact-oriented condition modeling method to complement the complexity of current condition modeling. For that, a way of fact modeling should be suggested first. The fact modeling language in this research is based on the Structured English in Semantics of Business Vocabulary and Business Rules (SBVR) (Management Group, 2008). Fig. 3 shows how the elements of the SBVR Structured English are expressed for this research.

As shown, the elements of SBVR Structured

Architecture for supportive activity management

Process executions for human processes are performed by humans rather than IT systems. Therefore, IT systems for supportive activity management in HIM environment, also called as HIMS, are implemented as process assistant software rather than process execution software. Fig. 4 describes the architecture of supportive activity management when HIMS are used for personal process assistants.

Three main building blocks of HIMS are RAD modeler, process manager, and communicator. Through RAD modeler,

Implicit state management based on state facts

As mentioned above, guiding a user through a process is based on states of the process. To manage the states of processes which are modeled using the fact-oriented process modeling approach of this research, using state facts that represent current state of processes is suggested. Using state facts means that states of process execution are managed and discriminated based on combinations of facts. This way of managing states seems correspond to HIM principles, as Harrison-Broninski said that

Procedure for fact-oriented human process modeling

The suggested fact-oriented human process modeling method for supportive activity management is based on the concepts and architecture which are introduced in Section 5 Architecture for supportive activity management, 6 Implicit state management and state-transitions based on state facts. Procedure for the fact-oriented human process modeling consists of 4 steps as follows.

An exemplary scenario

In this chapter, an exemplary scenario of state-transitions based on the process model in Fig. 1 is presented. In the scenario, several features of the supportive activity management which are realized by supportive activity modeling using pre-conditions and post-conditions are illustrated. The exemplary scenario in Fig. 15 is depicted with state facts and the RAD diagram of the process model which are assumed to be shown in user interface of HIMS in a state-by-state way.

Explanations about the

Conclusion

Supportive activity management in HIM theory can be an alternative human process modeling and management method for KIBS. And supportive activity management is achieved by using pre- and post-conditions for activities. However, modeling conditions in current HIM implementation has the problem of complexity. This is because pre- and post-conditions are modeled as attributes of activities using business rule technology, and the rule scripts are too complex for business people to model conditions.

Acknowledgement

This work was supported by the National Research Foundation of Korea (No. 2009-0079693).

References (21)

  • B. Pernici et al.

    Business process management

    Data and Knowledge Engineering.

    (2006)
  • S.W. Sadiq et al.

    Specification and validation of process constraints for flexible workflows

    Information Systems

    (2005)
  • Bentellis, A., & Boufaida, Z. (2008). Conceptual Method for Flexible Business Process Modeling. In Proceedings of World...
  • Bhat, J.M., & Deshmukh, N. (2005). Methods for Modeling Flexibility in Business Processes. In Proceedings of Business...
  • Dourish, P., Holms, J., MacLean, A., Marqvardsen, P., & Zbyslaw, A. (1996). Freeflow: mediating between representation...
  • Drools Rule Engine website,...
  • Fingar, P. (2008). Business Process Management: The Next Generation, BPTrands paper,...
  • Forssen, M., Keikkonen, M., Hietala, J., Hanninen, O., & Kontio, J. (2005). Knowledge-Intensive Service Activities...
  • S. Goedertier et al.

    Declarative process modeling with business vocabulary and business rules

    Lecture Notes in Computer Science

    (2007)
  • Y. Han et al.

    Human interaction management – adding human factors into business processes management special report for information systems integration

    (2007)
There are more references available in the full text version of this article.

Cited by (4)

  • A novel secure business process modeling approach and its impact on business performance

    2014, Information Sciences
    Citation Excerpt :

    This approach was adapted from the developed software engineering method in order to link the NFRs to the conceptual models. The author used the cancer registration process in Jordan as a case study of BPs in the healthcare area to show how the NRF graphing technique containing the goal operations and interaction analysis and goal evolution can be applied to create a NFR model for BPs by using a Role Activity Diagram (RAD) [2,52]. In [75], the authors proposed an approach to reuse the existing descriptions of BPs to analyze the security requirements and derive the required security measures.

  • Capturing cross-border logistics for analysis and improvement

    2022, Journal of Global Operations and Strategic Sourcing
  • A multi-layer framework for semantic modeling

    2020, Journal of Documentation
View full text