Efficacy-aware Business Process Modeling

In business process design, business objective models can fulfill the role of formal requirement definitions. Matching process models against objective models would, for instance, enable sound comparison of implementation alternatives. For that purpose, objective models should be available independently of their concrete implementation in a business process. This issue is not addressed by common business process management concepts yet. Moreover, process models are currently not sufficiently expressive to determine business process efficacy in the sense of fulfilling a business objective. Therefore, this paper develops and integrates constructs required for efficacy-aware process modeling and apt to extend common modeling approaches. The concept is illustrated with a sample scenario. Overall, it serves as an enabler for progressive applications like automated process optimization

Formalizing Concepts for Efficacy-aware Business Process Modeling

In business process design, business objective models can fulfill the role of formal requirement denitions. Matching process models against objective models would, for instance, enable sound comparison of implementation alternatives. For that purpose, objective models should be available independently of their concrete implementation in a business process. This issue is not addressed by common business process management concepts yet. Moreover, process models are currently not sufficiently expressive to determine business process efficacy in the sense of fulfilling a business objective. Therefore, this paper develops and integrates constructs required for efficacy-aware process modeling and apt to extend common modeling approaches. The concept is illustrated with a sample scenario. Overall, it serves as an enabler for progressive applications like automated process optimization

On the User Perception of Configurable Reference Process Models - Initial Insights

Enterprise Systems potentially lead to significant efficiency gains but require a well-conducted configuration process. A configurable reference modelling language based on the widely used EPC notation, which can be used to specify Configurable EPCs (C-EPCs), has been developed to support the task of Enterprise Systems configuration. This paper presents a laboratory experiment on C-EPCs and discusses empirical data on the comparison of C-EPCs to regular EPCs. Using the Method Adoption Model we report on modeller’s perceptions as to the usefulness and ease of use of C-EPCs, concluding that C-EPCs provide sufficient yet improvable conceptual support towards reference model configuration

Innovation and Self-Leadership: The Effects of Self-Leadership Knowledge on the Innovation Landscape

The open innovation landscape of today allows any individual the ability to work, use their creative ideas, and receive external ideas for innovation. Innovators are no longer the chosen few behind closed doors who are at the right level in an organization, at the right place, and at the right time. The open innovation environment requires individuals who are self-leaders with the skills and abilities to lead innovation projects. This study explores how the organizational position of individuals can affect how they feel about innovation and their perception of their innovative abilities. This information can help to guide organizations on where to focus self-leadership awareness and training and to match individuals with high innovator natural tendencies and perceptions with those in an organization that need to build their self-leadership skills for innovation

The Structured Process Modeling Method (SPMM) : what is the best way for me to construct a process model?

More and more organizations turn to the construction of process models to support strategical and operational tasks. At the same time, reports indicate quality issues for a considerable part of these models, caused by modeling errors. Therefore, the research described in this paper investigates the development of a practical method to determine and train an optimal process modeling strategy that aims to decrease the number of cognitive errors made during modeling. Such cognitive errors originate in inadequate cognitive processing caused by the inherent complexity of constructing process models. The method helps modelers to derive their personal cognitive profile and the related optimal cognitive strategy that minimizes these cognitive failures. The contribution of the research consists of the conceptual method and an automated modeling strategy selection and training instrument. These two artefacts are positively evaluated by a laboratory experiment covering multiple modeling sessions and involving a total of 149 master students at Ghent University

Knowledge-Intensive Processes: Characteristics, Requirements and Analysis of Contemporary Approaches

Engineering of knowledge-intensive processes (KiPs) is far from being mastered, since they are genuinely knowledge- and data-centric, and require substantial flexibility, at both design- and run-time. In this work, starting from a scientific literature analysis in the area of KiPs and from three real-world domains and application scenarios, we provide a precise characterization of KiPs. Furthermore, we devise some general requirements related to KiPs management and execution. Such requirements contribute to the definition of an evaluation framework to assess current system support for KiPs. To this end, we present a critical analysis on a number of existing process-oriented approaches by discussing their efficacy against the requirements

On the Interface Between Operations and Human Resources Management

Operations management (OM) and human resources management (HRM) have historically been very separate fields. In practice, operations managers and human resource managers interact primarily on administrative issues regarding payroll and other matters. In academia, the two subjects are studied by separate communities of scholars publishing in disjoint sets of journals, drawing on mostly separate disciplinary foundations. Yet, operations and human resources are intimately related at a fundamental level. Operations are the context that often explains or moderates the effects of human resource activities such as pay, training, communications and staffing. Human responses to operations management systems often explain variations or anomalies that would otherwise be treated as randomness or error variance in traditional operations research models. In this paper, we probe the interface between operations and human resources by examining how human considerations affect classical OM results and how operational considerations affect classical HRM results. We then propose a unifying framework for identifying new research opportunities at the intersection of the two fields