Pub. online:13 Jun 2022Type:Research ArticleOpen Access
Volume 33, Issue 2 (2022), pp. 399–420
The aim of the article is to identify drivers and limiters of the development of Business Process Management Systems (BPMS) from the point of view of the industry and the academia, and to formulate practical recommendations. Their identification is crucial in order to remove a considerable gap between the approach to knowledge-intensive business processes (kiBPs), which require dynamic management and are decisive with regard to the competitive position of the organization under the conditions of Industry 5.0, as well as the possibilities offered by ICT solution, and the current possibilities and needs of BPM practitioners. The authors applied a methodological approach based on a theoretical literature review and a review of practice through online structured expert interviews with key BPMS solution providers. According to the literature, the main drivers pertain to the enterprises’ efforts to reduce costs and improve their productivity and efficiency, develop technology, and enact changes in business models and business processes. According to vendors, the main drivers for the combination of BPMS and Case Management Systems (CMS) were the users’ expectations, technology identity, and further development perspectives. The main limiters of the decision to combine both classes of systems were technological problems predicted by vendors related to the unification of historically different technologies used in both classes of systems, as well as implementation-based problems related to the likely need to reconfigure the software environments of software users. The article formulated original recommendations for both vendors and users of iBPMS software, including the basic recommendation of the selection of the methodology of implementation of BPM and iBPMS in accordance with the context of the organization’s operations (the nature of its business processes).
Volume 31, Issue 3 (2020), pp. 579–595
One of the results of the evolution of business process management (BPM) is the development of information technology (IT), methodologies and software tools to manage all types of processes – from traditional, structured processes to unstructured processes, for which it is not possible to define a detailed flow as a sequence of tasks to be performed before implementation. The purpose of the article is to present the evolution of intelligent BPM systems (iBPMS) and dynamic case management/adaptive case management systems (DCMS/ACMS) and show that they converge into one class of systems, additionally absorbing new emerging technologies such as process mining, robotic process automation (RPA), or machine learning/artificial intelligence (ML/AI). The content of research reports on iBPMS and DCMS systems by Gartner and Forrester consulting companies from the last 10 years was analysed. The nature of this study is descriptive and based solely on information from secondary data sources. It is an argumentative paper, and the study serves as the arguments that relate to the main research questions. The research results reveal that under business pressure, the evolution of both classes of systems (iBPMS and DCMS/ACMS) tends to cover the functionality of the same area of requirements by enabling the support of processes of different nature. This de facto means the creation of one class of systems, although for marketing reasons, some vendors will still offer separate products for some time to come. The article shows that the main driver of unified software system development is not the new possibilities offered by IT, but the requirements imposed on BPM by the increasingly stronger impact of knowledge management (KM) with regard to the way business processes are executed. Hence the anticipation of the further evolution of methodologies and BPM supporting systems towards integration with KM and elements of knowledge management systems (KMS). This article presents an original view on the features and development trends of software systems supporting BPM as a consequence of knowledge economy (KE) requirements in accordance with the concept of dynamic BPM.