Role Of Business Process Management Research Articles

Beyond Optimization: The Evolving Role of Business Process Management in Industry Transformation

This article delves into the multifaceted realm of Business Process Management (BPM), exploring its historical evolution, transformative dimensions, and pivotal role in reshaping industries. Emphasizing the significance of BPM beyond mere optimization, the study examines the shift from traditional paradigms to holistic and innovative approaches, positioning the approach as a catalyst for enduring organizational transformation. Through a comparison of transformative aspects, case studies of companies showcase the diverse applications and positive outcomes of transformative BPM initiatives. The analysis extends to the evolving landscape of Industry 4.0-5.0, the integration of emerging technologies like AI, IoT, and Blockchain, and anticipated trends, highlighting BPM’s role as a strategic enabler for innovation, agility, and sustainability. Addressing challenges and proposing solutions in BPM-led transformations, the article provides insights into the dynamic and adaptive nature of approach implementations. Ultimately, this exploration contributes to a deeper understanding of BPM’s transformative potential and its profound impact on organizational excellence in the ever-evolving industrial landscape.

Creating AI business value through BPM capabilities

PurposeAlthough businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.Design/methodology/approachThe integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.FindingsThe results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.Research limitations/implicationsIn pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.Practical implicationsThe provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.Originality/valueWhile previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.

The Role of Business Process Management in Digital Innovation and Digital Transformation: A Systematic Literature Review

Business Process Management (BPM) is an approach that aims to improve organizational performance and flexibility through managing business processes. Digital Innovation (DI) and Digital Transformation (DT) are phenomena that relate to the use of digital technology to create new value for organizations and customers. This article explores the role of BPM in supporting DI and DT in organizations and how to implement BPM in an organization with a Systematic Literature Review (SLR). The search results, inclusion and exclusion criteria, and relevance assessment yielded 34 relevant articles. We found that BPM, DI, and DT interact with each other in various ways and have some theoretical and practical implications for researchers and practitioners.

Motivations to Adopt BPM in View of Digital Transformation

ABSTRACT We explore motivations for adopting Business Process Management (BPM) by analyzing 290 customer use cases published on-line by BPM systems vendors. We construct a classification framework of BPM motivations for the new challenges confronting BPM in the time of digital transformation, with highlights of the new role of BPM in this context. The proposed framework serves as a guide for future research on BPM motivation patterns, particularly in the context of digital transformation.

Customer relationship management and customer loyalty: Examining the mediating role of business process management

The purpose of this study is to investigate the impact of customer relationship management on customer loyalty (CL) at Jordan Telecommunication Company through business process management. The researcher uses the descriptive analytical method to scan members’ opinions. The random sample includes (367) workers from different sectors all over the country. The results show that customer relation management (CRM) has a dramatic impact on customer loyalty and business process management (BPM). Besides, BPM plays a vital role between CRM and CL. This study appears to be the first study in Jordan which empirically examines the indirect relationship between customer relation management and customer loyalty via business process management.

Method for Repairing Process Models with Selection Structures Based on Token Replay

Enterprise information systems (EIS) play an important role in business process management. Process mining techniques that can mine a large number of event logs generated in EIS become a very hot topic. There always exist some deviations between a process model of EIS and event logs. Therefore, a process model needs to be repaired. For the process model with selection structures, the mining accuracy of the existing methods is reduced because of the additional self-loops and invisible transitions. In this paper, a method for repairing Logical-Petri-nets-based process models with selection structures is proposed. According to the relationship between the input and output places of a sub-model, the deviation position is determined by a token replay method. Then, some algorithms are designed to repair the process models based on logical Petri nets. Finally, the effectiveness of the proposed method is illustrated by some experiments, and the proposed method has relatively high fitness and precision compared with its peers.

IT-CMF and BPM Critical Capability: Improving Software Development Lab on academic context

Abstract In order to generate better results, organizations are required to better manage and develop their processes. The role of Business Process Management (BPM) discipline and the exploitation of the organization’s Information Technology (IT) capabilities are perceived as important instruments to the improvement of business processes. An empirical study was conducted in the Software Development Lab of a Higher Education Institution using the Information Technology Capability Maturity Framework (IT-CMF) to diagnose the current BPM maturity level and to improve its processes. This Software Development Lab bridges the gap between academia and industry, developing students’ skills for the challenges of the workplace. One contribution to the study is a list of applied questions and their relationship with IT-CMF Capability Building Blocks that can serve as a basis for other practitioners. Another contribution is a list of actions to be performed by the Lab senior management to increase the maturity level of the Lab management of business processes.

An Enhanced LSTM Method to Improve the Accuracy of the Business Process Prediction

Prediction of the process behavior plays a key role in business process management. This research benefits from recent development in the field of deep learning to predict the next event in business processes. The proposed method uses Long Short-Term Memory (LSTM) as a promising architecture of recurrent neural networks. This architecture is implemented using a number of configurations with the aim of investigating how each of them affects the performance of the prediction models. In order to build and evaluate our prediction models, we used two publicly available datasets (BPI 2012 and BPI 2017). After developing 300 prediction models, the results indicated that the proposed method outperforms the state-of-the-art methods in terms of precision. The best result in terms of Accuracy (0.907) was achieved through “one-hidden” layer LSTM architecture and by using “Big” configuration in the absence of “feedback”.

Towards successful establishment of a project portfolio management system: business process management approach

Linking structures, processes and resources with corporate strategies is a key requirement of today’s organizations, bringing about integration toward achieving long-term objectives. Organizations can no longer rely on traditional practices since advanced systems and management approaches are being applied by their competitors. The project portfolio management (PPM) is a tool that plays a key role in collecting information from operational levels and consolidating them at the portfolio level for strategic decision-making. Establishment of this approach in organizations requires robust information systems, analytical software, decision-making structure, and governance framework to be in place. Primarily, a systematic perspective needs to be adopted to define, design and model all the necessary components of a PPM system. Business process management (BPM), as a systematic approach, can be effectively applied for this purpose. The aim of this study is to introduce one of the specific applications of the BPM approach in facilitating the systematic implementation of PPM in organizations. This theoretical study is exploratory in essence and tries to theorize the relationship between BPM and PPM to develop a conceptual framework highlighting the role of BPM in embedding all the necessary features of a PPM system. We found key functions of BPM that contribute to three aspects of PPM system namely; structure, infrastructure, and process. The findings introduce one of the important application of BPM in the management of project portfolios and also provide professionals with practical insight into how the BPM should be applied to facilitate the implementation of this system.

BPM motivations framework for digital challenges: lessons learned from customer use cases

Abstract In this paper we develop a BPM motivations framework for the era of digital transformation. An investigation of the motivations that trigger and guide Business Process Management (BPM) initiatives enabled us to examine whether these initiatives take advantage of the traditional understanding of BPM or of the emerging new perception of BPM in the time of digital transformation. This research is based on an analysis of 290 customer use cases published on-line by BPM systems vendors. We used the empirical/conceptual approach to framework development, basing the empirical analysis on a qualitative data-coding canon and conclusions from the literature regarding the role of BPM in the digital world. As a result of our research, we constructed a classification framework for BPM motivations that consists of four categories: operational and managerial motivations, IT-enabled motivations, customer centric motivations and motivations focused on digital transformation. In addition, we present the results of quantitative summaries for the distinguished categories and how they are embedded in the evolution of BPM. Our main contribution is the proposal of a framework of BPM motivations for the new challenges confronting BPM in the time of digital transformation, with highlights of the new role of BPM in this context. This framework serves as a guide for further research on BPM motivation patterns, particularly in the context of digital transformations.

Log automaton under conditions of infrequent behaviour mining

In the existing process mining methods, infrequent behaviours are often considered as noise is ignored, but some infrequent behaviours have an important role in business process management. Firstly, the knowledge of log automaton is applied to the low-frequency log to delete infrequent behaviour in the logs; secondly, the processed logs are added into attributes. Then, the condition-dependent value of the communication characteristics of different module networks is compared with the threshold, and the effective infrequent log is retained to optimise the model. Finally, a practical case is applied, which indicates the effectiveness and validation of the proposed method.

Log automaton under conditions of infrequent behaviour mining

In the existing process mining methods, infrequent behaviours are often considered as noise is ignored, but some infrequent behaviours have an important role in business process management. Firstly, the knowledge of log automaton is applied to the low-frequency log to delete infrequent behaviour in the logs; secondly, the processed logs are added into attributes. Then, the condition-dependent value of the communication characteristics of different module networks is compared with the threshold, and the effective infrequent log is retained to optimise the model. Finally, a practical case is applied, which indicates the effectiveness and validation of the proposed method.

Mastering digital transformation through business process management: Investigating alignments, goals, orchestration, and roles

Both business process management and digital transformation are areas that have been a topic of interest for both academia and practice. Since digital transformation is the creation of new, innovative business models and/or change and improvement of the existing business model with the help of digital technologies, one could raise a question regarding the role which business process management plays in digital transformation. With the purpose of shedding some light on that, this paper presents a theoretical framework for observing the link between business process management and digital transformation. Moreover, the results of an extensive literature review and analysis with regards to the presented framework has been given. The results confirm the important role of business process management in digital transformation. However, the results also indicate the need for further research and a greater understanding of practice.

The knowledge and process continuum

The aim of the paper is to propose the concept of the Knowledge and Process Continuum, which corresponds to the changing role of Business Process Management (BPM) in Knowledge Intensive Organizations in the Knowledge Economy. The paper is conceptual in nature and is grounded in the theories of Knowledge Management (KM) and BPM. The systematic literature review method was used in order to employ a manual search of peer‐reviewed papers available in the Springer and ProQuest databases. Seventeen articles were chosen for in‐depth analysis, which shows the research gap with respect to the integrated application of KM and BPM. The article is an inspiring contribution to the theoretical reflection on the current state and further evolution of BPM in the Knowledge Economy and its inseparable connection with KM. The proposed conceptual framework may facilitate the management of Knowledge Intensive Organizations to effectively capitalize on the relationship between knowledge and business processes of different nature.

From BPMN process models to DMN decision models

The interplay between process and decision models plays a crucial role in business process management, as decisions may be based on running processes and affect process outcomes. Often process models include decisions that are encoded through process control flow structures and data flow elements, thus reducing process model maintainability. The Decision Model and Notation (DMN) was proposed to achieve separation of concerns and to possibly complement the Business Process Model and Notation (BPMN) for designing decisions related to process models. Nevertheless, deriving decision models from process models remains challenging, especially when the same data underlie both process and decision models. In this paper, we explore how and to which extent the data modeled in BPMN processes and used for decision-making may be represented in the corresponding DMN decision models. To this end, we identify a set of patterns that capture possible representations of data in BPMN processes and that can be used to guide the derivation of decision models related to existing process models. Throughout the paper we refer to real-world healthcare processes to show the applicability of the proposed approach.

Detecting Difference Between Process Models Using Edge Network

Process difference detection has played an important role in business process management for enterprise applications. However, the business processes are becoming more and more complex, involving a wide spectrum of tasks and different types of execution orders among these tasks, such as sequential, parallel, loop and conditional order. Thus, there is a need to detect difference between two process models efficiently. To meet this requirement, we use a difference detection framework for process models based on edge computing, where the edges can perform the task of difference detection between two process models, and the difference detection results can be aggregated to the cloud center. Most existing approaches detect process difference based on one feature of a process model, while a process model actually contains multiple features such as structure, behavior, and performance. In this paper, we propose an approach that can detect both structural and behavioral differences between two process models, which provides two aspects of difference information to process analysts and these kinds of insights are helpful to improve the original process model with low-cost and high-efficiency. First, we transform the process models into their corresponding task-based process structure trees (TPSTs) and assign each TPST node a feature vector based on the one-hot encoding. Then, the common key structure of two process models is extracted by comparing the feature vectors of nodes. Finally, the structural and behavioral differences are displayed in terms of this common key structure. Both the case study and efficiency study are provided to show the practicality of the proposed approach.

A Comprehensive Process Similarity Measure Based on Models and Logs

Process similarity measure plays an important role in business process management and is usually considered as a versatile solution to fulfill the effective utilization of process models. Although many studies have worked on different notions of process similarity, most of them are not precise enough, as they simply compare processes with respect to the model structure features or the model behavior features separately. To address the problem, in this paper, we propose to measure the business process similarity by considering both process models and process logs. The process models are pre-defined descriptions of business processes, and the process logs can be considered as an objective observation of the actual process execution behavior. The combination of both can help to better character business processes. More specifically, two effective frameworks together with four novel approaches are presented. The former first constructs a weighted business process graph (WBPG) from the process model and the process log, and then computes the similarity of two corresponding WBPGs by using the weighted graph edit distance measure and the weighted node adjacent relation similarity measure. The latter first measures the similarity of process logs and the similarity of process models separately, and then merges the results. Finally, by experimental evaluation, we demonstrate the effectiveness and the applicability of the proposed approaches by comparing them with the start of the art.

Paradigms in business process management specifications: a critical overview

PurposeDespite its popularity, business process management (BPM) is not unequivocally defined, but obtains different forms with varying specifications. This paper presents a critical overview of BPM, as it appears within four dominant management paradigms: total quality management, standardized management systems, business process reengineering and Six Sigma. The purpose of this paper is to explore BPM specifications and compare the BPM implementation potential under each paradigm.Design/methodology/approachThis is based on the analysis of a large number of highly cited scholarly publications. In order to identify the nature of BPM within each paradigm, a common framework for comparison is first established and then, for each paradigm, BPM is analyzed according to the main parameters of this framework.FindingsMany differences among various BPM forms are paradigm driven. So, the approach adopted by each paradigm (i.e. individual-process or systemic approach) affects the scope and role of BPM. The principles of each paradigm directly affect the attributes assigned to BPM. Despite of important differences, the structure of BPM within all paradigms conforms to the stages of the classical BPM lifecycle. However, each paradigm assigns different weights to each stage and also displays different levels of BPM implementability.Originality/valueThe paper presents a first systematic comparison of BPM specifications for the dominant management paradigms primarily deployed. It thus explains why many attributes originating from the paradigms have crept into the general BPM specifications. This work can be considered as a step toward defining the core attributes of a paradigm-independent BPM model, thus enhancing its application scope as an invaluable management tool.

An Approach to Participatory Business Process Modeling: BPMN Model Generation Using Constraint Programming and Graph Composition

Designing business process models plays a vital role in business process management. The acquisition of such models may consume up to 60% of the project time. This time can be shortened using methods for the automatic or semi-automatic generation of process models. In this paper, we present a user-friendly method of business process composition. It uses a set of predefined constraints to generate a synthetic log of the process based on a simplified, unordered specification, which describes activities to be performed. Such a log can be used to generate a correct BPMN model. To achieve this, we propose the use of one of the existing process discovery algorithms or executing the activity graph-based composition algorithm, which generates the process model directly from the input log file. The proposed approach allows process participants to take part in process modeling. Moreover, it can be a support for business analysts or process designers in visualizing the workflow without the necessity to design the model explicitly in a graphical editor. The BPMN diagram is generated as an interchangeable XML file, which allows its further modification and adjustment. The included comparative analysis shows that our method is capable of generating process models characterized by high flow complexity and can support BPMN constructs, which are sufficient for about 70% of business cases.

The Role of Business Process Management in Driving Digital Transformation: Insurance Company Case Study

The Role of Business Process Management in Driving Digital Transformation: Insurance Company Case Study