Showing papers on "Business Process Model and Notation published in 2017"

Business Process Variability Modeling: A Survey

Abstract: It is common for organizations to maintain multiple variants of a given business process, such as multiple sales processes for different products or multiple bookkeeping processes for different countries. Conventional business process modeling languages do not explicitly support the representation of such families of process variants. This gap triggered significant research efforts over the past decade, leading to an array of approaches to business process variability modeling. In general, each of these approaches extends a conventional process modeling language with constructs to capture customizable process models. A customizable process model represents a family of process variants in a way that a model of each variant can be derived by adding or deleting fragments according to customization options or according to a domain model. This survey draws up a systematic inventory of approaches to customizable process modeling and provides a comparative evaluation with the aim of identifying common and differentiating modeling features, providing criteria for selecting among multiple approaches, and identifying gaps in the state of the art. The survey puts into evidence an abundance of customizable process-modeling languages, which contrasts with a relative scarcity of available tool support and empirical comparative evaluations.

Discovering digital business models in traditional industries

Abstract: Purpose The purpose of this paper is to provide managers from traditional industries with a blueprint to systematically analyze and discover digital business models and, thus, better cope with the digital transformation of their industrial businesses. Design/methodology/approach The proposed blueprint is built on state-of-the-art research on digital business model innovation and a rigorous taxonomy-building approach. The process is demonstrated through a simplified case study of a passenger transport company. Findings The process involves three steps: identifying existing products and services, deconstructing business models and discovering new configurations. The managers from the case company very positively evaluated the efficiency and effectiveness of the proposed procedure. Originality/value The proven methodology relates the generic components of digital business models to a specific firm’s context, listing the solution space for each relevant dimension. The resulting framework aids in better understanding the existing business models and serves as a tool for the systematic discovery of new models.

How Does Business Analytics Contribute to Business Value

Abstract: This paper presents a model, synthesized from the literature, of factors that explain how business analytics contributes to business value. It also reports results from a preliminary assessment of that model. The model consists of two parts: a process and a variance model. The process model depicts the analyze-insight-decision-action process through which use of an organization's business analytic capabilities is intended to create business value. The variance model proposes that the five factors in Davenport et al.'s DELTA model of business analytics success factors, six from Watson & Wixom and three from Seddon et al.'s model of organizational benefits from enterprise systems, assist a firm to gain business value from business analytics. A preliminary assessment of the model was conducted using data from 100 customer success stories from vendors such as IBM, SAP and Teradata. Our conclusion is that the business analytics success model is likely to be a useful basis for future research.

The business model pattern database — a tool for systematic business model innovation

Abstract: Companies are more frequently seen shifting their focus from technological innovation towards business model innovation. One efficient option for business model innovation is to learn from existing solutions, i.e., business model patterns. However, the various understandings of the business model pattern concept are often confusing and contradictory, with the available collections incomplete, overlapping, and inconsistently structured. Therefore, the rich body of literature on business model patterns has not yet reached its full potential for both practical application as well as theoretic advancement. To help remedy this, we conduct an exhaustive review, filter for duplicates, and structure the patterns along several dimensions by applying a rigorous taxonomy-building approach. The resulting business model pattern database allows for navigation to the relevant set of patterns for a specific impact on a company’s business model. It can be used for systematic business model innovation, which we illustrate via a simplified case study.

Bridging the gap between decision-making and emerging big data sources

Abstract: With the emergence of big data and new data sources, a challenge posed to today's organizations consists of identifying how to align their decision-making and organizational processes to data that could help them make better-informed decisions. This paper presents a study in the context of disaster management in Brazil that applies oDMN+, a framework that connects decision-making with data sources through an extended modeling notation and a modeling process. The study results revealed that the framework is an effective approach for improving the understanding of how to leverage big data in the organization's decision-making. An extended model-based framework connects decision-making to big data sources.A better understanding of decision-making is achieved with the framework.A modeling process is outlined for systematically using the framework in practice.Decision-making can be improved through the use of standard models and notations.Lessons were learned from a case study on a Brazilian disaster early-warning center.

Process mining using BPMN: relating event logs and process models

Abstract: Process-aware information systems (PAIS) are systems relying on processes, which involve human and software resources to achieve concrete goals. There is a need to develop approaches for modeling, analysis, improvement and monitoring processes within PAIS. These approaches include process mining techniques used to discover process models from event logs, find log and model deviations, and analyze performance characteristics of processes. The representational bias (a way to model processes) plays an important role in process mining. The BPMN 2.0 (Business Process Model and Notation) standard is widely used and allows to build conventional and understandable process models. In addition to the flat control flow perspective, subprocesses, data flows, resources can be integrated within one BPMN diagram. This makes BPMN very attractive for both process miners and business users, since the control flow perspective can be integrated with data and resource perspectives discovered from event logs. In this paper, we describe and justify robust control flow conversion algorithms, which provide the basis for more advanced BPMN-based discovery and conformance checking algorithms. Thus, on the basis of these conversion algorithms low-level models (such as Petri nets, causal nets and process trees) discovered from event logs using existing approaches can be represented in terms of BPMN. Moreover, we establish behavioral relations between Petri nets and BPMN models and use them to adopt existing conformance checking and performance analysis techniques in order to visualize conformance and performance information within a BPMN diagram. We believe that the results presented in this paper can be used for a wide variety of BPMN mining and conformance checking algorithms. We also provide metrics for the processes discovered before and after the conversion to BPMN structures. Cases for which conversion algorithms produce more compact or more complicated BPMN models in comparison with the initial models are identified.

Split Miner: Discovering Accurate and Simple Business Process Models from Event Logs

Abstract: The problem of automated discovery of process models from event logs has been intensively researched in the past two decades. Despite a rich field of proposals, state-of-the-art automated process discovery methods suffer from two recurrent deficiencies when applied to real-life logs: (i) they produce large and spaghetti-like models; and (ii) they produce models that either poorly fit the event log (low fitness) or highly generalize it (low precision). Striking a tradeoff between these quality dimensions in a robust and scalable manner has proved elusive. This paper presents an automated process discovery method that produces simple process models with low branching complexity and consistently high and balanced fitness, precision and generalization, while achieving execution times 2-6 times faster than state-of-the-art methods on a set of 12 real-life logs. Further, our approach guarantees deadlock-freedom for cyclic process models and soundness for acyclic. Our proposal combines a novel approach to filter the directly-follows graph induced by an event log, with an approach to identify combinations of split gateways that accurately capture the concurrency, conflict and causal relations between neighbors in the directly-follows graph.

A Guidelines framework for understandable BPMN models

Abstract: Business process modeling allows abstracting and reasoning on how work is structured within complex organizations. Business process models represent blueprints that can serve different purposes for a variety of stakeholders. For example, business analysts can use these models to better understand how the organization works; employees playing a role in the process can use them to learn the tasks that they are supposed to perform; software analysts/developers can refer to the models to understand the system-as-is before designing the system-to-be. Given the variety of stakeholders that need to interpret these models, and considering the pivotal function that models play within organizations, understandability becomes a fundamental quality that need to be taken into particular account by modelers. In this paper we provide a set of fifty guidelines that can help modelers to improve the understandability of their models. The work focuses on the Business Process Modelling Notation 2.0 standard published by the Object Management Group, which has acquired a clear predominance among the modeling notations for business processes. Guidelines were derived by means of a thoughtful literature review – which allowed identifying around one hundred guidelines – and through successive activities of synthesis and homogenization. In addition, we implemented a freely available open source tool, named B EBoP (understandaBility vErifier for Business Process models), to check the adherence of a model to the guidelines. Finally, guidelines violation has been checked with B EBoP on a dataset of 11,294 models available in a publicly accessible repository. Our tests show that, although the majority of the guidelines are respected by the models, some guidelines, which are recognized as fundamental by the literature, are frequently violated.

PSS business model conceptualization and application

Abstract: The discussion about business models has gained considerable attention in the last decade. Business model frameworks have been developed in the literature as management methods helping companies to comprehend and analyse their current business logic and guide the deployment of new strategies. In response to calls for a deeper understanding of the application of a business model approach to product-service systems (PSS), this study develops a two-level hierarchical framework that (i) includes a set of components with pertinent, second-order variables to take into account when undergoing the shift from products to solutions; (ii) supports industrial companies, especially SMEs, in designing their future business model and in consistently planning the actions needed to implement it. The framework was applied and refined within real-life settings. The application to KINE – a robot solutions supplier – shows how key challenges faced by servitization firms may be thoroughly addressed through the adoption...

Process querying: Enabling business intelligence through query-based process analytics

Abstract: The volume of process-related data is growing rapidly: more and more business operations are being supported and monitored by information systems. Industry 4.0 and the corresponding industrial Internet of Things are about to generate new waves of process-related data, next to the abundance of event data already present in enterprise systems. However, organizations often fail to convert such data into strategic and tactical intelligence. This is due to the lack of dedicated technologies that are tailored to effectively manage the information on processes encoded in process models and process execution records. Process-related information is a core organizational asset which requires dedicated analytics to unlock its full potential. This paper proposes a framework for devising process querying methods, i.e., techniques for the (automated) management of repositories of designed and executed processes, as well as models that describe relationships between processes. The framework is composed of generic components that can be configured to create a range of process querying methods. The motivation for the framework stems from use cases in the field of Business Process Management. The design of the framework is informed by and validated via a systematic literature review. The framework structures the state of the art and points to gaps in existing research. Process querying methods need to address these gaps to better support strategic decision-making and provide the next generation of Business Intelligence platforms.

Application fields for the new Object Management Group (OMG) Standards Case Management Model and Notation (CMMN) and Decision Management Notation (DMN) in the perioperative field

Abstract: Medical processes can be modeled using different methods and notations Currently used modeling systems like Business Process Model and Notation (BPMN) are not capable of describing the highly flexible and variable medical processes in sufficient detail We combined two modeling systems, Business Process Management (BPM) and Adaptive Case Management (ACM), to be able to model non-deterministic medical processes We used the new Standards Case Management Model and Notation (CMMN) and Decision Management Notation (DMN) First, we explain how CMMN, DMN and BPMN could be used to model non-deterministic medical processes We applied this methodology to model 79 cataract operations provided by University Hospital Leipzig, Germany, and four cataract operations provided by University Eye Hospital Tuebingen, Germany Our model consists of 85 tasks and about 20 decisions in BPMN We were able to expand the system with more complex situations that might appear during an intervention An effective modeling of the cataract intervention is possible using the combination of BPM and ACM The combination gives the possibility to depict complex processes with complex decisions This combination allows a significant advantage for modeling perioperative processes

A Recommendation System to Facilitate Business Process Modeling

Abstract: This paper presents a system that utilizes process recommendation technology to help design new business processes from scratch in an efficient and accurate way. The proposed system consists of two phases: 1) offline mining and 2) online recommendation. At the first phase, it mines relations among activity nodes from existing processes in repository, and then stores the extracted relations as patterns in a database. At the second phase, it compares the new process under construction with the premined patterns, and recommends proper activity nodes of the most matching patterns to help build a new process. Specifically, there are three different online recommendation strategies in this system. Experiments on both real and synthetic datasets are conducted to compare the proposed approaches with the other state-of-the-art ones, and the results show that the proposed approaches outperform them in terms of accuracy and efficiency.

Evaluating the effect of best practices for business process redesign

Abstract: The management of business processes in modern times is rapidly shifting towards being evidence-based. Business process evaluation indicators tend to focus on process performance only, neglecting the definition of indicators to evaluate other concerns of interest in different phases of the business process lifecycle. Moreover, they usually do not discuss specifically which data must be collected to calculate indicators and whether collecting these data is feasible or not. This paper proposes a business process assessment framework focused on the process redesign lifecycle phase and tightly coupled with process mining as an operational framework to calculate indicators. The framework includes process performance indicators and indicators to assess whether process redesign best practices have been applied and to what extent. Both sets of indicators can be calculated using standard process mining functionality. This, implicitly, also defines what data must be collected during process execution to enable their calculation. The framework is evaluated through case studies and a thorough comparison against other approaches in the literature. This paper presents a methodology to assess the effects accrued by BPR initiatives.The methodology provides evaluation measures to identify implementation and assess improvements.The methodology defines how evaluation measures are calculated using process mining.A couple of case studies demonstrates the applicability of the proposed methodology.

Probabilistic Model Checking-Based Service Selection Method for Business Process Modeling

Abstract: Business process modeling is a way to the organizational change management, which provides abstract workflows to describe business logics for customer demands analysis and IT infrastructures improv...

Survey of business process management: challenges and solutions

Abstract: The current literature shows that creating a good framework on business process model (PM) is not an easy task. A successful business PM should have the ability to ensure accurate alignment between...

Linking Data and BPMN Processes to Achieve Executable Models

Abstract: We describe a formally well founded approach to link data and processes conceptually, based on adopting UML class diagrams to represent data, and BPMN to represent the process. The UML class diagram together with a set of additional process variables, called Artifact, form the information model of the process. All activities of the BPMN process refer to such an information model by means of OCL operation contracts. We show that the resulting semantics while abstract is fully executable. We also provide an implementation of the executor.

Designing secure business processes with SecBPMN

Abstract: Modern information systems are increasingly large and consist of an interplay of technical components and social actors (humans and organizations). Such interplay threatens the security of the overall system and calls for verification techniques that enable determining compliance with security policies. Existing verification frameworks either have a limited expressiveness that inhibits the specification of real-world requirements or rely on formal languages that are difficult to use for most analysts. In this paper, we overcome the limitations of existing approaches by presenting the SecBPMN framework. Our proposal includes: (1) the SecBPMN-ml modeling language, a security-oriented extension of BPMN for specifying composite information systems; (2) the SecBPMN-Q query language for representing security policies; and (3) a query engine that enables checking SecBPMN-Q policies against SecBPMN-ml specifications. We evaluate our approach by studying its understandability and perceived complexity with experts, running scalability analysis of the query engine, and through an application to a large case study concerning air traffic management.

Designing Business Models for the Digital Economy

Abstract: Digital technologies are increasingly shifting the boundaries between everybody’s lives and information technology urging companies worldwide to address this vital topic. This requires a systematic approach to business model innovations, treating technical and business aspects in an integrated way. Currently one of the difficulties of such an approach is the lack of a common conceptualization to be used by both business and technology experts. The current chapter attempts to remedy this based on the interconnection of nine components of business model representation and five ‘Digital Key Elements’. The elements of the resulting matrix are called ‘Digital Value Drivers’; these describe the effect each digital key element has upon the various business model components. This matrix is transformed into a graphical representation and used in SAP Business Model Development and Implementation (BMDI) method to be then applied in Design Thinking workshops. BMDI is an iterative multi-step method aimed at designing innovative business models. Examples illustrate how the conceptualization is applied and how it enables to proceed from a digital business model design to an implementation in terms of ‘Service Design’; this includes persona development, customer journey map and service blueprint. Through this procedure we have obtained an integrated methodology for the systematic development of digital business models.

A participative end-user method for multi-perspective business process elicitation and improvement

Abstract: A business process can be characterized by multiple perspectives (intentional, organizational, operational, functional, interactional, informational, etc). Business process modeling must allow different stakeholders to analyze and represent process models according to these different perspectives. This representation is traditionally built using classical data acquisition methods together with a process representation language such as BPMN or UML. These techniques and specialized languages can easily become hard, complex and time consuming. In this paper, we propose ISEA, a participative end-user modeling approach that allows the stakeholders in a business process to collaborate together in a simple way to communicate and improve the business process elicitation in an accurate and understandable manner. Our approach covers the organizational perspective of business processes, exploits the information compiled during the elicitation of the organizational perspective and touches lightly an interactional perspective allowing users to create customized interface sketches to test the user interface navigability and the coherence within the processes. Thus, ISEA can be seen as a participative end-user modeling approach for business process elicitation and improvement.

Evaluating the impact of smart technologies on harbor’s logistics via BPMN modeling and simulation

Abstract: A smart Information and Communication Technology (ICT) enables a synchronized interplay of different key factors, aligning infrastructures, consumers, and governmental policy-making needs. In the harbor’s logistics context, smart ICT has been driving a multi-year wave of growth. Although there is a standalone value in the technological innovation of a task, the impact of a new smart technology is unknown without quantitative analysis methods on the end-to-end process. In this paper, we first present a review of the smart ICT for marine container terminals, and then we propose to evaluate the impact of such smart ICT via business process model and notation (BPMN) modeling and simulation. The proposed approach is discussed in a real-world modeling and simulation analysis, made on a pilot terminal of the Port of Leghorn (Italy).

Eye Tracking Experiments on Process Model Comprehension: Lessons Learned

Abstract: For documenting business processes, there exists a plethora of process modeling languages In this context, graphical process models are used to enhance the process comprehensibility of the stakeholders involved The large number of available modeling languages, however, aggravates process model comprehension and increases the knowledge gap between domain and modeling experts Upon this, one major challenge is to identify factors fostering the comprehension of process models This paper discusses the experiences we gathered with the use of eye tracking in experiments on process model comprehension and the lessons learned in this context The objective of the experiments was to study the comprehension of process models expressed in terms of four different modeling languages (ie, BPMN, eGantt, EPC, and Petri Net) This paper further provides recommendations along nine identified categories that can foster related experiments on process model comprehension

Soundness of Decision-Aware Business Processes

Abstract: With the recent release of the Decision Model and Notation (DMN) specification, standardized decision models can be designed to represent the decisions required for executing business processes. Outsourcing decision logic from process to decision models leads to a separation of concerns and therefore to decision-aware business processes. However, no exhaustive considerations regarding the soundness of the integration of the two types of models have been made so far. Classical soundness checking only looks at the control-flow of a process model. In this paper, we formally define soundness criteria for decision-aware processes that ensure that the process can continue after a decision has been taken, and that all activities following the decision can be executed. A scalable implementation and an analysis of models from participants of an online course on process and decision modeling as well as a from a BPM project of a large insurance company demonstrate the benefits of our contribution.

PE-BPMN: Privacy-Enhanced Business Process Model and Notation

Abstract: Privacy Enhancing Technologies (PETs) play an important role in preventing privacy leakage of data along information flows. Although business process modelling is well-suited for expressing stakeholder collaboration and process support by technical solutions, little is done to visualise and analyse privacy leakages in the processes. We propose PE-BPMN – privacy-enhanced extensions to the BPMN language for capturing data leakages. We demonstrate its feasibility in the mobile app scenario where private data leakages are determined. Our approach helps system builders make decisions on the privacy solutions at the early stages of development and lets auditors analyse existing systems.

Modeling business motivation and underlying processes for RAMI 4.0-aligned cyber-physical production systems

Abstract: Industry 4.0 is one of the most prominent initiatives towards the vision of smart manufacturing to foster efficiency and synergy among suppliers, producers, and customers. It will transform the production systems into a smart, fully integrated, and optimized cyber-physical production systems (CPPS) based on technology enablers such as Internet of Things (IoT). Moreover, the availability of a wide range of data and information in the context of CPPS provides a huge possibility to create novel business opportunities. However, for these business opportunities to materialize successfully there is an evident need to have an efficient communication and clear visualization of the new strategies and the underlying operational process among all the stakeholders involved in the manufacturing value chain. In this paper, we propose a model-based approach for creating and communicating business strategies (mission, goals, and tactics) and bridging the gap between the business strategies and corresponding operational processes using Business Motivation Model (BMM) and Business Process Modeling and Notation (BPMN) respectively. Concretely, we do the following, (i) create BMM models to communicate business ideas and connect corresponding business tactics to the processes models in BPMN, (ii) simulate processes to check achievable KPIs corresponding to different strategies (modeled in BMM), and (iii) define organizational units in BMM that perform tasks modeled in BPMN. We illustrate our approach through an exemplar case study about production of plastic cups by modeling high-level strategies and their underlying processes. To prove the feasibility of our work, we used and developed the BMM and BPMN plugins based on Eclipse Papyrus framework.

Specification and derivation of key performance indicators for business analytics

Abstract: Key Performance Indicators (KPI) measure the performance of an enterprise relative to its objectives thereby enabling corrective action where there are deviations. In current practice, KPIs are manually integrated within dashboards and scorecards used by decision makers. This practice entails various shortcomings. First, KPIs are not related to their business objectives and strategy. Consequently, decision makers often obtain a scattered view of the business status and business concerns. Second, while KPIs are defined by decision makers, their implementation is performed by IT specialists. This often results in discrepancies that are difficult to identify. In this paper, we propose an approach that provides decision makers with an integrated view of strategic business objectives and conceptual data warehouse KPIs. The main benefit of our proposal is that it links strategic business models to the data for monitoring and assessing them. In our proposal, KPIs are defined using a modeling language where decision makers specify KPIs using business terminology, but can also perform quick modifications and even navigate data while maintaining a strategic view. This enables monitoring and what-if analysis, thereby helping analysts to compare expectations with reported results. HighlightsNovel approach for conceptualizing and specifying Key Performance Indicators.Transforms strategic models into analytic tools to aid in decision making.Enables the user to analyze data subspaces from a strategic point of view.Based on the Semantics for Business Vocabulary and Rules specification.Implemented to support the whole process from definition to data extraction.

Preliminary validation of the metamodel for developing learning ecosystems

Abstract: Learning ecosystems are positioned as a technological solution able to provide learning environments that evolve over time to cover the changing needs of users or include new tools for knowledge management. The definition, development and deployment of this type of software solutions is complex and involves several problems identified and analyzed in previous works. In order to solve these problems, an architectural pattern based on Buschmann's Layers pattern has been defined. The accumulated experience developing learning ecosystems along with the problems analysis using Business Process Model and Notation and the architectural pattern, have provided a knowledge base to define an ecosystems metamodel. The proposed metamodel provides a framework for Model-Driven Development of learning ecosystems. The main objective of the present work is to validate the ecosystems metamodel from modeling a learning ecosystem.