Business Process Configuration Research Articles

Optimization and manual configuration of business processes in modern economic conditions

The article discusses the principles and approaches to optimizing business processes, provides an optimization algorithm from the functional management principle to the process principle based on flow construction, discusses risks and ways to mitigate them.

Optimization models in the SCM-system: progressive supply chain management

Transformations in socio-economic space affect functioning of entrepreneurial activity, leading to a change in the configuration of business processes. In the context of increasing complexity of external environment and digitalization, subjects must ensure the activities effectiveness based on supply chains optimization. Entities are required to use progressive methods of supply chain management. The purpose of the study is to analyze main optimization models in supply chain management (SCM) to determine progressive ways to improve them. The issues of SCM have been worked out, models of their optimization considered and suggestions for their improvement made. Theoretical analysis and generalization of information that allow to substantiate the SCM optimization models’ apparatus (SCOR, DCOR, CCOR) act as a methodological basis. As a result, it is proposed to focus on possibilities of progressive supply chain management, which make it possible to use information technologies to work through a large array of data and continuously obtain values for indicators, contributing to the development of models for optimizing logistics operations and processes in the SCM. The developments obtained are planned to be used for the development of practical models for optimizing enterprises’ supply chains.

Uncertainty measurement of a configurable business process

AbstractToday, the economic crisis is putting enormous pressure on most organizations. It evolves in a crucial competitive environment with a multiplication of production cycles and implementation on the market. Due to this dynamism, organizations must be scalable and agile by adopting an approach that aims to make the process model of a given organization reusable. Indeed, according to the new paradigm which is called “Design by reuse” the models of configurable processes, gain recently in importance since these models have the capacity to represent explicitly the common parts and variables of identical processes in a customizable model. These configurable process which group several execution choices through a variation point called configurable connector will present an uncertainty related to the execution (or not) of the conditional tasks in a process model. In this paper, we propose a measure based on Shannon's entropy in order to model the uncertainty of the process at design time to guide configurable business process designers and analysts in developing and improving processes to be more predictable, less complex, and more understandable.

Organization-driven business process configurable modeling for spatial variability

Nowadays, enterprises need to continually adjust their business processes to adapt to the changes of business environments, especially when one business needs to be deployed in different application scenarios, which is called spatial variability in this paper. In the field of BPM (Business Process Management), configurable business process models have demonstrated their effectiveness in aspects of process modeling and model reuse. Yet, we found that the existing techniques lead to complex configurable models, and are inadequate for model reuse especially for the spatial variability issue because they neglect the root impact of organizations on control flow. S-BPM (Subject-oriented Business Process Management) models provide a solid foundation for dealing with complex applications and help to bridge the gap between business and IT for process execution. In this paper, we propose an organization-driven business process configurable modeling approach for spatial variability by integrating both restriction and extension operations based on the S-BPM paradigm, in which business objects are also included. Our approach is validated with a general business process developed for the Real Estate Administration (REA) in a certain province of China. The resulting configurable modeling framework can express the heterogeneous activity sequences for one business and has the potential to generate process models for uncertain environments in a new organization structure.

Advances and Challenges for Model and Data Engineering

Advances and Challenges for Model and Data Engineering

A Formal Model for Configurable Business Process with Optimal Cloud Resource Allocation

In today’s competitive business environments, organizations increasingly need to model and deploy flexible and cost effective business processes. In this context, configurable process models are used to offer flexibility by representing process variants in a generic manner. Hence, the behavior of similar variants is grouped in a single model holding configurable elements. Such elements are then customized and configured depending on specific needs. However, the decision to configure an element may be incorrect leading to critical behavioral errors. Recently, process configuration has been extended to include Cloud resources allocation, to meet the need of business scalability by allowing access to on-demand IT resources. In this work, we propose a formal model based on propositional satisfiability formula allowing to find correct elements configuration including resources allocation ones. In addition, we propose to select optimal con- figurations based on Cloud resources cost. This approach allows to provide the designers with correct and cost-effective configuration decisions.

ИНФОРМАЦИОННЫЕ БИЗНЕС-ПРОЦЕССЫ СИСТЕМНОЙ КОНФИГУРАЦИИ В СОПРОВОЖДЕНИИ РЕАЛИЗАЦИИ СТРАТЕГИЧЕСКИХ ОРИЕНТИРОВ РАЗВИТИЯ КРУПНЫХ ЭКОНОМИЧЕСКИХ СТРУКТУР ХОЛДИНГОВОГО ТИПА

The article substantiates the need to create a system configuration of information business processes in large holding-type structures aimed at providing managers with the necessary information for making decisions regarding the implementation of the company's strategy. It is substantiated that such a system includes the formation, collection, processing, filtering of information by content, taking into account the goals, requests of managers of different levels and areas of activity, its distribution in accordance with the needs of managers of higher, middle and lower levels.

Configurable artefact-centric business process modelling with proclets

Configurable artefact-centric business process modelling with proclets

Configurable artefact-centric business process modelling with proclets

Configurable artefact-centric business process modelling with proclets

Handling Sudden and Recurrent Changes in Business Process Variability: Change Mining based Approach

Changes are random and unavoidable actions in business processes, and they are frequently overlooked by managers, especially when managers need to deal with a collection of process variants. Because they must manage every single business process variant separately which is a time-consuming task. They exist many approaches to manage a collection of business process and deal with variability. Such as process mining approaches, that can discover configurable business process models, enhancing them and verify conformity automatically. However, those approaches do not cover changes and concept drift that occur over time. This paper presents a novel change mining approach that discovers changes in a collection of event logs and reports them on a change log. This change log can be analyzed to determine whether the changes are sudden or recurrent and recommend afterward some improvement to the configurable process model.

A DSDEVS-Based Model for Verifying Structural Constraints in Dynamic Business Processes

This paper presents a DSDEVS-based model “Dynamic Structure Discrete Event System specification” for modeling and simulating business processes with dynamic structure regarding to different contexts. Consequently, this model, formally, improves the reuse of configurable business processes. Thus, the proposed model allows the analysts to personalize their configurable business processes in a sound manner by verifying a set of structure properties, such as, the lack of synchronization and the deadlock by means of simulation. The implementation was done in DEVS-Suite simulator, which is based on DEVSJAVA models.

New trends in adaptive smart systems, services, and architectures

Smart Systems are composed of interconnected nodes (devices, services, components, etc.) that can be intelligent, mobile, embedded, cloud-based, or/and adaptive. These nodes interact together through new communication protocols. Architectures of such system needs to adapt its behavior and deals with change in the environment. An adaptive and reconfigurable architecture can repair itself if any execution problems occur, in order to successfully complete its own execution. In the design of an adaptive and reconfigurable software system, several aspects have to be considered. Also other emerging areas such as Big data can also be used to solve traditional problems of Smart Systems, like scalability and performance. This special issue addresses these issues and is composed of seven papers. The paper of1 entitled “Efficient monitoring for intrusion detection in wireless sensor networks” addresses the design of a reliable and energy-efficient monitoring system that resists internal security attacks based on a distributed smart monitoring protocol. The paper of2 entitled “Cloud SLA negotiation and re-negotiation: An ontology-based context-aware approach” defines a context-aware system that automates the negotiation of dynamically generated and adapted SLAs using reasoning techniques and semantic mapping between client requests and provider offers. The paper of3 entitled “Cloud service composition using minimal unsatisfiability and genetic algorithm” targets the run-time phase of adaptive systems. It addresses the dynamic properties of service-oriented adaptive systems by provide a hybrid approach for automatic WS composition based on formal methods and genetic algorithms. The paper of4 entitled “A knowledge-based approach to manage configurable business processes” targets both run-time and design-time as well as structural and behavioral properties of enterprise systems modelled and enacted as Business Processes (BP). It proposes a knowledge-based approach for capturing the different versions of a BP into a single configurable BP and splitting this process into fragments as an alternative of handling multiple BP versions. The paper of5 entitled “Avoiding resource misallocations in business processes” presents an approach for avoiding resource misallocations, considered as an improper combination of resources, in Business Processes (BPs). The paper of6 entitled “Simulating systems of systems using situation/reaction paradigm” targets the designs-time phase of adaptive systems. It considers the paradigm of Systems of Systems that can be applied to different smart and adaptive systems. The paper sees these systems from the mission point of view to characterise their evolving rules with formal modelling and simulation. The paper of7 entitled “A comprehensive survey on modeling of cyber-physical systems” provides a survey of existing approaches to modeling CPS. It aims to study and to classify the CPS properties and to discuss their importance in different application domains. We would like to thank CCPE Editor-in-Chief Dr. Geoffrey C. Fox for his strong support. A special thank goes to all authors for their valuable contributions to this special issue. Special thanks go to all the guest eidtorial board members for their comments that helped in enhancing the quality of the papers.

Transactional Behavior Verification in Business Process as a Service Configuration

Business Process as a Service (BPaaS) is an emerging type of cloud service that offers configurable and executable business processes to clients over the Internet. As BPaaS is still in early years of research, many open issues remain. Managing the configuration of BPaaS builds on areas such as software product lines and configurable business processes. The problem has concerns to consider from several perspectives, such as the different types of variable features, constraints between configuration options, and satisfying the requirements provided by the client. In our approach, we use temporal logic templates to elicit transactional requirements from clients that the configured service must adhere to. For formalizing constraints over configuration, feature models are used. To manage all these concerns during BPaaS configuration, we develop a structured process that applies formal methods while directing clients through specifying transactional requirements and selecting configurable features. The Binary Decision Diagram (BDD) analysis is then used to verify that the selected configurable features do not violate any constraints. Finally, model checking is applied to verify the configured service against the transactional requirement set. We demonstrate the feasibility of our approach with several validation scenarios and performance evaluations.

Optimal Deployment of Configurable Business Processes in Cloud Federations

Configurable processes are increasingly being adopted by enterprises that seek experience sharing and best practice adoption. A configurable process is a customizable model that specifies how different enterprises perform similar processes. At the modeling level, a configurable process model provides for flexible business process (BP) reuse by (de)selecting the (ir)relevant parts to derive a particular process variant. At the exploitation level, it offers flexibility and agility to an enterprise looking to outsource its BP to different providers cooperating in a cloud federation. More specifically, an enterprise can use a configurable process model to derive particular process variants that it outsources depending on its objectives. In particular, it may opt for outsourcing the variant that results in the optimal deployment , e.g., having the minimal cost of allocated cloud services that fulfill the user quality of service (QoS) requirements. However, identifying the optimal deployment variants is a complex problem because of the heterogeneity of services within a cloud federation and the number of possible variants that can be derived from a configurable process model. In addition, the complexity of this problem increases for variable user QoS requirements. In this paper, we propose an approach to derive, from a configurable process model, the variant that has the optimal deployment in a cloud federation. We propose a linear programming approach that accounts for the variability of both the BP model and the user QoS requirements, and that ensures an optimal time-aware cloud service allocation. We experimentally show the effectiveness and flexibility of our approach on a generated testbed.

A knowledge‐based approach to manage configurable business processes

SummaryThis paper stresses out the struggle of organizations when managing multiple variants of the same business process. Each variant constitutes a response to structural and/or functional needs that overtime become unsustainable due to the multiplicity and complexity of these needs. To mitigate this struggle, a knowledge‐based approach for capturing these versions into a single configurable business process and splitting this process into fragments is discussed in the paper. The approach builds a configuration knowledge base to track the business process variability (ie, particularities of each business process variant). Variants are represented as a new configurable process structure tree resulting from fragmenting a business process. Implementation of the approach is, also, reported in this paper.

Business Process Configuration According to Data Dependency Specification

Configuration techniques have been used in several fields, such as the design of business process models. Sometimes these models depend on the data dependencies, being easier to describe what has to be done instead of how. Configuration models enable to use a declarative representation of business processes, deciding the most appropriate work-flow in each case. Unfortunately, data dependencies among the activities and how they can affect the correct execution of the process, has been overlooked in the declarative specifications and configurable systems found in the literature. In order to find the best process configuration for optimizing the execution time of processes according to data dependencies, we propose the use of Constraint Programming paradigm with the aim of obtaining an adaptable imperative model in function of the data dependencies of the activities described declarative.

Artefact-centric business process configuration

Currently, there are two mainstream process modelling paradigms: the traditional activity-centric approach and the recent artefact-centric approach. Several approaches have been proposed for configuration of traditional activity-centric business processes; however, to the best of our knowledge, few approaches have been developed for artefact-centric business processes. This paper fills this gap by proposing a novel configuration approach for artefact-centric business processes. The configuration of artefact-centric process modelling is achieved by the configuration of artefact lifecycle models for all the involved artefact classes. First, we apply deterministic finite automaton to formalise an artefact lifecycle model ALM. To derive configurable ALM, we propose merger operation for ALMs. Also, an artefact lifecycle graph ALG is proposed to describe ALM as a state diagram, and the structural soundness of ALG is also presented. Then, we propose configurable artefact lifecycle graph C-ALG to describe the configurable artefact lifecycle model, in which arcs and sets of business rules can be defined to be configurable points. Finally, by configuring C-ALGs for each artefact class with our individualisation algorithm, structurally sound artefact lifecycle models are derived including data models of artefacts, associated services and business rules, thus resulting a complete configured artefact-centric process model.

A semantic framework for configurable business process as a service in the cloud

With the advent of Cloud Computing, new opportunities for Business Process Outsourcing services have emerged. Business Process as a Service (BPaaS), a new cloud service model, has recently gained a great importance for outsourcing cloud-based business processes constructed for multi-tenancy. In such a multi-tenant environment, using configurable business process models enables the sharing of a reference process among different tenants that can be customized according to specific needs. With a large choice of configurable process modeling languages, different providers may deliver configurable processes with common functionalities but different representations which makes the process discovery and configuration a manual tedious task. This in turn creates cloud silos and vendors lock-in with non-reusable configurable BPaaS models. Therefore, with the aim of enabling the interoperability between multiple BPaaS providers, we propose in this paper a semantic framework for BPaaS configurable models. Taking advantage of Semantic Web technologies and data mining techniques, our framework allows for (1) an ontology-based high level abstract representation of BPaaS configurable models enriched with configuration guidelines and (2) an automated approach for extracting the configuration guidelines from existing process repositories. To show the feasibility and effectiveness of our approach, we extend Signavio with our semantic framework and conduct experiments on a dataset from SAP reference model.

Software Architecture for Document Anonymization

Organizations often have a dilemma in relation to their documents: ensure confidentiality of the data or publish the information contained in them, for transparency, scientific interest, or other reasons. In this context is that document anonymization arises, i.e. the replacement of sensitive data in such a way that preserves the confidentiality of the documents without altering their value or usefulness. There are proposals for (semi)automatic anonymization, but they are often domain-specific or they partially address the problem. In this paper we present a software architecture for supporting document anonymization, which is based on the representation of the problem as a domain and platform independent configurable business process. In addition, we analyze the technological alternatives for implementing the architecture and we present a functional prototype applied to the domain of legal documents.

Generating optimized configurable business process models in scenarios subject to uncertainty

ContextThe quality of business process models (i.e., software artifacts that capture the relations between the organizational units of a business) is essential for enhancing the management of business processes. However, such modeling is typically carried out manually. This is already challenging and time consuming when (1) input uncertainty exists, (2) activities are related, and (3) resource allocation has to be considered. When including optimization requirements regarding flexibility and robustness it becomes even more complicated potentially resulting into non-optimized models, errors, and lack of flexibility. ObjectiveTo facilitate the human work and to improve the resulting models in scenarios subject to uncertainty, we propose a software-supported approach for automatically creating configurable business process models from declarative specifications considering all the aforementioned requirements. MethodFirst, the scenario is modeled through a declarative language which allows the analysts to specify its variability and uncertainty. Thereafter, a set of optimized enactment plans (each one representing a potential execution alternative) are generated from such a model considering the input uncertainty. Finally, to deal with this uncertainty during run-time, a flexible configurable business process model is created from these plans. ResultsTo validate the proposed approach, we conduct a case study based on a real business which is subject to uncertainty. Results indicate that our approach improves the actual performance of the business and that the generated models support most of the uncertainty inherent to the business. ConclusionsThe proposed approach automatically selects the best part of the variability of a declarative specification. Unlike existing approaches, our approach considers input uncertainty, the optimization of multiple objective functions, as well as the resource and the control-flow perspectives. However, our approach also presents a few limitations: (1) it is focused on the control-flow and the data perspective is only partially addressed and (2) model attributes need to be estimated.