Building a Process Driven Organization with the Process Normalization Technique

Business process modeling (BPM) is one of the key technologies to benefit enterprises with higher efficiencies and greater business values. However, BPM requires intensive business expertise and human resources. Thus, it is valuable and challenging to enable fast delivery of reusable business process designs, regarding the existence of various popular business processes modeling languages and fast changing markets. In this paper, we generate language-specific business process models and process interaction semantics from UML 2.0 process models. A WS-BPEL metadata model and a process interaction semantics metadata model is defined to annotate UML 2.0 business process model as stereotypes; with a set of transformation patterns, we can generate a WS-BPEL business process model and a process interaction semantics file from each annotated UML 2.0 process model. Our approach can also be similarly applied to other process modeling languages to highly reuse the business process model in UML 2.0.

Business process analysis and modeling is a crucial step in formulating information systems user requirements. The practice of information technology (IT) development does not indicate a lack of problems in spite of the growing number of modeling techniques. This article gives an action research account of formulating and applying a new business process modeling framework to manufacturing processes to guide software development. It is based on a combination of soft systems methodology (SSM) and the Unified Modeling Language (UML) business process modeling extensions suggested by Eriksson and Penker. SSM has been linked to information systems provision in the past. The examination of prior research shows that there is no underlying reasoning about the justification from a methodological point of view of the combination of SSM and UML. This article justifies the mixing of SSM and Eriksson and Penker’s UML extensions using the ideas of Mingers’ Multimethodology. The latter helps to overcome the ontological complexities of combining soft and hard techniques in a single intervention. The proposed framework was applied to modeling the production process in an aluminum rolling plant as a step in the development of a new information system for it. The reflections on the intervention give details on how actual learning and appreciation is facilitated using SSM, leading to better UML models in this complex problem.

Business process design and business process reengineering (BPR) depend crucially on linking production procedures and organizational services to business goals and objectives. There is currently very little formula support for this kind of reasoning as analytical tasks are usually carried out informally and individual design decisions are hard to relate to business objectives. If BPR is carried out without understanding the way it is done, then the most likely outcome would be continuing less-than-satisfactory current practice and automating outdated processes. This kind of practice misses opportunities for innovation and rationalization. The modelling and analysis of business processes along with business strategies and organizational structures are essential to study the implications of BPR. In this paper, an attempt has been made to study the modelling, analysis and tools/techniques used for modelling of BPR with the help of a survey on the recently (1993-2000) employed methods and tools used for BPR modelling and analysis. A framework for modelling and analysis, and guidelines for the selection of tools/techniques of business process reengineering are presented.

The theoretical basis and implementation solution of business process simulation and analysis system (BPSAS) is put forward in this paper. With workflow technology, Petri net theory and simulation technology, the workflow engine independent business process analyzing system is realized to provide Petri net based business process analysis. Further more, an example is illustrated to demonstrate how to analyze business process in order to select optimized model. And at the same time, as a business process analyzing tool, it supports the specified BPM (business process management) process.

In many companies, the business processes of logistics, accounting and human resources are unclear — or often even unknown. With the R/3 Reference Model, a tool is available to users that, taking variants (scenario examples) into consideration, clearly portrays business processes of the R/3 system.The introduction of standard software such as SAP's R/3 makes it possible to reengineer existing processes together with organizational structures. New business solutions are derived from the vast amount of process know-how build into the R/3 System from over 23 years of industry experience.In order to support this introduction, SAP has developed the R/3 Reference Model, a business process model for the processes supported by the R/3 software. It serves as the knowledge base for consultants, managers, and project staff.The processes are described within the R/3 Reference Model by process, function, data, organization, and interaction views. The R/3 Reference Model covers all R/3 Business Applications including Sales and Distribution, Human Resources, and Finance by depicting overall functionality as well as the integration of the application areas.The purpose of this paper is to describe SAP's process modeling method, especially the process view, and to delineate the benefits of using the R/3 Reference Model.

Business process modelling is an important part of system design. When designing or redesigning a business process, stakeholders specify, negotiate, and agree on business requirements to be satisfied, including non-functional requirements that concern the quality of the business process. This thesis addresses the question of how to specify and compute the quality of a business process, given the model that stakeholders use. The motivation for this thesis is the increasing importance of the quality of business processes. Knowing the quality of specific business processes enables stakeholders to judge if these processes need improvement. Knowing the quality of the constructs of those processes (viz., events, inputs, activities, and outputs) and the way they are structured enables a more detailed analysis of their shortcomings and provides a basis for the design of improvements. The research challenge of this thesis is grounded in the assumption that: “Organisations need an appropriate means to effectively compute achievement of their goals and objectives by their business processes.” Given this challenge, the main research question on which this thesis focuses is: “Can the quality of a business process be computed quantitatively at different levels of granularity?” The research objective is: “To develop frameworks, factors, and metrics for computing non-functional requirements (quality) of business processes quantitatively at different levels of granularity.” The outcomes of this thesis are: 1) BPIMM, a language-independent business process integrating meta-model, based on the concepts of seven mainstream business process modelling languages: BPMN, EPC, RAD, UML AD, SADT, IDEF0, and IDEF3. 2) BPC-QC (Business Process Concept - Quality Computation), an approach to quality computation at the lowest level of granularity of a business process. The approach consists of: i. BPC-QEF (Business Process Concept - Quality Evaluation Framework), a language-independent generic framework and algorithm to compute the quality of the constructs of a business process: event, input, activity, and output. ii. A set of business process quality dimensions and factors. The following quality dimensions are distinguished: performance, efficiency, reliability, recoverability, permissibility, and availability. Each dimension categorises different quality aspects in terms of factors. A non-exhaustive set of sixteen quantitative factors is provided. iii. Quality metrics for each of the quality factors, to facilitate a quantitative computation of the quality of a specific construct of a business process. 3) BP-QC (Business Process - Quality Computation), an approach to compute the quality at the highest level of granularity of a business process. The approach consists of: i. BP-CQCF (Business Process - Compositional Quality Computation Framework), a language-independent generic framework and algorithm to compute the quality of a business process as a whole, given the quality of its constructs. ii. A set of generic business process modelling patterns to decompose a business process into more succinct parts, namely: sequential, parallel with synchronisation, exclusive, inclusive, simple loop, and complex loop. iii. A set of over one hundred computational formulae. For each combination of modelling pattern and a quality factor, there is a formula to compute the quality. 4) AAV (Approach to Application and Validation), an evaluation plan to evaluate BPIMM, BPC-QC and BP-QC in practice, together with expert stakeholders. The plan consists of the units of measure, a measurement model, and a case study procedure. To evaluate the applicability of the contributions of this thesis to real world business needs, four case studies have been conducted in different environments: a Dutch educational institution, a global financial institution, an international financial service provider, and a Dutch research project on crisis management. Each of these case studies concerns a different, single business process. This thesis shows that: 1) A quality computation approach can be adopted independent of a business process modelling language. 2) Quantitative quality factors can be introduced specifically for the constructs of a business process. 3) Quantitative metrics and computational formulae can be developed for specific quality factors, allowing the computation of different aspects of the quality of a business process quantitatively at different levels of granularity. 4) An evaluation plan can be developed to evaluate the applicability of the contributions of this thesis (viz., BPIMM, BPC-QC, and BP-QC). The contributions of this thesis are designed to be beneficial to the areas of business and management, requirements engineering, software engineering, and business process modelling. In the areas of requirements engineering and software engineering, these contributions are intended to help practitioners to consider non-functional requirements at the earliest stage. In the area of business process modelling, information systems, service computing, and cloud computing, the contributions can be used for quality-driven modelling, design, and redesign. To conclude, knowing the quality value of a business process at different levels of granularity provides a basis for its improvement.

Business process models are a central knowledge asset for organizations, as they explicitly capture the knowledge for documentation, analysis, automation, and certification of business processes. Companies maintain an abundance of process models and their reuse requires powerful means to searching them and presenting the search results effectively. Visualizing specific fragments of a process model facilitates comprehension, and can be used to highlight those parts of a process model that have been matched by a query in process model search.

ion in business processes (BP) modeling arises from the recognition of similarities to the detriment of its differences. However, teaching modeling to beginning students in the context of process management is a hard task to perform, given the high level of abstraction required for these students to develop. This paper uses BP fragments to facilitate the teaching of BP modeling. Thus, two different process models were used from a BP Office. This observation resulted in the fragments being abstracted and defined by a group of students, later another group applied the third model. Thus, two fragments were abstracted, specified, and reused. In addition to the approach itself and the template used to define the fragments here presented, this research’s main contribution is the role that abstraction plays in BP learning and modeling skills. Finally, the fragments were validated by ten specialists, who emphasized the feasibility of using these fragments.

Business Process Analysis and Optimization on Road Traffic Law Enforcement of the Beijing Intelligent Traffic Management

1 IntroductionOrganizations focus on automate their processes in order to improve efficiency, reduce costs, and/or reduce human beings' errors in an easy and rapid manner. Business process management (BPM) methods provide a solution to this issue. In this context, information systems like CRM, ERP, SCM, etc. have known an increasing demand. The main problem consists of the length of the business process specifications. If new regulations appear, these specifications must be adapted. Manually extraction of visual models is time consuming. During time, a series of solutions were proposed. The literature shows a crowd of approaches that extracts data models [1], [2], [3], and process models [4], [5] from Natural Language (NL) text. This paper aims to analyze the Natural Language Processing (NLP) techniques and tools used in order to provide different types of visual representations.On the last few years, approaches based on NLP have been developed in order to automate process conversion from NL text. NLP plays an important role in NL text analysis as NLP tries to understand speech and text as humans beings would do. Colloquialism, abbreviations or typos make this task a challenging one. NLP has the origins in 1950s when Alan Turing proposed the Turing test [6], by introducing the imitation game. Since then, the literature shows a plethora of NLP tools [7], [8], [9], [10] using several machine learning techniques, our focus being on those applied on data models and process models discovery from NL text, starting with the first language parser [11] to the actual ones like NLTk [7], [8], ANTLR1, etc.Linguistic analysis is closely tied to NLP. Liddy [12] highlights 7 levels of linguistic analysis: a) Phonetic or Phonological level: how words are pronounced, b) Morphological level: prefixes, suffixes and roots analysis, c) Lexical level: word level analysis including lexical meaning and Part-Of-Speech (POS) analysis, d) Syntactic level: grammatical analysis of words in a sentence, e) Semantic level: determining the possible meanings of sentences, f) Discourse level: interpreting structure and meaning for texts larger than a sentence, g) Pragmatic level: understanding the purpose of a language.Some of the problems approached by NLP are: POS tagging, parsing, Named Entity Recognition (NER), chunking, Semantic Role Labeling (SRL). Anaphora resolution [13] refers to the interpretation of the link between the anaphor and its antecedents.The remainder of the paper is organized as follows: Section 2 briefly outlines the NLP domain, describing the levels of linguistic analysis and the main NLP approaches of analyzing NL requirements. Section 3 focuses on data and process models extraction from NL text. This section makes an introduction to Object Oriented Analysis and Business Process Modeling and analyses the existing tools that discover data and process models from text. Subsequently, Section 4 summarizes the results of this work and the conclusions are drawn in Section 5.2NLPA detailed review on NLP is given in [14] and in [15]. Jones [14] divides the history of NLP into four phases: the first starts at the beginning of the 1940s and lasts to the late 1960s, the second begins from the end of 60s and lasts to the end of 70s, the third is represented by late 80s, where the fourth phase starts in the late of 90s. Next, we will detail each phase as they were defined in [14] and [15]. First phase treated machine translation issues, while the second focused on artificial intelligence. The third phase can be called grammatico-logical phase, which is followed by the lexical phase. A fifth phase is proposed in [16] where formal theories and statistical data are combined. Since this study was published first in 1994 and then it was re-organized in 2001 we can add the sixth phase: from 2000 until present where NLP techniques are combined in order to contribute to visual models extraction.Software requirements are usually written in NL which is asymmetric and irregular [17]. …

Web service composition involves the combination of a number of existing web services to create a value-added one. WS-BPEL is a promising language which describes Web service composition in form of business processes. However, WS-BPEL is an XML-based language and may suffer from ambiguities or some erroneous properties. The analysis and verification of business processes specified in WS-BPEL by a formal method has been a hot topic in the research community lately. In this paper, we propose a method to model and analyze WS-BPEL business processes based on ServiceNet, a special class of Petri nets. Unlike most of the existing work which analyze only control flow properties of WS-BPEL business processes but neglect data flow properties, our method models and analyzes both control properties and data properties of WS-BPEL business processes. We present the transformation rules of WS-BPEL business processes into ServiceNet and enrich the reduction rules of ServiceNet by applying them in some practical projects. Then the throughness of a business processes can be verified by reducing its ServiceNet representation based on some reduction rules. Moreover, we define some data-aspect properties of WS-BPEL business processes and give the corresponding checking algorithm.

Information System is one of the key domain in which lot of research has been done in the past few years. Applying Information systems to heterogeneous and distributed environments is one of the current research areas. Business Process Management Systems is the information systems which deal with the administration of tasks in the business processes, organizational structures, or in the related context. The Workflow Management system, the early idea of BPM, controls the workflow in an organization, data transfer, and integration of legacy information systems with existing programs and program modules, delegation of business tasks. Offering task management services especially modeling of business processes and underlying organizations, BPM serves it meaning and incorporates the WFM system. BPM supporting the use of knowledge concerning the awareness/unawareness of integrated software, and analysis of processes and organizational structure in terms of verification, modification, evaluation are key management in BPM system I.INTRODUCTION TO BPM: Combination of corporate restructuring and mergers urged the department and processes to be automated and linked together. Unfortunately it created largely disconnected spaghetti of systems and applications. Business Process Management (BPM) was born from a strong need to streamline internal processes and connections between both internal and external functions. It provides ability to model, monitor, manage and manipulate processes quickly in response to changes in strategy and market forces. BPM is an extension of classical Work Flow Management (WFM) systems and approaches. BPM delivers the maximum utility of legacy system. It is a method for revolutionizing the way the work moves throughout an organization. II.COMPONENTS OF BPM: The four key elements in Business Process Management are: Process modeling, Process rule, Process management, and Process performance analytics. Process modeling: Process modeling describes the flow of information (business process).It helps in building a model of process and mapping into an implementation frame work. Modeling requires a consistent analysis and representation of the processes. It forms the basis for the userspecific process environment. Process Rule: Process Rule is a heart of the BPM. It involves execution of discrete steps & integration of information. A process rules engine is used for this purpose. The engine is to monitor and manage the given steps by providing a flow control over the business process. If a process fails or delayed, a compensated action can be done to rectify. Process Management: Process Management is to correlate business/application events to fundamental business metrics .It enables the organization to monitor and optimize the business process. Once the process has been analyzed, modeled and the associated rules are formed. The next stage involves the visualization and management. Visualization means transaction data ranging from holistic to process-state or client state specific rules. Process Performance Analytics: Process Performance Analytics is a transition data source available for sophisticated management analytics .This data should be available on a retrospective or real-time basis. It should answer to one of the most difficult question like “how much does it cost to process a specific transaction?” By this way BPM mainly addresses four components. They are Work Flow Management, Content and records management Enterprise Application Integration (EAI) and Business Activity monitoring (BAM). III.RELEVENCE TO SYSTEM INTEGRATION: BPM can be fitted easily on the top of existing IT system. It is the Process rules that governs all the happenings and optimizes the process. BPM will not be able to work without the connectivity provided by the EAI layer. EAI layer provides BPM to gain and measure the value from the investment. On the other hand, BPM provides value to the EAI technology layer of Information technology. BPM layer offers business management the view of the message processing layer. It is used to unlock the value of the information held in the integration layer. It is also used to gather data of every transaction in the lifecycle. IV.APPLICATION OF BPM: BPM can be applied to any application which needs these advantages. BPM reduces unnecessary high losses in time critical transactions, helps to provide any critical information, practical application yield fast ROI ,better control over the information, identifying and maximizing the benefits faster, better analysis and tracking, provides enterprise-wide visibility of business processes, improve the effectiveness of the core operations, provides ability to coordinate interactions between information systems, business process and the people, flexible and easily changed by non-technical business people.

UPROM tool is a business process modeling tool designed to conduct business process and user requirements analysis in an integrated way to constitute a basis for process automation. Usually, business process models are not utilized systematically to develop related artifacts, specifically when a process-aware information system is to be developed to automate those processes. This results in completeness, consistency and maintainability problems for those artifacts. Unified business process modeling methodology, UPROM, is developed to integrate process modeling and practices. Enabling the application of UPROM, the tool provides editors for six different diagram types based on a common meta-model. It offers features so that modelers can develop a cohesive set of models. Using these models, UPROM tool can be used to automatically generate artifacts of user requirements document, COSMIC based software size estimation, process definition document and business glossary.

Process mining has an important place in business process (BP) analysis. It aims to analyze process events in order to discover the related BP model. However, these techniques are only based on process events and sometimes on business data, leaving aside a large set of data, namely the BP execution context. Existing studies have shown the benefits of considering the context in the BP analysis but they only suggest manual techniques to bind a BP with its context, which is not scalable and time consuming in real deployment environment. To address this issue, we propose a semi-automatic BP contextualization solution which takes into account the BP execution context in the BP analysis time. It uses semantic techniques to perform a matching of the BP model with contextual data and with business data, and then it obtains the value of these data during the BP execution. In this paper, we present a tool that implements this solution in order to enhance current analysis techniques which facilitates the monitoring and enables deep BP analysis. The proposed tool is validated by its application to a real life process, a palettization process.

An Agile Business Process and Practice Meta-model