Object-Aware Process Management

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.

Process and data are equally important for business process management. Data is especially relevant in the context of automated business processes, and process controlling. In the context of knowledge-intensive domain, data modified by engineers and used by a fully automatic manufacturing system can lead to unpredictable errors. In this paper, a method permitting the discovery of truly enforced business rules used by the process is proposed. These rules will be highlighted using data from the model of the studied process. The proposed methodology is mainly based on a data mining approach. The proposed method has been tested on data from semiconductor industry, in which processes are known to be complex, and the number of business rules is known to be important. The results show that the method is efficient in assisting engineers in process errors detection and practical process improvement.

Service-oriented architectures, business process management (BPM) systems, and BPM in general receive a lot of attention these days and the number of articles which describe the benefits and great potential of these technologies has significantly increased. It is something like a second wave after the first (and short) workflow hype in the middle of the 90’s. However, the contemporary hype in newspapers and IT magazines does not really reflect reality. In fact, much more companies are still thinking about whether and in which form they shall introduce these technologies rather than concretely performing projects in these fields. And many companies which have started respective projects are still in the phase of designing and implementing (web) services or in evaluating SOA platforms and repositories of different vendors; i.e., they are still not bringing (larger) processes into production. Nevertheless, expectations are very high: Everything will become easier and more flexible, implementation of crossorganizational processes will become business as usual, and process management systems will enable new kinds of process-aware applications which have to be performed manually today. In fact, BPM has a great potential. However, to realize this potential in practice, we have to face much more the challenges of the real world, we have to learn more seriously from how business processes are executed today, and we have to understand how actors deal with exceptional situations. It is not hard to predict what will happen with the current BPM hype if users discover that they cannot do much more with these technologies than with previous ones or, even worse, that they can do less. And no organization will accept to become inflexible. – It is partially up to us, whether BPM will become a big and sustainable success or whether it will share the fate of many other hypes (like Computer Integrated Manufacturing at the end of the 80’s). This talk will present real-world examples from different domains to illustrate where we jump too short. It will use the ADEPT project [1,2] to show how stimulating it can be also from a research point of view to face the reality as it is.

The systematic improvement of processes is practically realised in the industry and economy by operating a Process Management (PcM) System. Many authors also recommend a systematic repetition of Value Stream Mapping (VSM); but the global experiences in applying VSM do more or less indicate a single or punctual application of VSM to improve processes or value streams. The findings discussed in this paper describe the systematic embedding of Value Stream Mapping into the life cycle of a Process Management System using the principles of “innovation and continuous improvement”. Thus the Process Management System enables a systematic, regularly repeating application of VSM by extending its 4-Step-procedure. One suitable way to standardise the application of VSM is specified in this paper on a theoretical base to make this approach international applicable.

Business processes and information systems mutually affect each other in non-trivial ways. Frequently, the business process design and the information system design are not well aligned. This means that business processes are designed without taking the information system impact into account, and vice versa. Missing alignment at design time often results in quality problems at runtime, such as large response times of information systems, large process execution times, overloaded information systems or interrupted processes. Aligning business process quality and information system quality at design time requires to
\nsolve the following problems (P). Business process quality and information system quality have to be characterized. P1: In contrast to information system quality, which is specified in the ISO/IEC 9126 standard, for example, there is no common and comprehensive understanding of business process quality. P2: Beyond that, current business process
\nmodeling notations do not aim to represent quality aspects. The impact of a business process on the quality of an information system, and vice versa, is unknown at design
\ntime. P3: The mutual impact between business processes and information systems must be predicted at design time.
\nIn this thesis, the Business Process Quality Reference-Model (BPQRM), a quality model for business processes, is introduced. The model allows for a comprehensive characterization of business process quality (P1). The BPQRM is applied successfully in a case study to
\nidentify potential for process quality improvement in practice. Based on the BPQRM an existing process modeling notation is extended by model elements to represent quality
\naspects (P2). Simulation is a powerful means to predict the impact of a business process on the quality of an information system, and vice versa, at design time. This thesis proposes two simulation approaches to predict the mutual impact between business processes and information systems, in terms of performance (P3). The approach Business
\nIT Impact Simulation (BIIS) defines interfaces between the business process simulation and the information system simulation. Performance-relevant information is exchanged
\nvia the interfaces between both simulations. Using business process simulation and information system simulation in isolation, workload burstiness is not adequately reflected.
\nThis is especially true for occasional, volatile peak loads. Workload burstiness can significantly affect the performance of business processes and information systems. The approach Integrated Business IT Impact Simulation (IntBIIS) for the integration of business processes and information systems in a single simulation allows for reflecting workload burstiness correctly. The simulation approaches support the comparison of design alternatives and the verification of a certain design against requirements. A case study confirms the feasibility in practice and the acceptance from practitioners’ point of
\nview.

To solve the emerging problems in network courses, we propose the design of a teaching process monitoring and management system, based on the education technology related theories, such as cooperative learning, environment learning, etc. Through the interaction between the monitoring, management, evaluation, and feedback, the system is able to increase the utilization rate of the network course, improve the learning interest and efficiency. Finally, the teaching management and quality are maximally improved.

Objective To explore the clinical value of application research in business process reengineering in transferring of inpatients for check-up. Methods We reorganized transferring of inpatients for check-up and service tache by introducing the Systematic Redesign method from the therory of Business Process Reengineering. The reengineered process was adopted and applied in the transferring processes. We randomly selected patients for check-up(126 cases for electrocardiogram,130 cases for Xrayand 128 cases for CT examination)and investigated the time cost for check-up and patients satisfaction rate. The above results were compared with those patients(112 cases for electrocardiogram,112 cases for Xrayand 120 cases for CT examination)before use of reengineered process. Results The time cost for the above mentioned check-up was shorter and patients satisfaction rate were alleviated compared with those before use of reengineered process(U=14.55,12.26,13.57;x2=17.37,14.65,10.75,P＜0.01).Conclusion Application of business process reengineering in the transferring process of inpatients for check-up proved pivotal important in that it could shorten time cost for transferring process and improve patients satisfaction rate.It possessed realistic significance for increasing benefit and competitions for hospitals. Key words: Business process reengineering; Inpatients; Check-up; Transferring; Process

In order to strength the value of process management, Group company launches the process management and information system improvement, aiming to define the responsibility of each position and department, and indicate the process points of risk control as well as related institution, organization responsibility and control standard in a graphical way, by which to connect institutional procedure and totally change the previous method of program management. Therefore, a project team was built to present a long-term stable process management system applying to ARIS process management platform. The system was requested to express the all businesses macroscopically and detail all job specifications in microscopically. An area of Group Company was selected to be researched including the process, internal control and institutional procedure. Finally, the process management platform based on ARIS was built, and Group Company achieved significant value in process management include sharing, integration, specification, dynamic, clear control etc.

Development of a Building Information Modelling Asset (BIMAsset) value realisation model

The automatic detection of divergences from a desired process behavior is a common research topic in the business process management community. An established technique to analyze processes is called conformance checking. Given a definition of a process in form of a process model, conformance checking can be used to test whether the executions of a process contained in a so-called event log data structure are conforming with the process as it was defined. The result is a comparison of the execution traces and their respective correct execution, according to the process model. This technique provides insights into where the divergence has occurred and how the execution must be altered to conform to the process model. However, a problem is that it requires a process model to be available. Process models in the correct format are not always available. Contrary to conformance checking, process anomaly detection aims to find anomalous executions without relying on a predefined process model. A process anomaly detection algorithm derives the process logic from the event log itself and exploits the patterns found within the event log to distinguish normal from anomalous process executions. Though process anomaly detection provides the benefit of not relying on a process model, it typically does not provide the level of detail that conformance checking does. A process execution can either be normal or it can be anomalous. This dissertation proposes process anomaly correction, a novel approach that combines the benefits of conformance checking and process anomaly detection. Given only an event log, process anomaly correction detects anomalous executions, clearly indicates where the anomaly has occurred during the execution and suggests possible corrective measures. The solution presented in this work is based on a new concept to the field of process anomaly detection: Process learning. In process learning, the task of understanding the process based on the example data is transformed into a learning problem in which a neural network is trained to predict the very next activity in a running process execution. The resulting machine learning model thus represents an approximation of the real process that created the data. This cumulative dissertation consists of five contributions to the field of business process management that demonstrate how, starting from a process anomaly detection, process anomaly correction is achieved in a series of four steps. (1) Process learning is employed to generate an approximated model of the process logic. (2) The limitation of only distinguishing between normal and anomalous process executions is overcome by employing the process learning model which processes the process executions on a finer level of detail than existing approaches. (3) The necessity of providing manual threshold settings, as it is typical for process anomaly detection algorithms, is replaced by an automatic parameterization utilizing the process learning model. (4) The predictive capabilities of the process learning model are exploited to generate possible corrections of detected anomalies. The resulting process anomaly correction approach can be employed in scenarios where classic conformance checking would be infeasible, due to the restriction of relying on a process model. Furthermore, it can be employed alongside classical conformance checking, for it incorporates more information coming from the event log than classical conformance checking (such as employees executing a process step, in which country the process is executed, etc.), and thus provides a new perspective for the process analyst.

Firm performance has been linked to information technology adoption. However, limited research exists related to minority entrepreneurs’ technology usage due to inequalities of ownership, cultural ethnicity impact, and inconsistent comparative usage, specifically among Latino users. This study investigates Latino and non-Latino entrepreneurs: 116 subjects with 61% Latinos; the relationships of ethnic identity, resistance to technology use, and self-efficacy; differences between business process and social media technologies; contexts of financial management and linguistic communication for business processes; business owner’s self-efficacy and technology adoption. Latinos results: higher technology resistance, social technology usage; and, lower self-efficacy, use of linguistic communication technology context.

In traditional formal concept analysis, the attributes in the formal context are considered fixed. However, in the real world data set, attributes always have different levels of granularity, correspondingly, the derived concept lattice may reveal different information and patterns. Therefore, the capability to change the level of granularity of an attribute in formal concept analysis to capture relevant patterns in data is a natural requirement. In this paper, a theoretical study has been undertaken in multi-scale formal contexts, where attributes with different levels of granularity possess different attribute values. Two types of formal concepts, i.e., object-oriented and property-oriented multi-scale concepts, are introduced and studied in detail. The collection of object-oriented concept lattices and property-oriented concept lattices can be obtained at different granularity levels of attributes. It has been shown that the set of extents in the derived concept lattices increases when we choose to use a finer level of granularity. Moreover, a corresponding bidirectional approach to concept construction(i.e., from coarser to finer and from finer to coarser, respectively) is exhibited, and some characterization theorems have been obtained.

The statistical concept, six sigma is used to define problems systematically, provides tools to measure and influential factors and identifies the improvements that can be implemented easily. It is quality management tool which can be considered as a vision, a philosophy, a symbol, a metric, a goal, a methodology. It simply means a measure of quality that struggle for near perfection. It is a highly disciplined process that focuses on developing & deliveringNear perfect product & services It is based on three element Process improvement, Process.Design/re-design and Process management. When we use this technique for a process then process variation reduced to 3.4 DPMO (Defects per million Opportunities).Six sigma is divided in two sub methods DMAIC (Define, Measure, Analyze, Improve and Control) is improvement system for existing processes that doesnt meet specification. DMADV (Define, Measure, Analyze, Design, Verify) is used to develop new processes at six sigma level.

In this paper we present a system for automatic Arabic text diacritization using three levels of analysis granularity in a layered back off manner. We build and exploit diacritized language models (LM) for each of three different levels of granularity: surface form, morphologically segmented into prefix/stem/suffix, and character level. For each of the passes, we use Viterbi search to pick the most probable diacritization per word in the input. We start with the surface form LM, followed by the morphological level, then finally we leverage the character level LM. Our system outperforms all of the published systems evaluated against the same training and test data. It achieves a 10.87% WER for complete full diacritization including lexical and syntactic diacritization, and 3.0% WER for lexical diacritization, ignoring syntactic diacritization.

Over the last few years, we have seen the transformation of the traditional monolithic enterprise, in which all operations were performed in-house, to the extended enterprise, which consists of a network of collaborating entities. Global operations, outsourcing, and increasing specialization have all contributed to this trend. One challenge facing the extended enterprise is how to reconnect the information flows and business processes that were disconnected as the enterprise disaggregated. The emergence of web services, service-oriented architectures, and business process modeling and execution standards are helping to address this challenge. Our contention is that the next phase of evolution is the rise of the intelligent enterprise, which is characterized by being able to adapt quickly to changes in its operating environment. The intelligent enterprise monitors its own business processes and its interactions with customers, partners, suppliers, and collaborators; it understands how this information relates to its business objectives; and it acts to control and optimize its operations to meet its business objectives. Decisions are made quickly and accurately to modify business processes on the fly, dynamically allocate resources, or change business partners (e.g., suppliers, service providers) and partnerships (e.g., establish new service level agreements). This talk will describe challenges in managing the business operations of an intelligent enterprise. While a plethora of tools exist for managing the IT infrastructure (servers, storage, and network resources) of the enterprise, there is little systematic support today for the closed loop management and control of business operations. We will describe technology approaches to intelligent business operations management that we are pursuing at HP Labs., the progress we have made, and some open research questions.