The aim of this study was to assess the impact that Business Process Excellence has on the innovation process to create new products and services in the software development environment. The best practices were identified in the current use of BPE in software development organisations. Subsequently, a proposal was put forward to enhance the use of BPE in the software development process to create innovative products and services. Once these products are implemented the organisation can use these products as a sustainable competitive advantage. The use of Business Process Excellence in software development creates an innovative environment for employees in order to develop innovative products that can create shareholder wealth, and increase market share. Companies want to create products that are unique to the market, and be able to offer their customers products that only they can offer in order to secure future business. Innovation is a key factor to enhance processes within the software development company. Enhancing the processes can generate new ideas that contribute to the sustainable competitive advantage of the company. The literature does not create a definite link between the use of Business Process Excellence and innovation, and the study aimed at evaluating the possibility to merge the concepts. Business Process Excellence optimises a currently implemented process, by exploring all ideas to increase the effectiveness of the system. It is a structured way to ensure that all possibilities are explored before a decision is made on how the process is structured to implement new products or services. The software development industry is a very competitive industry, and most companies do not share their competitive strategy, or make it available to the public, to ensure that they would be offering their customer something unique. These companies would only make their strategy known to the market once the new product or service is launched, and the trend is set for other companies to follow. It also creates the opportunity for companies to become the market leader within the industry, to ensure growth, and increase profits. Some key aspects were identified that companies could focus on to encourage an innovative environment. Most employees are willing to accept responsibility for the v innovative ideas, since this will benefit the company. Managers should take responsibility for their actions within the software development department, and reward employees that assist in reaching the goals set in company strategy. The software development process should always include a step for quality and reliability. This step is needed, since even the most innovative product needs to be stable and reliable, otherwise the product will not be used by customers if they are frustrated. / Thesis (MBA)--North-West University, Potchefstroom Campus, 2012.

This research is concerned with investigating reengineering teams in the context of business process change, or more widely known, business process reengineering (BPR). Business Process Change, on the one hand, is still considered as being an approach that is required in recent times. Reengineering teams (teams that are involved with the planning, analysis and design of the approach) on the other hand, have been viewed to be essential for the development and implementation of BPR. Bearing these points in mind, it was discovered that although the reengineering teams area warrants attention, there has been little attention paid to it. In the reengineering area, specifically, this research aims to address two main issues: first, the role of reengineering teams in business process change and second, the human and organisational aspects that surround the teams. For this, the research applied several steps and they are described in the following paragraphs. To discover the role of the reengineering teams in the context of business process change, it was initially assumed that the foundations of the BPR lie in organisational change. Using this assumption, it became simpler and clearer to determine the exact role of teams. With regards to the human and organisational aspects, a strategy unique to the topic was adopted. At the outset, some human and organisational aspects that are more commonly found in the organisational behaviour and psychology areas were revealed and research with regards to these particular aspects was described. Whilst that was the theoretical side of the research, the research then had to determine whether the deductions formed from the theoretical side were evident in practice. For the empirical results, the research used a combination of approaches in order to obtain the desired results. A qualitative approach that has its foundations in Interpretivism was the methodology used in the research. The ontology assumed then that subjective meanings could be assumed to reconstruct reality. Evidence from practice was obtained using initially, two pilot studies. Further, a multiple case study strategy and the research techniques of mainly, interviews and referring to archival documents were utilised. Once the data was analysed, a theory that could be used for future research in the reengineering teams area was developed. This was arrived at using a combination of certain grounded theory techniques, particularly, the forming of categories and coding. The findings suggested that reengineering teams are imperative for BPR and that some of the selected human and organisational aspects are evident in the newly formed theory.

In this thesis, eliciting system functional requirements based on business requirements during software intensive systems acquisition or development process is investigated and an approach is proposed for this purpose. Concepts and current problems within the framework of business requirements are investigated with a general literature review of requirements engineering and technology acquisition. Determination of requirements of IT system to be acquired according to the business objectives and base lining business processes is dealt with business process modeling. ARIS providing integrated and complete information system architecture along with modeling techniques and modeling tool is also investigated. Proposed approach recommends EEPC as process modeling technique and ARIS software as supporting toolset, and explains how to conduct application of automatic requirements eliciting from business process models, by extending a reporting script provided by ARIS software. Proposed approach was partially applied to the real project and the obtained results were presented in this thesis.

The purpose of this work is to provide simulation-based support for making optimal (or near-optimal) decisions in situations where decision makers are faced with imperfect information. We develop several novel techniques and algorithms for simulation-based optimization and decision support and apply them to two categories of problems: (i) Unmanned Aerial Vehicle (UAV) path planning in search operations, and; (ii) optimization of business process models. Common features of these two problems for which analytical approaches are not available, are the presence of imperfect information and their inherent complexity. In the UAV path planning problem, the objective is to define the path of a UAV searching for a target on a known road network. It is assumed that the target is moving toward a goal and we have some uncertain information about the start point of the target, its velocity, and the final goal of the target. The target does not take evasive action to avoid being detected. The UAV is equipped with a sensor, which may detect the target once it is in the sensor’s scope. Nevertheless, the detection process is uncertain and the sensor is subject to both false-positive and false-negative errors. We propose three different solutions, two of which are simulation-based. The most promising solution is an on-line simulation-based method that estimates the location of the target by using a Sequential Monte Carlo (SMC) method. During the entire mission, different UAV paths are simulated and the one is chosen that most reduces the uncertainty about the location of the target. In the optimization of the business process models, several different but related problems are addressed: (i) we define a measure of performance for a business process model based on the value added by agents (employees) to the process; (ii) we use this model for optimization of the business process models. Different types of processes are distinguished and methods for finding the optimal or near-optimal solutions are provided; (iii) we propose a model for estimating the performance of collaborative agents. This model is used to solve a class of Assignment Problems (AP), where tasks are assigned to collaborative agents; (iv) we propose a model for team activity and the performance of a team of agents. We introduce different collaboration strategies between agents and a negotiation algorithm for resolving conflicts between agents. We compare the effect of different strategies on the output of the team. Most of the studied cases are complex problems for which no analytical solution is available. Simulation methods are successfully applied to these problems. They are shown to be more general than analytical models for handling uncertainty since they usually have fewer assumptions and impose no restrictions on the probability distributions involved. Our investigation confirms that simulation is a powerful tool for providing decision-making support. Moreover, our proposed algorithms and methods in the accompanying articles contribute to providing support for making optimal and in some cases near-optimal decisions: (i) our tests of the UAV simulation-based search methods on a simulator show that the on-line simulation method has generally a high performance and detects the target in a reasonable time. The performance of this method was compared with the detection time when the UAV had the exact information about the initial location of the target, its velocity, and its path (minimum detection time). This comparison indicated that the online simulation method in many cases achieved a near-optimal performance in the studied scenario; (ii) our business process optimization framework combines simulation with the Hungarian method and finds the optimal solution for all cases where the assignment of tasks does not change the workflow of the process. For the most general cases, where the assignment of tasks may change the workflow, we propose an algorithm that finds near-optimal solutions. In this algorithm, simulation, which deals with the uncertainty in the process, is combined with the Hungarian method and hill-climbing heuristics. In the study of assigning tasks to collaborative agents we suggest a Genetic Algorithm (GA) that finds near-optimal solutions with a high degree of accuracy, stability, scalability and robustness. While investigating the effect of different agent strategies on the output of a team, we find that the output of a team is near-optimal, when agents choose a collaboration strategy that follows the principle of least effort (Zipf’s law) and use our suggested algorithm for negotiation and resolving conflicts. / QC 20111202

In the past decades, organizations had to face numerous challenges due to intensifying globalization and internationalization, shorter innovation cycles and growing IT support for business. Business process management is seen as a comprehensive approach to align business strategy, organization, controlling, and business activities to react flexibly to market changes. For this purpose, business process models are increasingly utilized to document and redesign relevant parts of the organization's business operations. Since companies tend to have a growing number of business process models stored in a process model repository, analysis techniques are required that assess the quality of these process models in an automatic fashion. While available techniques can easily check the formal content of a process model, there are only a few techniques available that analyze the natural language content of a process model. Therefore, techniques are required that address linguistic issues caused by the actual use of natural language. In order to close this gap, this doctoral thesis explicitly targets inconsistencies caused by natural language and investigates the potential of automatically detecting and resolving them under a linguistic perspective. In particular, this doctoral thesis provides the following contributions. First, it defines a classification framework that structures existing work on process model analysis and refactoring. Second, it introduces the notion of atomicity, which implements a strict consistency condition between the formal content and the textual content of a process model. Based on an explorative investigation, we reveal several reoccurring violation patterns are not compliant with the notion of atomicity. Third, this thesis proposes an automatic refactoring technique that formalizes the identified patterns to transform a non-atomic process models into an atomic one. Fourth, this thesis defines an automatic technique for detecting and refactoring synonyms and homonyms in process models, which is eventually useful to unify the terminology used in an organization. Fifth and finally, this thesis proposes a recommendation-based refactoring approach that addresses process models suffering from incompleteness and leading to several possible interpretations. The efficiency and usefulness of the proposed techniques is further evaluated by real-world process model repositories from various industries. (author's abstract)

Le marché du véhicule électrique (VE) est aujourd’hui en plein essor et il s’agit d’un marché quireprésente un intérêt pour des industriels comme EDF. Pour réaliser ses objectifs (optimisation de laconsommation, tarification...) EDF doit d’abord extraire des données hétérogènes (issues des VE etdes bornes de recharge) puis les analyser. Pour cela nous nous sommes orientés vers un entrepôt dedonnées (ED) qui est ensuite exploité par les processus métiers (PM). Afin d’éviter le phénomèneGarbage In/Garbage Out, les données doivent être traitées. Nous avons choisi d’utiliser une ontologiepour réduire l’hétérogénéité des sources de données. La construction d’une ontologie étant lente, nousavons proposé une solution incrémentale à base briques ontologiques modulaires liées entre elles. Laconstruction de l’ED, basé sur l’ontologie, est alors incrémentale. Afin de charger des données dansl’ED, nous avons défini les processus ETL (Extract, Transform & Load) au niveau sémantique. Ensuitenous avons modélisé les PM répétitifs selon les spécifications BPMN (Business Process Modelisation& Notation) pour extraire les connaissances requises par EDF de l’ED. L’ED constitué possède lesdonnées et des PM, le tout dans un cadre sémantique. Nous avons implémenté cela sur la plateformeOntoDB développée au Laboratoire d’Informatique et d’Automatique pour les Systèmes de l’ISAEENSMA.Elle nous a permis de manipuler l’ontologie, les données et les PM d’une manière homogènegrâce au langage OntoQL. De plus, nous lui avons fourni la capacité d’exécuter automatiquement lesPM. Cela nous a permis de fournir à EDF une plate-forme adaptée à leurs besoins à base d’élémentsdéclaratifs. / Nowadays, the electrical vehicles (EV) market is undergoing a rapid expansion and has become ofgreat importance for utility companies such as EDF. In order to fulfill its objectives (demand optimization,pricing, etc.), EDF has to extract and analyze heterogeneous data from EV and charging spots. Inorder to tackle this, we used data warehousing (DW) technology serving as a basis for business process(BP). To avoid the garbage in/garbage out phenomena, data had to be formatted and standardized.We have chosen to rely on an ontology in order to deal with data sources heterogeneity. Because theconstruction of an ontology can be a slow process, we proposed an modular and incremental constructionof the ontology based on bricks. We based our DW on the ontology which makes its construction alsoan incremental process. To upload data to this particular DW, we defined the ETL (Extract, Trasform& Load) process at the semantic level. We then designed recurrent BP with BPMN (Business ProcessModelization & Notation) specifications to extract EDF required knowledge. The assembled DWpossesses data and BP that are both described in a semantic context. We implemented our solutionon the OntoDB platform, developed at the ISAE-ENSMA Laboratory of Computer Science and AutomaticControl for Systems. The solution has allowed us to homogeneously manipulate the ontology, thedata and the BP through the OntoQL language. Furthermore, we added to the proposed platform thecapacity to automatically execute any BP described with BPMN. Ultimately, we were able to provideEDF with a tailor made platform based on declarative elements adapted to their needs.

The design and development of process-aware information systems is often supported by specifying requirements as business process models. Although this approach is generally accepted as an effective strategy, it remains a fundamental challenge to adequately validate these models given the diverging skill set of domain experts and system analysts. As domain experts often do not feel confident in judging the correctness and completeness of process models that system analysts create, the validation often has to regress to a discourse using natural language. In order to support such a discourse appropriately, so-called verbalization techniques have been defined for different types of conceptual models. However, there is currently no sophisticated technique available that is capable of generating natural-looking text from process models. In this paper, we address this research gap and propose a technique for generating natural language texts from business process models. A comparison with manually created process descriptions demonstrates that the generated texts are superior in terms of completeness, structure, and linguistic complexity. An evaluation with users further demonstrates that the texts are very understandable and effectively allow the reader to infer the process model semantics. Hence, the generated texts represent a useful input for process model validation.

Process-oriented organisations need to manage the different types of responsibilities their employees may have w.r.t. the activities involved in their business processes. Despite several approaches provide support for responsibility modelling, in current Business Process Management Systems (BPMS) the only responsibility considered at runtime is the one related to performing the work required for activity completion. Others like accountability or consultation must be implemented by manually adding activities in the executable process model, which is time-consuming and error-prone. In this paper, we address this limitation by enabling current BPMS to execute processes in which people with different responsibilities interact to complete the activities. We introduce a metamodel based on Responsibility Assignment Matrices (RAM) to model the responsibility assignment for each activity, and a flexible template-based mechanism that automatically transforms such information into BPMN elements, which can be interpreted and executed by a BPMS. Thus, our approach does not enforce any specific behaviour for the different responsibilities but new templates can be modelled to specify the interaction that best suits the activity requirements. Furthermore, libraries of templates can be created and reused in different processes. We provide a reference implementation and build a library of templates for a well-known set of responsibilities.

Large corporations increasingly utilize business process models for documenting and redesigning their operations. The extent of such modeling initiatives with several hundred models and dozens of often hardly trained modelers calls for automated quality assurance. While formal properties of control flow can easily be checked by existing tools, there is a notable gap for checking the quality of the textual content of models, in particular, its activity labels. In this paper, we address the problem of activity label quality in business process models. We designed a technique for the recognition of labeling styles, and the automatic refactoring of labels with quality issues. More specifically, we developed a parsing algorithm that is able to deal with the shortness of activity labels, which integrates natural language tools like WordNet and the Stanford Parser. Using three business process model collections from practice with differing labeling style distributions, we demonstrate the applicability of our technique. In comparison to a straightforward application of standard natural language tools, our technique provides much more stable results. As an outcome, the technique shifts the boundary of process model quality issues that can be checked automatically from syntactic to semantic aspects.

This thesis deals with the problem of the transport company reservation system innovation. Innovation includes definition and automation of new processes, new system for expenses control and web pages optimalized for using on mobile phones and tablets. According to IS innovation problem analysis and transport company requirements the new IS will be designed and implemented.