8 research outputs found

    Towards Objectives-Based Process Redesign

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    Continuously growing and changing multinational companies oftentimes struggle with heterogeneous degrees of standardization.Especially in case of redesigning business processes that have been historically grown over decades, the capability of handlingsemi-structures process is central. Nevertheless, for competitive advantages, it is essential for a company to work on the optimizationof all processes. Existing redesign techniques either focus on completely unstructured or structured processes. TheRedesign Model presented in this paper transforms processes with any level of structuredness into processes with an increaseddegree of standardization. Our technique consists of four main steps: (i) we extract the objectives for an efficient business processredesign from existing literature; (ii) we formulate a list of requirements an innovative redesign model has to fulfill; (iii) wepresent a design science based Business Process Redesign Framework including our Redesign model; (iv) we evaluate our modelshowing its applicability and completeness

    QUALITY OF PROCESS ? A BUSINESS PROCESS PERSPECTIVE ON QUALITY OF SERVICE

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    The fundamental paradigm shift from a product- to a service-oriented economy implies novel technical and organizational challenges. The resulting dynamic of the technical infrastructure and the increasing development towards requesting external business services to be integrated into end-to-end business processes requires mechanisms ensuring the reliability of the organization?s composed services, workflows and business processes. From a business perspective, QoS characteristics defined based on technical services within the infrastructural layer have to be aggregated to more business-relevant Key Performance Indicators on business process layer to express the Quality of Process. These KPIs represent quality that is highly related to the business?s performance (e.g. processing time of a business service) and are crucial for achieving predefined goals in order to stay competitive in the market. The contribution of this paper is threefold: We (i) provide an in-depth requirements analysis for such a holistic quality management framework, we (ii) develop a holistic aggregation framework which enables service level aggregation incorporating the loosely coupled structure of business processes with invoked systems and services in an instance based manner. To demonstrate the expressive power of our framework we (iii) provide an exemplary industrial application scenario and illustrate the functioning and interplay of the designed artifacts

    Service Contract Automation

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    Today’s transition from a product- to a service-oriented economy implies fundamental technical, organizational and economic challenges. The trend of compensating missing core competencies by requesting business services from external providers to be integrated in internal end-to-end processes has recently gained tremendous momentum. Nevertheless, service level agreements between the parties involved are still specified for each service entity that is part of composite business services which results in a managerial overhead generated from multiple contractual relations. The contribution of this paper is threefold: (i) We analyze the fundamental requirements in the context of describing services, quality and agreements as well as their aggregation in a generic manner. Based on the results, we (ii) provide a holistic framework that enables the automation of service contracts for composite business services. Facilitating semantic technologies we provide means for describing service quality from a technical and business-oriented perspective, adequate metrics as well as quality aggregation operations in the context of composite business services. Furthermore, we (iii) evaluate our framework based on an industrial application scenario

    Networked Mechanism Design Incentive Engineering in Service Value Networks as Exemplified by the Co-Opetition Mechanism

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    The software industry is currently experiencing a fundamental transition from selling proprietary applications towards the provision of networked services – i.e. modularized and specialized services composed in a plug-and-play fashion in networked service systems. In such service systems, participants’ interests need to be aligned with the network’s global objectives in an incentive engineering approach. In more detail, this paper seeks to tackle the challenge of coordinating self-interested service providers in a co-opetitive environment by designing adequate mechanisms. However, “classic” mechanism design focuses on design goals such as efficiency, incentive compatibility and budget balance whose mere consideration does not always hit the target in service networks. Incorporating the requirements that are imposed by newly arising networked scenarios where a set of agents must cooperate to create value resulting in a complex service, we propose a novel variation of mechanism design: networked mechanism design. Following this approach, we present the co-opetition mechanism as a possible instantiation of networked mechanism design which pursues network-related goals such as network growth, a high degree of interconnectedness, readiness to deliver, and fairness

    Data analytics for smart decision-making and resilient systems

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    In a networked world, companies depend on fast and smart decisions, especially when it comes to reacting to external change. With the wealth of data available today, smart decisions can increasingly be based on data analysis and be supported by IT systems that leverage AI. A global pandemic brings external change to an unprecedented level of unpredictability and severity of impact. Resilience therefore becomes an essential factor in most decisions when aiming at making and keeping them smart. In this chapter, we study the characteristics of resilient systems and test them with four use cases in a wide-ranging set of application areas. In all use cases, we highlight how AI can be used for data analysis to make smart decisions and contribute to the resilience of systems
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