10,289 research outputs found

    Redesign and innovation in hospitals: foundations to making it happen

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    This paper describes key features of hospital redesign processes in Australia by analysing Victorian, NSW and other models. It discusses frameworks and drivers of large scale change in health systems including challenges and barriers to success.  The use of systems thinking and institutional entrepreneurship to support achieving change is described.   Insights are provided to enable policy development that can support innovation and system redesign. What is the problem? Australia\u27s demand for healthcare services is escalating, driven by an ageing population with complex health care needs, rising rates of chronic illness, increasing health care costs and rapid information technology innovation. These pressures may not be adequately met within the health system\u27s current and future economic capacity. Therefore, healthcare services and systems must achieve wide-ranging reform and redesign if they are to meet these challenges. The key questions for those working as health services leaders are: how can we support the innovation and change required to address this reality? and what should national policy makers do to support this work? What does the evidence say? Considerable evidence describes overlapping aspects of successful redesign in hospitals. These include: leadership to achieve change; the use of data to monitor and evaluate change; coherent alignment to organisational strategic plans; the development of organisational culture that is ready for change; and ensuring integration of change into routine practice. Systems thinking and institutional entrepreneurship offer approaches to change and redesign that take into consideration networks and relationships of individuals, teams and clinical disciplines working within it, resources and current processes and the cultural context of the organisation. What does this mean for health service leaders? In order to fully meet the requirements for redesign and innovation, health service leaders will need to address a number of key areas. First and foremost, leaders need to develop their organisational strategic vision around the concept of redesign and innovation and build staff understanding of the importance of these concepts. Staff must be given the capacity and confidence to pursue meaningful change in their everyday operations. Leaders must recognise the benefits of data and analytics and support the development of systems to utilise these tools. Innovative practices from outside of the health sector should be studied and adapted, and partnerships with industry and academia must be pursued. What does this mean for policy makers? Policy makers need to commit to investment in the concept of redesign and innovation. They should consider funding models that reward health services for innovation. Policy makers must support health services to pursue and sustain meaningful change while recognising that transformation requires time, perseverance and willingness to learn from success and failure

    Critical business intelligence practices to create meta-knowledge

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    In order to successfully implement strategies and respond to business variations in real-time, business intelligence (BI) systems have been deployed by organisations that assist in focused analytical assessments for execution of critical decisions. Although businesses have realised the significance of BI, few studies have explored their analytical decision-enabling capabilities linked to organisational practices. This study investigates the BI practices critical in creating meta-knowledge successfully for strategy-focused analytical decision-making. First, key BI suppliers are interviewed to develop an understanding of their BI capabilities and current deployment practices. Subsequently, two large BI implementation case studies are conducted to examine their practices in data transformation process. Findings reveal that BI practices are highly context-specific in mapping decisions with data assets. Complimentary static and dynamic evaluations provide holistic intelligence in predicting and prescribing a more complete picture of the enterprise. These practices vary across firms in their effectiveness reflecting numerous challenges and improvement opportunities.Publishe

    Assessment of process capabilities in transition to a data-driven organisation: A multidisciplinary approach

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    The ability to leverage data science can generate valuable insights and actions in organisations by enhancing data-driven decision-making to find optimal solutions based on complex business parameters and data. However, only a small percentage of the organisations can successfully obtain a business value from their investments due to a lack of organisational management, alignment, and culture. Becoming a data-driven organisation requires an organisational change that should be managed and fostered from a holistic multidisciplinary perspective. Accordingly, this study seeks to address these problems by developing the Data Drivenness Process Capability Determination Model (DDPCDM) based on the ISO/IEC 330xx family of standards. The proposed model enables organisations to determine their current management capabilities, derivation of a gap analysis, and the creation of a comprehensive roadmap for improvement in a structured and standardised way. DDPCDM comprises two main dimensions: process and capability. The process dimension consists of five organisational management processes: change management, skill and talent management, strategic alignment, organisational learning, and sponsorship and portfolio management. The capability dimension embraces six levels, from incomplete to innovating. The applicability and usability of DDPCDM are also evaluated by conducting a multiple-case study in two organisations. The results reveal that the proposed model is able to evaluate the strengths and weaknesses of an organisation in adopting, managing, and fostering the transition to a data-driven organisation and providing a roadmap for continuously improving the data-drivenness of organisations

    Systemic capabilities: the source of IT business value

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    Purpose – The purpose of this paper is to develop, and explicate the significance of the need for a systemic conceptual framework for understanding IT business value. Design/methodology/approach – Embracing a systems perspective, this paper examines the interrelationship between IT and other organisational factors at the organisational level and its impact on the business value of IT. As a result, a systemic conceptual framework for understanding IT business value is developed. An example of enhancing IT business value through developing systemic capabilities is then used to test and demonstrate the value of this framework. Findings – The findings suggest that IT business value would be significantly enhanced when systemic capabilities are generated from the synergistic interrelations among IT and other organisational factors at the systems level, while the system’s human agents play a critical role in developing systemic capabilities by purposely configuring and reconfiguring organisational factors. Practical implications – The conceptual framework advanced provides the means to recognise the significance of the need for understanding IT business value systemically and dynamically. It encourages an organisation to focus on developing systemic capabilities by ensuring that IT and other organisational factors work together as a synergistic whole, better managing the role its human agents play in shaping the systems interrelations, and developing and redeveloping systemic capabilities by configuring its subsystems purposely with the changing business environment. Originality/value – This paper reveals the nature of systemic capabilities underpinned by a systems perspective. The resultant systemic conceptual framework for understanding IT business value can help us move away from pairwise resource complementarity to focusing on the whole system and its interrelations while responding to the changing business environment. It is hoped that the framework can help organisations delineate important IT investment considerations and the priorities that they must adopt to create superior IT business value

    Becoming an analytics-based organisation : strategic agency in the change process in a retail organisation

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    The paper examines how the upward and downward strategic influences of the head of the BI unit in the case organization have evolved over time and the BI perspective became legitimate in the organization. The analysis covers a decade long period of time. We engaged in an Action Research (AR) inquiry where the change process was explored through the first-hand experiences of one of the co-authors. The model of the strategic agency of middle managers was applied in the analysis. We analyse the evolution as well as the enablers and constraints of the strategic agency of the head of the BI unit in the case organisation and identify the type of strategic agency exhibited in the case.<br /

    A Conceptual Model for the Application of Business Analytics in the Horizontal Strategic Alliance

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    The formation of strategic alliances amongst organisations has grown in recent years as globalisation has opened new markets for firms to pursue. It is of ever-increasing importance that organisations have a thorough understanding of the performance of their alliance to achieve competitive advantage. However, much research on strategic alliance has focused on examining the organisations within the alliance rather than focusing on the alliance itself. Using the new discipline of business analytics, this paper proposes a hierarchical model blending the functional roles of business analytics with data standardisation and context mediation frameworks to allow business analytics to be applied to horizontal strategic alliances with the aim of producing valid, alliance-wide strategic options. A proof of concept whereby the proposed model is theoretically applied to a real-life alliance in the airline industry is given, demonstrating how the model generates insight at the alliance level at each of the model\u27s five levels
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