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The book presents a model for assessing and systematically improving corporate agility in businesses. Agility enhances a company's responsiveness, innovative capacity, and resilience in crises, thereby creating an important success factor for businesses. For the successful implementation of an agile transformation, it is particularly important to proceed in a structured manner and accompany the transformation with professional expertise. With the INSERT Framework, a novel maturity and procedural model has been developed, which guides you step by step towards higher corporate agility. This framework prevents typical mistakes and risks of the agile transformation and optimizes success factors by utilizing best practices. Content Agile working methods as a success factor in modern corporate strategies The four maturity levels of corporate agility The phased model of the INSERT Framework: Initiation, Preparation, Execution
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This book is a volume in the Penn Press Anniversary Collection. To mark its 125th anniversary in 2015, the University of Pennsylvania Press rereleased more than 1,100 titles from Penn Press's distinguished backlist from 1899-1999 that had fallen out of print. Spanning an entire century, the Anniversary Collection offers peer-reviewed scholarship in a wide range of subject areas.
Know-how für erfolgreiche Self-Service-Initiativen Praktischer Leitfaden zur unternehmensweiten Einführung von Self-Service Fokus auf die Konzeption und Governance von Self-Service Mit Impulsen, was bei einer laufenden Self-Service-Organisation zu beachten ist Self-Service im BI- und Analytics-Kontext bedeutet, dass BI-Anwender selbst aktiv werden, um auf bestimmte Daten und Informationsprodukte zuzugreifen. Dabei hängt die Möglichkeit des Self-Service von Umgebungsfaktoren ab, nicht von einzelnen Werkzeugen. Um die Daten nutzen zu können, ist Datenkompetenz bei den Beteiligten erforderlich. Self-Service ist somit als strategischer Prozess zu verstehen, der als Teil der Datenstrategie i...
This self-contained monograph presents matrix algorithms and their analysis. The new technique enables not only the solution of linear systems but also the approximation of matrix functions, e.g., the matrix exponential. Other applications include the solution of matrix equations, e.g., the Lyapunov or Riccati equation. The required mathematical background can be found in the appendix. The numerical treatment of fully populated large-scale matrices is usually rather costly. However, the technique of hierarchical matrices makes it possible to store matrices and to perform matrix operations approximately with almost linear cost and a controllable degree of approximation error. For important classes of matrices, the computational cost increases only logarithmically with the approximation error. The operations provided include the matrix inversion and LU decomposition. Since large-scale linear algebra problems are standard in scientific computing, the subject of hierarchical matrices is of interest to scientists in computational mathematics, physics, chemistry and engineering.
Available online: https://pub.norden.org/temanord2022-563/ An increasing number of non-state actors are taking steps towards and beyond carbon neutrality and making claims about their contribution to global climate action. The voluntary use of carbon credits is one way to support more, earlier and faster climate action than what would be possible with own emission reductions alone, if high environmental and social integrity is ensured. The Nordic Dialogue on Voluntary Compensation brought together Nordic stakeholders to co-create guidance for the robust voluntary use of carbon credits in line with the long-term goals of the Paris Agreement and the UN Sustainable Development Agenda. This report summarises Nordic perspectives on best practice for the voluntary use of carbon credits and related claims, and recommendations for further Nordic cooperation in this field.
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