Government organizations are no different than private organizations when it comes to ensuring the delivery of value for money. Managers and politicians alike seek to do the best they can often do with limited budgets as they work in an environment characterized by rapidly changing external conditions. Where government organizations differ from those in the private sector is in the level of complexity and ambiguity that is part and parcel of managing in public-sector organizations.
Within this context, big data analytics (BDA) can be an important tool given that many analytic techniques within the big data world have been created specifically to deal with complexity and rapidly changing conditions. The important task for public sector organizations is to liberate analytics from narrow scientific silos and expand it across internally to reap maximum benefit across their portfolios of programs.
This book focuses on the application of analytics to derive insight and drive program efficiency. To show how to apply BDA effectively, it examines three important factors:
- Data should be available and accessible to users
- Analysts and managers need to understand how to process and draw insights from the data.
- A context for the use of BDA needs to exist in which an organization’s management team relies on evidence for decision-making and overall management.
This book highlights contextual factors important to better situating the use of BDA within government organizations and demonstrates the wide range of applications of different BDA techniques. It emphasizes the importance of leadership and organizational practices that can improve performance. It explains that BDA initiatives should not be bolted on but should be integrated into the organization’s performance management processes. Equally important, the book includes chapters that demonstrate the diversity of factors that need to be managed to launch and sustain BDA initiatives in public sector organizations.
Big Data And Analytics Applications In Government PDF: Current Practices And Future Opportunities (Data Analytics Applications)
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