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 applicationof analytics to derive insight and drive program efficiency. To show how to apply BDA effectively, it examines three important factors:
1.Data should be available and accessible to users
2.Analysts and managers need to understand how to process and draw insights from the data.
3.A context for the use of BDA needs to exist in which an organizations 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 organizations 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.
I. Conceptual
1. Big Data and Analytics in Government Organizations: A Knowledge-Based Perspective
Matthew Chegus
II. Setting the Stage for Analytics: The Organizational Perspective
2. Setting the Context for Analytics: Performance Management in Canadian Public Organizations: Findings of a Multi-Case Study
Sweec. Goh, Catherine Elliott, and Gregory Richards
3. Preparing for Analytics: The Dubai Government Excellence Program
Khaled Khattab and Rajesh K. Tyagi
III. Applications and Case Studies
4. Leveraging Innovation Systems: Supporting Science and Technology Capability Analysis through Big Messy Data Visualization
Andrew Valler And, Anthony J. Masys, and Gary Geling
5. Big Data Analytics and Public Bus Transportation Systems in China: A Strategic Intelligence Approach Based on Knowledge and Risk Management
Eduardo Rodriguez
6. Government of India Prepares for Big Data Analytics Using Aadhaar Card Unique Identification System
Nikhil Varma and Rajesh K. Tyagi
7. Visual Data Mining with Virtual Reality Spaces: Exploring Canadian Federal Government Data
Julio J. Valdes
8. Institutionalizing Analytics: A Case Study
Gregory Richards, Catherine Elliott, and Swee C. Goh
9. Modeling Data Sources
Okhaide Akhigbe and Daniel Amyot
10 Analyzing Predictors of Severe Traffic Accidents
Sean Geddes and Kevin Lai
Epilog. An Analytic Maturity Model for Government Organizations
Gregory Richards
Index
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