predictive analytics in uae government organizations
DESCRIPTION
This presentation is to create awareness of the use the use of predicative analytics in public sector organizations with emphasis on UAE government organizations.TRANSCRIPT
www.mofa.gov.ae
Predictive Analytics in UAE Government Organizations
Dr. Saeed Al Dhaheri
Advisor, Ministry of Foreign Affairs – U.A.E@DDSaeed
IDC Big Data and Business Analytics Forum, 18 November 2013, Abu Dhabi
2
Predictive Analytics in UAE Government Organizations: Agenda
statistics
Overview and definition
drivers
challenges
Potential for predictive analytics in government
examples
Building Predictive analytics capability in UAE government sector
Technology tools used for predictive analytics
conclusion
3
World Wide interest in Big Data and Predictive analytics
4
Statistics: Analytics big bang
The rate of CIO investing in analytics and big data technologies in the ME is
growing more from 12% in 2012 to more than 40% in 2013 – IDC
Investment is expected to increase at CAGR of more than 20% over the
next five years – IDC
New jobs arising: Data Scientist
5
6
Overview and Definitions
Big Data: collection of data sets so large and complex and difficult to
process using traditional data processing techniques
Forces: mobile, social media, information and cloud are driving big data
Predictive analytics (PA): encompasses a variety of techniques from
statistics, modelling, machine learning, and data mining that analyze current
and historical facts to make predictions about future, or otherwise unknown,
events
Based on predictive models and data mining
PA answers what is likely to happen?
Types of analytics:
– Descriptive analytics: insight into what is happening
– Predictive analytics: understand what can potentially happen
– Prescriptive analytics: how to make specific outcomes happen
7
Strategic Drivers
UAE Gov vision to be one of the best government in the world by 2021
Smart city initiatives (e.g, Dubai smart city initiative)
Digital government initiative - increasing volume of data
Internet of things adoption (M2M applications)
– Example: salik by RTA, smart metering by ADWEA and DEWA, security
and surveillance
8
Challenges
organizational
– Lack of understanding of the value of PA
– Lack of analytical talent in government
– A general lack of career paths for analysts who do not transition to management
roles is a serious issue for employee retention
Technical
– Perceived complexity of PA
– Building the predictive models is sometimes complex process
Cultural
9
Potential for Predictive Analytics in Government
Law enforcement – “why just count crime when you can predict it!”
– Shifting crime fighting work from reactive to predictive and preventative
modes
– Examples:
Police force deployment decisions:
Models to predict area at greater risk for violent crime
Identify suspicious patterns to detect and prevent fraud
Health Care
– To determine which patients are at risk of developing certain conditions,
like diabetes, asthma, heart disease, and other lifetime illnesses
10
Best Practice: Singapore example
Singapore has positioned data & Analytics as a key driver for
competitiveness and growth
– Integrated approach
– Developing infocom industry and manpower capabilities
– Establishing data exchange platform
– Formulating the appropriate data policies
– Developing data hubs
Government business analytics program
11
Best Practice: Australia Public Service big data strategy
DACoE builds analytics capability across government
- a common capability framework
- sharing technical knowledge, skills and tools
- building collaborative arrangements to develop analytics professionals
12
Big data & Analytics example: Etihad Airways
Etihad airways uses big data and analytics in many ways:
maximizing income opportunities (optimizing pricing strategy)
forecasting maintenance and spot problems before happening
Benefits:
Reduce fuel consumption and shorten turn-around-time at airports
improve the traveller’s experience while on board.
13
Big data and Analytics example: Masdar Institute
Masdar institute is very active in research and development
– Workshop: Data analytics for renewable energy integration
Renewable energy integration
– Multidisciplinary issue
– Example of research topics:
– forecasting of electricity supply
and demand,
– detection of faults
– demand response applications
14
MoFA interest in business analytics
Building up use cases for analytics
– MoFA mobile app usage and performance
– Staff deployment at UAE missions overseas
15
Building PA capability in UAE Government Organizations
Five critical enablers: building maturity in each area
– People
– Processes
– Technology
– Data
– Governance
Raising awareness
Training programs
16
Technology
BI vendors offer advanced analytics tools
New generation BI software offers more user friendly
visual PA for more pervasive adoption
On premise vs. cloud based solutions
Look for free or cheap tools for experimentation
Plan and implement proper Infrastructure for big data
and analytics
17
Conclusions
Government needs to move to data-driven decision making culture
More collaboration between the federal and local government is needed in
information sharing
Leadership sponsorship is important
Start small, demonstrate value and grow
Data governance and Data quality is key to successful PA projects
PA needs to be more invisible to users and embedded at points of decision
or action
Don’t rush into PA tools before proper planning
18
Thank you