UNICEF and the data revolution March 11, 2014. Key data needs More complete global reporting on...

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UNICEF and the data revolution March 11, 2014

Transcript of UNICEF and the data revolution March 11, 2014. Key data needs More complete global reporting on...

Page 1: UNICEF and the data revolution March 11, 2014. Key data needs More complete global reporting on progress toward goals Data to achieve better results –

UNICEF and the data revolution

March 11, 2014

Page 2: UNICEF and the data revolution March 11, 2014. Key data needs More complete global reporting on progress toward goals Data to achieve better results –

Key data needs

• More complete global reporting on progress toward goals

• Data to achieve better results – accountability and results-based management

Page 3: UNICEF and the data revolution March 11, 2014. Key data needs More complete global reporting on progress toward goals Data to achieve better results –

Outline

• Big data• Surveys• User engagement

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Big Data Priority Areas

• Big Data for programming• Child Protection • Tower Data Project

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Big Data as an Information Source

• UNICEF’s comparative advantage is in connecting data to operational projects

• Have already done a year of work on this with PD and Global Pulse

• Using UN Data and working with other UN Agencies, Funds, and Programmes

• Using new data streams to combine with UNICEF’s work to give us more accurate predictive power and situational assessment

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Areas of interest for big data

• Early warning systems for natural disasters and other exogenous shocks

• Disease outbreak • Effectiveness of UNICEF Programs • Education progress • Population Movement • Scale and Scope of an Emergency • Understanding target populations• Understanding Youth Sentiment

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Child Protection and Big Data Protocols

• Write a Big Data and Child Protection protocol• Following on Child Protection protocols in

other areas• Equity focus – make sure those represented

are not just those with access to social media

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Tower Project

• Real-time system to see exogenous shock to societies through volume of calls and SMS at a per tower level

• Beginning hypothesis test looking at landslides in Eastern Uganda

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• UNICEF has a long history in monitoring the situation of children and women

• UNICEF’s plays a vital role to support: – data collection at country level (MICS)

– compilation and analysis of data

– disseminating these data for use in policy formulation and programme planning

• Without UNICEF’s support the development community would be unable to assess progress against global development goals, including the MDGs

UNICEF’s critical role in data collection, analysis and dissemination

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Global Reporting

Reports, profiles, websites etc.

AnalysisUN Agencies,

Interagency Groups, Research groups etc.

Compilation and Quality AssuranceDatabases

(Maintenance of global databases)UN Agencies, Interagency Groups

Data Collection Household surveys for coverage indicators

UNICEF-supported MICS

Effective global monitoring requires quality at each step

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UNICEF’s support for data collection Multiple Indicator Cluster Surveys (MICS)

• One of the largest data collection efforts on the MDGs globally

• Provides critically important information for well over 100 indicators including around half of the data for the child health related MDG indicators

• Started in 1995 and now over 240 MICS surveys conducted in over 100 countries

• The fifth round has been initiated with close to 50 countries participating and data will be used for:

‒ final MDG assessment

‒ baseline for post 2015 goals/targets

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Multiple Indicator Cluster Surveys (MICS) Since 1995, more than 100 countries and around 240 surveys*

*As of February 2013Countries with at least one MICS survey, including sub-national surveys

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MICS – Leading Data Source on Equity

Data collection through MICS and DHS are the primary source of disaggregated data

Multiple Indicator Cluster Surveys (MICS)

MICS provides data for 126 indicators which can be disaggregated by:

·geozones·residence (urban, urban-poor, rural)·gender·wealth·education·age·ethnicity/religion/language·other stratifiers·combinations of the above

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Better analysis of existing data is part of the data revolution

• Multidimensional poverty analysis (MPI, MODA)

• Supporting local use of these data• Using survey data in conjunction with routine

systems to validate progress

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• Strengthen citizen-led service delivery monitoring

• Support community awareness and demand for basic entitlements

• Provide targeted, community derived information to service delivery providers and “channels of influence”

• Create an “accountability chain” through publically available information

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Mass Citizen Participation via Mobile

Towards Engaging the 50m…

• Citizen reporting via mobile• +256,000 people registered• 8% response rate per poll (+/- 20,000 people)• 2 polls / week• U–Reporters in all 112 Districts• Average age: 24

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A Two Way Communication Platform

Two types of communication…

1. Information to improve individual/community development• Immunization, FHDs, Breastfeeding, Handwashing, etc.

2. Questions about development issues

Two types of response:• Multiple choice – pre-selected• SMS – individual narration

In its essence, U-Report is

A Communication 4 Development Tool

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Supporting a Virtual Cycle of Engagement

Empowerment and Demand for Accountability

Demand for Accountability

Empowerment

The Citizen

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Supporting our AdvocacyLinkage with Parliament and media

• All 384 MPs are U-Reporters• Poll results are communicated via print, radio and TV media• Some MPs requesting polls to better understand the views of their

constituents• Some Ministries and Development Partners have requested polls (ie

Agriculture, WB)

Direct action by decision makers

=

Game Changer!

A new form of advocacy that can trigger service delivery and good governance

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Challenges

• Biases inherent in all data sources—traditional, big data, real-time

• The “signal problem” in big data• “social-science approaches help us to ask productive

questions about data to prevent us from falling victim to our own cognitive biases that often suggest answers we expect or lead us to results we wish to find.” Kate Crawford

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Ways forward

• Fitness of purpose for data—articulating the sources, their strengths and weaknesses and appropriate uses

• Integrated framework where we use new data sources where appropriate but triangulate and validate data

• Protecting the independence and quality of data

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data.unicef.org