Big and Better Data Revolutionizing Development | The Daily Star
12:00 AM, April 28, 2016 / LAST MODIFIED: 12:00 AM, April 28, 2016

Data to Drive the SDGs

Big and Better Data Revolutionizing Development

Lessons learned from the Millennium Development Goals have made it clear that there is a need for better data to monitor and implement the Sustainable Development Goals. The principle of Inclusiveness and Leaving no one Behind requires disaggregated data by geographic location and by sex and gender, but more specifically by population groups, such as children, women of reproductive age, youth and elderly, ethnic and religious minorities and other vulnerable groups.  

Sources of data
Censuses, Civil Registration Vital Statistics (CVRS), and Household Surveys are core instruments for the generation of demographic information.
While Population and Housing Censuses will continue to be the most important data source, they are conducted at lengthy intervals and therefore cannot monitor real-time change. A possible solution could be centralized population register records for up-to-date statistics on the size, characteristics and location of the population and of its components of change, namely births, deaths and migration. The system is in its inception stage in many countries of Asia, including Bangladesh. Currently only 39 per cent of births in South Asia are registered, despite being a necessary precondition of human rights. 
The Demographic and Health Survey (DHS) and the Multiple Indicator Cluster Survey (MICS) have become critical sources for monitoring progress on many aspects of health including sexual and reproductive health. In Bangladesh, the DHS however only provides division level data. In order for it to serve the Leave no one Behind purpose, there is a need for it to go deeper to district and upazila level and possibly even closer to village level. 

Examples of gaps in social and health Data
* Age and sex disaggregated data on fertility, contraceptive prevalence rate and unmet need for unmarried adolescents and youth. 
Age and spatial disaggregated data on physical and sexual violence against women and girls, particularly in educational institutions and workplaces.
A sample vital registration could be included in the PMA2020 (survey focusing on family planning indicators) surveys.
Data to track needs of people below the age of 15 and adults above the age of 49. 
Data on number of maternal deaths and their spatial concentration, prevalence of common morbidities affecting women, sexually transmitted infections, disaggregated SRH indicators among occupational groups such as tea garden workers, and coverage of SRH services in emergencies. 
There are constraints to get consistent SRH data from the private sector. 
Lack of a centralized MIS system that would bring together Data from different Government entities tasked with health services. 

Towards real-time data
The Data revolution can bridge the long time periods between census and surveys.  The CRVS can collect mortality data in real time through reports on the causes of death. The integration of diverse data sources via geo-referencing can produce evidence linking demography with other relevant processes, especially to monitor the reduction of spatial inequities in service delivery and health status. Better coordination in and between Government entities to centralize MIS systems in the Ministry of Health and Family Welfare will lead to a more comprehensive picture of national health. 
Advances in Big Data, non-sampled data characterized by the creation of databases from electronic sources, holds the promise of an exceptional development of new demographic knowledge. 

Integration of conventional and real-time data
There is a need for Population censuses to be increasingly integrated within a data ecosystem combining census data with administrative registers, household surveys and other new data sources. Geo-location could be used both for data collection and analytical purposes. Big data could complement traditional sources, but new policy frameworks are required to ensure responsible use. Data integration is expensive to carry out but saves money in the long run, by reducing the incidence of error and simplified replication.

Removing the firewall between data producers and users
Current approaches in many developing countries are heavily geared towards the production and processing of data. UNFPA's evaluation of the 2010 round of censuses globally revealed that growing support for the collection of census data, and even measurable improvements in dissemination, have not been matched by a growing use of the data.  

Partnerships to implement national and global commitments 
The generation of data is largely underfunded and uncoordinated. The 2030 Agenda points to the National Statistics Offices (NSOs) for leadership in monitoring and implementing the SDGs. Development partners, the United Nations System, as well as other relevant international organizations and multilateral institutions are encouraged to provide technical and financial assistance to NSOs in a coordinated fashion, as requested by national Governments. 

The way forward
The Statistical Act of 2013 has given the BBS the mandate to collect and endorse all official statistics. To track SDG indicators more investment and technical assistance should be channeled for data generation, particularly in CRVS. A stronger national leadership is needed to: 
Bring together relevant national entities that produce Data to do so in a way that meets the demands for monitoring of the SDGs
Bring together international partners to avoid duplications in technical and financial assistance.

Source: UNFPA Team.

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