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National Bureau of Statistics Integration of Data Produced by Various Sources to Produce SDGs National Bureau of Statistics Integration of Data Produced by Various Sources to Produce SDGs Indicators Tanzania Experience

National Bureau of Statistics Tanzania Country Profile Important Statistics: - § Land Area : National Bureau of Statistics Tanzania Country Profile Important Statistics: - § Land Area : 945, 087 Square Km § Total Pop. (2017) = 52 million people § Life expectancy at birth: 62 yrs § Pop growth rate: 2. 7 § GDP growth rate: 7. 0 (2016) § Annual Av. Inflation Rate (2016): 5. 2% § Pop. Below basic needs: 28. 2% 2

Integration of Data Produced by Various Sources to Produce SDGs Indicators Outline 1. Tanzania’s Integration of Data Produced by Various Sources to Produce SDGs Indicators Outline 1. Tanzania’s Data Ecosystem 2. SDGs Data Gaps Assessment 3. Data Innovations in Tanzania towards SDGs implementation 4. Challenges 5. The Way Forward

Integration of Data Produced by Various Sources to Produce SDGs Indicators 1. Tanzania’s Data Integration of Data Produced by Various Sources to Produce SDGs Indicators 1. Tanzania’s Data ecosystem – Key Actors § A data ecosystem is the complex system of relationships between data producers, suppliers and users; it also include Research and Training Institutions Key Actors in NSS BIG DATA Service delivery and Planning data Service delivery data MDAs CSOs LGAs Socio economic data Official Statistics NBS Specialised data Research Inst. EOB DPs Private Sector National and International data CGD Business and economic data

Integration of Data Produced by Various Sources to Produce SDGs Indicators 1. Tanzania’s Data Integration of Data Produced by Various Sources to Produce SDGs Indicators 1. Tanzania’s Data ecosystem – Highlight on Legal Framework. . § The NBS is mandated by the Statistics Act, 2015 to coordinate production of Official Statistics within the NSS. § Official Statistics Includes statistics produced by: i. NBS ii. Government Institutions; and iii. agencies*. *Statistics produced by agencies (Research Institutions, NGOs, DPs or any other person) shall qualify to be official statistics if they meet the criteria and standards set by the NBS and approved by the DG.

Integration of Data Produced by Various Sources to Produce SDGs Indicators 1. Tanzania’s Data Integration of Data Produced by Various Sources to Produce SDGs Indicators 1. Tanzania’s Data ecosystem – Highlight on Legal Framework. . § Tanzania’s Statistical Act, 2015 insists on a need for provision of high quality, reliable and timely official statistical information to the public. § NBS provides methods, standards, concepts and definitions for the production of official statistics and to also regulate the official information. § NBS is responsible for issuing code of practice for official statistics including setting up professional standards to be followed by all agencies authorized to produce official statistics

Integration of Data Produced by Various Sources to Produce SDGs Indicators 1. Tanzania’s Data Integration of Data Produced by Various Sources to Produce SDGs Indicators 1. Tanzania’s Data ecosystem – Highlight on Legal Framework. . § In general, the Act provides both challenges and opportunities in production of Official Statistics § On opportunities: NBS can collaborate with other actors such as academia, private sector and CSOs in production of Official Statistics; This opportunity is consistent with the philosophy of the Post-MDG Agenda, which calls for a need to engage multiple actors in data generation for monitoring the SDGs through the Data Revolution. § Challenge: - The issue of Big Data Ecosystem. . CGD. . . in Tanzania is not well covered which may result into delay in terms of usage and analysis these kind of data sources.

Integration of Data Produced by Various Sources to Produce SDGs Indicators 1. Tanzania’s Data Integration of Data Produced by Various Sources to Produce SDGs Indicators 1. Tanzania’s Data ecosystem - Experience with MDGs Monitoring § The Data ecosystem showed some mixed experiences; § it proved to be successful in MDGs for some indicators such as education-related targets where data was readily available from multiple sources and at a reasonable frequency § On other hand, it proved to be challenging on some indicators, especially, those related to environmental and some of health-related dimensions § Generally, the systems was generating data with either huge lags, with some quality concerns or unavailable all together §

Integration of Data Produced by Various Sources to Produce SDGs Indicators 1. Tanzania’s Data Integration of Data Produced by Various Sources to Produce SDGs Indicators 1. Tanzania’s Data ecosystem - Experience with MDGs Monitoring. . § The review of MDG experiences reveals some issues, which serve as the lessons to inform Tanzania data ecosystem for SDGs § The need for strengthening existing Tanzania Data Ecosystem through Data Revolution § Alignment of global and national development agendas is important for better monitoring and development outcomes § Data Ecosystem for SDGs should be inclusive in a sense that nobody is left behind - data should be available in disaggregated forms representing different population groups § Enhancement of statistical capacity within NSS to ensure quality of data produced § The data ecosystem should have a clear demarcation between what is to be monitored at different levels such as sub national level, nationally, regionally and globally to avoid confusions in reporting progress

Integration of Data Produced by Various Sources to Produce SDGs Indicators 2. SDGs Data Integration of Data Produced by Various Sources to Produce SDGs Indicators 2. SDGs Data Gaps Assessment - Engagement with Data Communities within NSS Two National Workshops conducted: Awareness Creation Creating ownership of the SDGs Build partnerships with stakeholders Plan for National Data Roadmap dev. Participants: The Government, Civil Society Organizations , Academic Institutions, Research Institutions, Private Sector, Development Partners and other international collaborators

Integration of Data Produced by Various Sources to Produce SDGs Indicators 2. SDGs Data Integration of Data Produced by Various Sources to Produce SDGs Indicators 2. SDGs Data Gaps Assessment. . -Engagement with Data Communities within NSS Training and workshops on ADAPT for SDGs data gap assessment Domestication of SDGs and preparation for preliminary results Development of M&E Framework for FYDP II with Planning Commission SDGs awareness seminars for all LGAs by PED; Development of draft SDGs baseline report, 2016 by PED Ongoing preparations for development of a SDGs, AU 2063 Development Agenda , EAC Vision 2050 and FYDPII data visualization

Integration of Data Produced by Various Sources to Produce SDGs Indicators SDGs Data Gaps Integration of Data Produced by Various Sources to Produce SDGs Indicators SDGs Data Gaps Assessment. . -Engagement with Data Communities within NSS NBS in collaboration with the UN Women, line Ministry and other Partners conducted the first thematic forum on SDGs focusing on Gender Data, in May, 2017 Data dive workshops for Open Data Portal; Health, Water, Education and Agriculture Sectors.

Integration of Data Produced by Various Sources to Produce SDGs Indicators 2. SDGs Data Integration of Data Produced by Various Sources to Produce SDGs Indicators 2. SDGs Data Gaps Assessment - Domestication of SDGs - Phases. . Phase-III Data entry for all Available FYDP II indicators and Metadata into the ADAPT; NBS, Mo. FP and d. LAB Development of Missing FYDP II Metadata and Data entry into the ADAPT – MDAs, NBS, Mo. FP and d. LAB Mapping and Domestication of FYDP II Indicators with SDGs Phase-IV Higher Level Data Validation, reconciliation and Mult stakeholder Engagement

Integration of Data Produced by Various Sources to Produce SDGs Indicators 2. SDGs Data Integration of Data Produced by Various Sources to Produce SDGs Indicators 2. SDGs Data Gaps Assessment - Domestication of SDGs. . FYDP II Indicators into the ADAPT The FYDP II has 282 indicators classified into four themes Out of 282 indicators of the FYDP II; only 39% are produced by the NBS, (Census and Surveys) 61% are produced by MDAs and other data producers in NSS Need to strengthening routine data collection systems within the NSS to fill the data gaps

Integration of Data Produced by Various Sources to Produce SDGs Indicators 2. SDGs Data Integration of Data Produced by Various Sources to Produce SDGs Indicators 2. SDGs Data Gaps Assessment - Domestication of SDGs. . Availability of metadata for FYDP II Metadata are vital in making decisions during the mapping exercise 41% of all FYDP II indicators had metadata already 59% required extra effort and resources for development

Integration of Data Produced by Various Sources to Produce SDGs Indicators 2. SDGs Data Integration of Data Produced by Various Sources to Produce SDGs Indicators 2. SDGs Data Gaps Assessment - Domestication of SDGs. . Distribution of Mapped SDGs Indicators with FYDP II and OII Out of 244 SDGs indicators 165 indicators (68%) have been mapped with the FYDP II indicators and OII either fully or partially Out of the mapped SDGs indicators, 38% have been mapped with the FYDP II indicators and 30% with the OII Only 5 (2% )of SDGs indicators identified to be Not Applicable to Tanzanian context

Integration of Data Produced by Various Sources to Produce SDGs Indicators 2. SDGs Data Integration of Data Produced by Various Sources to Produce SDGs Indicators 2. SDGs Data Gaps Assessment - Domestication of SDGs. . Distribution of Mapped SDGs Indicators with FYDP II and OII Out of 244 SDGs indicators 37% are fully mapped with the FYDP II or OII and 31% partially mapped Both 30% of unmapped SDGs indicators and 31% of partially mapped indicators calls for additional resources to fill the gaps

Integration of Data Produced by Various Sources to Produce SDGs Indicators 3. Data Innovations Integration of Data Produced by Various Sources to Produce SDGs Indicators 3. Data Innovations in Tanzania towards SDGs implementation § Data innovation is particularly crucial in the current development era to ensure sustainability. Advance in technologies has made it easy and cheap to collect, store, analyze, use and disseminate data § Various initiatives for data innovation take place in Tanzania, particularly on the data sharing and providing access to data both by the government and non-government actors § There has been some innovation in the actual data collection…use of ICT based instruments such as tablets and smart phones for timely, accurate and high quality data to monitor SDGs across various actors

Integration of Data Produced by Various Sources to Produce SDGs Indicators 3. Data Innovations Integration of Data Produced by Various Sources to Produce SDGs Indicators 3. Data Innovations in Tanzania towards SDGs implementation. . Specific initiatives includes; (i) Tanzania Data Lab (D-Lab) project which is guided by four pillars: Ø Engagement, ØCapacity Building, ØResources, and ØPublic/CSOs Dialogue § The D-lab project recognizes a need for; Ø awareness raising and building linkages with the Open Data Community Ø capacity building through training Ø enhancing open data access through open portal to promote and use data generated by CSOs…in collaboration with NBS as per St. Act, 2015 on officiating data generated at CSO level

Integration of Data Produced by Various Sources to Produce SDGs Indicators 3. Data Innovations Integration of Data Produced by Various Sources to Produce SDGs Indicators 3. Data Innovations in Tanzania towards SDGs implementation. . (ii) Tanzania Open Data Initiative This is a government initiative (portal) to enhance access to data in key social sectors of health, education, water and Agriculture; also statistics from the Census and Surveys conducted by the NBS. . More Sectors will be added in phases (iii) Tanzania Socio-economic Database (TSED). The database captures official statistics from MDAs on various socio-economic indicators. The TSED, varying by data sources, allows disaggregation of data at national, district and sub-district level. The database also provides web dashboard for quick analysis on key indicators.

Integration of Data Produced by Various Sources to Produce SDGs Indicators 3. Data Innovations Integration of Data Produced by Various Sources to Produce SDGs Indicators 3. Data Innovations in Tanzania towards SDGs implementation. . (iii) Disability Statistics Database It provides data for population with disabilities including employment, earnings, education and household income. The database which comprise These information include, ILFS; HBS; PHC; NPS and Disability Survey. (iv) Tanzania National Data Archive (TNADA). The Database provides Basic Statistics and micro data from Agricultural Sample Census, Construction Industry sector, Business Register Survey; and Employment and Earnings Surveys and others. (v) Africa Information Highway Provides socioeconomic data at regional level including Tanzania

Integration of Data Produced by Various Sources to Produce SDGs Indicators 3. Data Innovations Integration of Data Produced by Various Sources to Produce SDGs Indicators 3. Data Innovations in Tanzania towards SDGs implementation. . (v) Food and Agricultural Statistics. This is a statistical framework and applied information system for statistical data and metadata on food and agriculture originating from different sources. (vi) Local Government Monitoring Database (LGMD) This is a Government system designed for the Local Government Authorities and Regional Government and the ministry responsible for RALG to monitor pro-poor sectors - health, agriculture, education, water, roads and lands. (vii) Sector/Thematic based MIS These exist in sectors, such as water (e. g. water point mapping), education (e. g. BEST), health, etc.

Integration of Data Produced by Various Sources to Produce SDGs Indicators 4. Challenges Data Integration of Data Produced by Various Sources to Produce SDGs Indicators 4. Challenges Data Gaps: • • • Level of data disaggregation – no one is left behind? ? Frequency of data production Data Quality particularly Administrative Data Unreliable Routine Data Collection Systems Lack of interoperable data management systems within NSS Inadequate mobilisation of financial resources Policy incoherence Big Data concept is still new in Tanzania which needs more capacity for statistician for quality data in monitoring SDGs

Integration of Data Produced by Various Sources to Produce SDGs Indicators 5. The Way Integration of Data Produced by Various Sources to Produce SDGs Indicators 5. The Way Forward Finalize domestication of SDGs including higher level data validation, reconciliation and costing for data production in ADAPT Development of SDGs, AU 2063 and FYDP II visualisation portal and reporting platform. Mobilising political and fiscal commitment for the data for development agenda in Tanzania. Ø Convene high level meeting on data for development in Tanzania for mobilising support From Government Leaders Ø Convene a data ecosystem funders’ meeting to discuss prospect of a multistakeholder fund for the Tanzania Data Development Strategy

Integration of Data Produced by Various Sources to Produce SDGs Indicators 5. The Way Integration of Data Produced by Various Sources to Produce SDGs Indicators 5. The Way Forward. . Convening of thematic meetings to discuss SDG, AU 2063 and FYDP II data gaps and partnerships to address them: - • • Theme 1: Poverty Reduction and Human Development (Goal 1, 2, 3, 4, 6 & 10) Theme 2: Economic growth, Employment, and Competitiveness (Goal 7, 8, & 9) Theme 3: Environmental Sustainability (Goals 12, 13, 14 & 15) Theme 4: Sustainable Cities and Communities (Human Settlement, Housing and Population Infrastructure) (Goal 11) • • Theme 5: Governance Peace & Security (Goals 16) Theme 6: Gender Parity (Goal 5)

Integration of Data Produced by Various Sources to Produce SDGs Indicators 5. The Way Integration of Data Produced by Various Sources to Produce SDGs Indicators 5. The Way Forward. . Finalise TSMP phase I review and development of phase II Strengthening the Private Public Partnership in the context of SDGs including CSOs and FBOs

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