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HomeTHE PROCESS LANDSCAPE Core ProcessesCore Process: Data analysis and usage

Core Process: Data analysis and usage

Rationale

The only legitimate justification for an investment in data production is that the end-product is relevant to the needs of the users, corresponds to their demands in terms of format, frequency and quality and is effectively used to feed their respective works and activities. There are thus different layers of concerns that must be addressed after data have been produced, and in particular:  

  • Their availability: users must know where and how they can get them and when they are made available (see Core process “data production and dissemination”), 
  • Their accessibility by all the users. The access to the data must be easy, straight forward but diversified according to the details requested. If possible this access should not be costly (most of the official statistics are free but accessing them may require specific tools and software. This shouldn’t compromise some fundamental principles of quality statistics such as confidentiality and security, 
  • The fact that they are understood by the users who should be able to draw the maximum benefits from their usage. They should know how the data were built (meta-data) and how they could best be used; support from the producers may help greatly, 
  • Their attractivity: data visualisation may help making data more attractive to the users/audiences and more relevant to new modes of usage of information (the social media in particular).  

Data and their usages are intimately linked in a national data eco-system where interactions should lead to informed decision-making by all actors. It is not enough to create a favourable environment for user/producer dialogue, instead the collaboration must go beyond. The quality of the data eco-system is closely related to the extent of the engagement of the actors and their commitment to work together and to learn from each other. In this framework, different main usages should be given a specific attention: 

  • Promoting and supporting research and analysis. There is a strong interest for the data producers to collaborate with the researchers and academics working on their data as this may constitute a professional and free quality control. However, these users have data needs that are very specific and that may not be generally answered with the standard and regular statistical products. Answering better their needs may require additional investments in the production of the data and/or in the way they are made available (micro-data), 
  • Supporting decision-making, monitoring and evaluation of policies and programmes. Evidence-based policy design and decision-making is a key purpose for statistical/data production. However, there are still multiple obstacles to its practical implementation that are linked to culture and education, on the one hand, and to the functioning of the national systems, on the other hand. The delivery of the data to decision-makers must thus be accompanied by a specific effort in explaining their content and the limitations of their usages and in presentation (attractiveness),
  • Feeding national information and dialogue on development options. Objective of professionally-produced statistics/data that are made available at the same time to all constitute an indispensable pillar of democratic systems and vivid societies. Unlimited and open access to a transparent information may limit misinterpretations of facts and the development of biased positions and debates. The producers of data must crucially build trust and confidence on their professional ability and their independence,
  • Reporting on the SDGs. The follow-up and review of the SDGs are incremental part of the 2030 Agenda. This reporting must be organised at the national level (involving all stakeholders from the public sector as well as non-state actors from the private sectors, the civil society and academia) but also at the regional and international levels ”). There are guidelines and recommendations for (voluntarily) reporting on the SDGs on the global level – but not for reporting structures on the national or regional level. (see Supporting process “International networking and coordination  

Some main obstacles to data usage (official statistics in particular): 

  • Non-availability of data
  • Outdated data 
  • No time series (only one-shot estimates)
  • Inadequate level of disaggregation
  • Difficult/costly accessibility
  • Weak understanding of the content/structure of the data and of the limits of its usage, particularly when there is no accompanying meta data
  • Low attractiveness in the presentation of the data 

Objective/ Outcome

Data produced on the SDGs are used by the various user groups in their respective capacities. 

Contents / Outputs

Statistical products are available in a user friendly and easy to read manner/ publically accessable: 

  • Data bases, tables and graphs, data visualisation (infographics, visual animation, video), maps, profiles on specific sectors or topics, dashboard … 
  • Dedicated web-sites, social media (Facebook, Instagram, Twitter, YouTube …), news media (TV, Radios, newspaper, information web sites), Paper publications (reports, leaflets, yearbooks …) 


Data is used for specific products: 

  • Research and analysis work (sector and cross sector, Cross-cutting issues, studies on specific topics, trends, comparisons …)
  • Policy and programme design (sector, macro and micro)
  • Strategy formulation (Government, non-government, businesses …)
  • Feeding dialogue and debate (institutional framework, civil society and citizens, local environment …)
  • Reporting (nationally and internationally)
  • Impact assessment, monitoring and evaluation 


Data analysis is enhanced by digital means (algorithm/ artificial intelligence)/ and/or used for cross references  

Possible Activities & Good Practices

  1. Perform research and analysis including target-group-specific and cross-sectoral analysis, processing and data disaggregation by key criteria (gender, age, income, education, etc.) – but also other attributes such as urban/rural, in order to highlight interactions 
    Digital potential: use alternative data sources, algorithms and artificial intelligence to generate further proxy indicators and show interconnections (between indicators), for instance through dashboards, etc. 
    Mine data to produce further analytical products such as heat maps  
    Translate data into comprehensible and legible information for different user groups (political decision-makers, citizens, academics) 
    Process, visualise and disseminate data (open data, dashboards, infographics, media and platforms) 
  2. Create basis for establishing a dialogue (at the political level, e.g. parliament) or for informed citizens 
    Create space for participation and accountability 
    Bring data users and producers together 
    Discuss progress/setbacks in SDG achievement 
  3. Use data to generate recommendations, requirements and feedback 
    Formulate action required (level of strategy formulation) 
    Ascertain demand for further data/data coherence, formulate proxy indicators; bear in mind synergies from existing data sets 
  4. Use data for SDG reporting 
    National/sub-national/international level  
    Supply data to the global data system (e.g. UN) for comparable global reporting 
    Shadow reports produced by civil society 

Relevant GIZ activities

  1. Data visualisation
  2. Open data approaches in governance projects
  3. Press and public relations
  4. Dialogue user/producers
  5. Development of strategic capacities/competences in Government
  6. Advice on SDG reporting 

  • Palestinian territories: Local governance reform programme (LGRP) (for internal GIZ use only)
    (PN: 2014.2501.6; May 2015 – March 2019)
    Development and spatial planning and finance and accountability are being improved in local authorities in the Palestinian territories. Measures primarily involve improvements in the fields of remote sensing data and land registration systems.
  • Global: Sustainable Development Solutions Network II (SDSN II) (for internal GIZ use only)
    (PN: 2017.6252.5; January 2018 – December 2020)
    Through networks in the South, the Sustainable Development Solutions Network (SDSN) is making a practical contribution to implementing the 2030 Agenda on cross-cutting topics and issues of global responsibility.
  • Georgia: Legal and judicial reform in the South Caucasus (for internal GIZ use only)
    (PN: 2017.2129.9; February 2018 – November 2020)
    This project supports the alignment of legal systems in the South Caucasus with European standards. The area of activity is supporting the Ministry of Justice with reforms to incorporate 2030 Agenda requirements into regulatory impact assessments.
  • Namibia: SDG Initiative Namibia (for internal GIZ use only)
    (PN: 2016.2237.2; July 2017 – June 2020)
    An enabling environment is being created for national implementation of the 2030 Agenda in Namibia. In Namibia, a development worker is supporting the National Planning Commission with SDG reporting.
  • Mexico: Supporting the Office of the President of Mexico in implementing the 2030 Agenda (for internal GIZ use only)
    (PN: 2016.2234.9; May 2017 – April 2019)
    The Office of the President is being advised on establishing a sustainability architecture, developing a strategy and strengthening the participation of non-governmental actors. Federalism for sustainable development in Mexico is also being strengthened.
  • AU: DATA-CIPATION – Using citizen participation and innovative approaches to data for Africa’s development (for internal GIZ use only)
    (PN: 2017.2158.8; July 2018 – March 2019)
    The AU’s capacities for civic engagement and innovative data management are being improved.
  • Global: Realising human rights in development cooperation (for internal GIZ use only)
    (PN: 2017.2011.9; November 2017 – October 2020)
    BMZ and its implementing organisations are aligning their development policy and development cooperation activities with human rights standards and principles more systematically.
  • Global: Sector programme on governance (for internal GIZ use only)
    (PN: 2017.2112.5; September 2017 – September 2020)
    This project is creating a more enabling environment for German development cooperation to promote governance in line with the 2030 Agenda. In cooperation with the Deutsche Welle Akademie, the media component is being improved in the field of data journalism and data security.
  • Myanmar: Capacity development for SDG implementation (for internal GIZ use only)
    (PN: 2016.2236.4; October 2017 – September 2020)
    A more enabling environment is being created for national implementation of the 2030 Agenda in Myanmar, particularly in the fields of data collection and analysis and evidence-based policy-making.
  • 2030 Agenda Initiative: Kenya: ‘Monitoring and Review of the SDGs’ as an additional field of action for the existing project Strengthening good governance (for internal GIZ use only) (PN: 2016.2105.1; January 2017 – June 2020)
    Involves strengthening cooperation between governmental and non-governmental data communities and better integrating their contributions to monitoring. By actively involving civil society and the private sector, the aim is to use non-official data, innovative digital data sources and new data collection methods for SDG monitoring.
  • Bolivia: Implementing the 2030 Agenda in Bolivia (for internal GIZ use only)
    (PN: 2017.2195.0; December 2018 – May 2021)
    Key actors at the national and sub-national levels are being enabled to use monitoring data on selected water targets of the 2030 Agenda, which were collected in accordance with uniform standards, for policy-making purposes.
  • Partners for Review:
    Global: Strengthening the review process for the 2030 Agenda for Sustainable Development (Partners for Review)
    (PN: 2019.6255.4; July 2016 –March 2022)
    Review processes for the 2030 Agenda are being strengthened for selected countries. Peer-learning among VNR countries of various years: Stakeholder groups from countries that have already undergone a national review process network with stakeholders that have not yet had this experience and establish a process of joint learning and exchange. Within the learning and exchange network, the stakeholders jointly analyse and transfer specific lessons learned from implementation at the national level. Six-monthly network meetings to complement UN events. Year-round online exchange. Review support unit with helpdesk function.

Links with other elements of the process landscape

Linkages with Steering processes: The stronger the signals and interests from the policy and institutional framework, the stronger will be the demand for data and their usages. Working on collaboration users/producers has a cost and this should be acknowledged in budgets and resource mobilisation. Quality concern is strong in all cases of data usages.  

Linkages with the other Core processes: All the user/producer relations call for a close and extended coordination; engaging the users may lead to reviewing data production and dissemination but also involving them strongly into the choice of the indicators. 

Linkages with Supporting processes: Efforts in capacity development are crucial for the users (research and analysis, data visualisation …); the satisfaction of the users’ needs may be increased through the impact digitalisation may have on data production; it is crucial to communicate on the results of data usages and to increase the visibility of the data when they are available. 

Quality standards and references

National actors involved

Producers and users of data (national and local levels):  

Key targeted users:  Decision makers (private and public sectors), media, researchers and academics, businesses, legislative and advisory institutions (Parliament, Economic and social committee …), associations and organisations of the civil society, university and college students, general population, …