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Purpose

“The challenges and commitments contained in these major conferences and summits are interrelated and call for integrated solutions. To address them effectively, a new approach is needed. Sustainable development recognizes that eradicating poverty in all its forms and dimensions, combatting inequality within and among countries, preserving the planet, creating sustained, inclusive and sustainable economic growth and fostering social inclusion are linked to each other and are interdependent.”

The 2030 Agenda for Sustainable Development (UN 2015)

The purpose of this section is to heed The 2030 Agenda’s call ‘for integrated solutions’ by featuring guidance and tools that connect and break down traditional sector silos and create horizontal policy coherence, integration and partnerships. This is relevant to all levels of governance: national, sub-national and local.

Guidance

There is for the most part, a shared understanding of the inherent interconnectedness and complexity of sustainable development. But what has remained mostly elusive over the years is how to deal with this reality. How do we undertake strategy-making, planning and policy-making that is based in systems thinking and delivers an integrated view?

Fortunately, some very useful approaches and tools have been developed over the past decades since the 1992 Earth Summit. But they require considerable effort and strong leadership to apply, and for that reason, their application in development planning is still somewhat limited. The 2030 Agenda is telling us that time is of the essence on most critical issues (see quotation above) – it is asking us to urgently roll up our sleeves, so-to-speak, and to use ‘integrated solutions’ with ‘new approaches.’

The guidance provided in this section for creating horizontal policy coherence, integration and partnerships is three-fold:

  1. Integrated policy analysis: to ensure that proposed policies, programmes and targets are supportive of nationally-adapted SDGs;
  2. Coordinated institutional mechanisms: to create formal partnerships across sectoral line ministries and agencies;
  3. Integrated modelling: to help clarify and articulate the interconnected system of goals and targets and to analyse and inform key policies, programs and projects for their impact on nationally-adapted SDGs.  

Integrated Policy Analysis

Integrated policy analysis is an approach that UNCTs could share with Member States as a means to screen policy and programme proposals for their potential to either benefit or negatively impact on specific national issues of concern. The approach then ideally asks for policy revisions before they can be submitted to cabinet for approval.

Two countries in particular provide good examples and guidance for integrated policy analysis: Bhutan and Switzerland. Consider first Bhutan’s Gross National Happiness Policy Screening Tool, featured in the Innovative Case Example below.

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Innovative Case Example: Application of Bhutan’s GNH Policy Screening Tool

Gross National Happiness (GNH) comprises four pillars and nine domains and is Bhutan’s “holistic and sustainable approach to development.” The GNH Policy Screening Tool is used by the government’s Gross National Happiness Commission to “assess/review all draft policies, programmes and projects through a GNH lens” and furthermore, “[w]hilst it is not the determining factor for ultimately approving/endorsing policy, it highlights specific recommendations and feedback to review the policy within the scope of the 9 domains of GNH.”

 “An intriguing example of the screening tool in action was the proposal for Bhutan’s accession to the WTO. Initially 19 of 24 GNHCS (Gross National Happiness Commission Secretariat) officers voted in favour of joining. After putting the policy through the Screening Tool, 19 officers voted against on the basis that the policy was not GNH favourable. To date Bhutan has not joined the WTO.”

Source: GNH Centre (2015b). Additional information in GNH Commission (2015) and UNOSD (2014)

Switzerland has a long history of applying integrated policy analysis methods in the form of ‘sustainability assessment (SA). The Federal Office for Spatial Development (ARE) provides guidelines and tools for SA which are “intended as instructions on how to evaluate Federal Government initiatives (laws, programmes, strategies, concepts and projects) to find out how they comply with the principles of sustainable development.” Accompanying the online SA guidelines is an MS Excel-based tool to help government officers to conduct assessments.

In addition, the Swiss ARE collaborated with representatives from 30 Swiss cantons and local municipalities to prepare guidelines for “assessing project sustainability at cantonal and municipal level.” The guidelines are available online and describe the benefits of assessment, how the sustainability assessment process can be initiated and provides assistance for choosing the right assessment tool.

Another integrated analysis tool is the Framework for Cooperation for the system-wide application of Human Security (Framework for Cooperation) developed by the Inter-Agency Working Group on Human Security. This approach offers practical guidance on how to harness the potential of the human security approach in areas including implementation of The 2030 Agenda. The human security approach is people-centered, context-specific, comprehensive and prevention-oriented. The approach advances both top-down protection and bottom-up empowerment solutions. The Framework for Cooperation offers an analytical framework that advances comprehensive and integrated solutions and breaks through the conventional single-agency style of planning and programme implementation, and is a key tool for the United Nations system in supporting The 2030 Agenda’s call for integrated solutions.

Coordinated Institutional Mechanisms

Formalized institutional mechanisms in the form of inter-agency coordinating bodies are another key approach that UNCTs could discuss with Member States for purposes of creating horizontal policy coherence, integration and partnerships. With the involvement of the highest level offices in government (i.e., Prime Ministers and Presidents offices, Cabinet Offices), these coordinating institutions can serve to connect and break down silos across government.

Good practice examples in Bhutan, Finland and Colombia provide relevant guidance for this aspect. Bhutan’s Gross National Happiness (GNH) Commission is an example of an inter-agency coordinating body designed to foster horizontal coherence, integration and partnerships across government sectors. The GNH Commission is “the Government of Bhutan’s Planning Commission and is charged with ensuring that GNH is mainstreamed into government planning, policy making and implementation.  The GNH Commission coordinates the country’s Five Year Plan process and is composed of all ministry secretaries with planning officers that provide links between individual ministries and the GNH Commission (Bertelsmann Stiftung 2013b).

The inter-ministerial secretariat of the Finnish National Commission for Sustainable Development (FNCSD) is another example of an inter-agency coordinating body that facilitates horizontal policy coherence, integration and partnerships. Steered by the Ministry of the Environment, the secretariat “comprises of about 20 members from different ministries, each taking the lead in preparing themes within their area of expertise (ESDN 2015).” The secretariat facilitated horizontal coordination over the years, including striking a sub-committee for integrating multiple strategies from across government and other stakeholder groups (Bertelsmann Stiftung 2013c).

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Innovative Case Example: Colombia’s Horizontal Institutions

As an original champion of the SDGs in the run-up to Rio+20, Colombia has enjoyed early political commitment to the 2030 Agenda for Sustainable Development. This commitment gained momentum through involvement as a member of the Open Working Group and its SDGs consultations, and through its role in the Inter-Agency Expert Group on SDG indicators. This inherent government commitment has enabled Colombia to make early progress on mainstreaming the 2030 Agenda.

Among Colombia’s new institutions for mainstreaming and implementing the 2030 Agenda are its High-level Inter-Institutional Commission for SDGs with a technical secretariat, technical committee and transverse and inter-sectorial working groups.

Source: UNDG and UNDP (2015)

Integrated Modelling of the System of Interconnected Goals and Targets

The 2030 Agenda states that the SDGs are “integrated and indivisible and balance the three dimensions of sustainable development: the economic, social and environmental.” This statement highlights the imperative of an integrated approach to contextualizing issues and planning, implementing and monitoring their solutions.

While the basic groundwork for adapting the SDGs to national context can be set through deliberative processes such as described above, adapting of specific targets requires more detailed analysis and deliberation. UNCTs could discuss with Member States approaches for: (i) ‘mapping’ the system of interconnections among a nation’s goals and targets; and (ii) support the mapping with integrated models to better understand and inform the setting of potential targets.

Mapping Interconnections of goals and targets: Social network analysis (SNA) is a strategy for investigating social structures through the use of network and graph theories (Wikipedia 2015, Otte and Ronald 2002). It has been used by the UNDESA to map the interconnectedness among the 17 SDGs and its 169 targets and can provide important insights for policy coherence and integration when applied in the national context (see innovative case example below).

Although the analysis was done at the global level, UNCTs could share such approaches with Member States to undertake similar analysis at the national level also (UNDESA 2015b).

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Innovative Case Example: UNDESA Analysis of the SDGs as a Network of Targets

Using network analysis techniques, UNDESA revealed that the SDGs and targets can be seen as a network, in which links among goals exist through targets that refer to multiple goals.

“Because of these connections, the structure of the set of SDGs has implications for policy integration and coherence across areas. For many of the thematic areas covered by the SDGs, targets relating to those areas are found not only under their namesake goal (when it exists), but across a range of other goals as well. In designing and monitoring their work, agencies concerned with a specific goal (e.g. education, health, economic growth) will have to take into account targets that refer to other goals, which, due to the normative clout of the SDGs for development work coming forward, may provide stronger incentives than in the past for cross-sector, integrated work. Similarly, for institutions concerned with monitoring and evaluation of progress under the goals, it will be necessary to look at multiple goals – indeed, all those which include targets referring to one institution’s area of interest. This may enable greater integration across goals.”

Note: The sixteen SDGs are represented as broader circles of differing colors, while targets are figured by smaller circles and have the color of the goal under which they figure.

Source: UNDESA (2015b)

Use of Integrated Modelling Tools: Government planning agencies can use integrated modelling tools to gain a systems-wide perspective on sustainable development issues to inform the setting or achievable and ambitious targets for plans and policies.

UNDESA’s 2015 workshop on Integrated Approaches to Sustainable Development (IASD) hosted by the Division for Sustainable Development feature many such tools in its deliberations (Crawford 2015). For example, the Millennium Institute’s Threshold 21 model has been applied by governments in the national planning process to generate “scenarios describing the future consequences of the proposed strategies (MI 2015).” In Mali the T21 model was applied to support the country’s poverty reduction strategy and analyze the coherence between the strategy and the MDGs (MI 2015). In Kenya the model was used to analyze the risks of climate change on multiple economic sectors (see the Innovative Case Example below). A companion model has recently been developed by the Millennium Institute, iSDG, which “simulates the fundamental trends for SDGs until 2030 under a business-as-usual scenario, and supports the analysis of relevant alternative scenarios (MI 2015).”

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Innovative Case Example: Integrated Modelling to Support National Development Planning in Kenya

The Millennium Institute’s Threshold 21 (T21) model was applied by the Kenyan Government to “develop more coherent adaptation policies that encourage sustainable development, poverty eradication, and increased wellbeing of vulnerable groups within the context of Kenya’s Vision 2030 program (MI 2015).” In particular, the T21-Kenya model was customized to “enable simulations of policies to attain selected MDGs and specific aspects of Kenya Vision 2030 particularly on the economic and social pillars (MI 2011).”

From: UNDP (2012)

Customization of the T21 model for Kenya used a multi-stakeholder participatory process involving participants from diverse sectors. Development of the model was also accompanied by in-depth training of the participants in System Dynamics modelling and model development. The T21-Kenya model was used by Kenya’s Macro Planning Directorate, Ministry of State for Planning, National Development and Vision 2030, where a core team of 12 modellers were trained to maintain T21-Kenya and use it for policy scenario analysis, with a larger group of 25 government official were also trained in the more general use of System Dynamics and T21. [Source: MI (2011)]

Economy-wide models are another type of integrated modelling approach that governments can use (Sánchez 2015). Examples include the World Bank’s MAMS model (Maquette for MDG Simulations) which is a “dynamic Computable General Equilibrium (CGE) model that has been extended to cover the generation of outcomes in terms of growth, MDGs, and the educational make-up of the labor force, as well as the interaction of these outcomes with other aspects of economic performance (World Bank 2015).”

Additionally, UNDESA has used integrated macro-micro modeling with the objective to “strengthen the capacity of policymakers to formulate countercyclical policies that may help mitigate the adverse impacts of the global economic crisis and other external shocks and put countries back on track to timely achieve the MDGs by 2015 (UNDESA 2013).”

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Innovative Case Example: Decision Theatres – The Future of Evidence-based Policy-making

There is a growing trend in the construction of ‘Decision Theaters’ for bringing together the benefits of integrated modelling with multi-stakeholder deliberation in a visually-immersive environment. Decision Theaters have been referred to as the future of evidence-based policy-making (Cornforth et al. 2014), with facilities operating in the United States (ASU 2015), Canada (UBC 2015), and China (HUST 2015).

Decision Theater at Arizona State University

Source: ASU (2015)

Arizona State University was a pioneer in the development of Decision Theaters. With two facilities situated in Arizona and Washington, D.C., ASU provides “meeting rooms with large-format displays and on-site computer systems, tools and personnel that can provide specialized geographic information systems (GIS), systems modeling, business intelligence, 3D spatial modeling and simulation (ASU 2015).” The ASU Decision Theater has assisted with a range of policy issues in the U.S. including pandemic preparedness, energy grid planning and sustainable water use.

Toolkit

UNITAR National Briefing Package

Integrated Policy Analysis Tools

  • Bhutan GNH Policy Screening Tool (GNH Centre 2015b).
  • Swiss Sustainability Assessment at Federal and Canton level (ARE 2015).
  • Framework for Cooperation for the system-wide application of Human Security (UNHSU 2015).

Institutional Coordinating Mechanisms

Network Mapping Tools

  • Pajek (Slovene word for ‘spider’) is a windows-based program for the analysis of very large networks. This program was used by UNDESA in its social network analysis of the SDGs and targets. (Mrvar and Batagelj 2015).
  • Sentinal Visualizer is a program for “advanced link analysis, data visualization, geospatial mapping, and social network analysis (FMS-ASG 2015).” It has been used by the UN Office for Sustainable Development to map the connections among knowledge networks.
  • A Reader’s Guide to Social Network Analysis (SNA) Softwareprovides a website link to a comprehensive listing of network mapping software (Huisman and van Duijn 2011).

Integrated Models

Some examples of integrated models include:

  • Threshold 21 (T21) and iSDG (MI 2015)
  • CLEWs – Climate, Land-use, Energy and Water Strategies (Howells et al. 2013)
  • MAMS (World Bank 2015)
  • Integrated micro-macro modeling (UNDESA 2013)

Employment and labour market modelling

  • ILO Dynamic Social Accounting Matrix (ILO 2011)
  • Computable General Equilibrium modelling of regional integration and labour market impacts (ADB and ILO 2014)

Gender Mainstreaming Guidance

  • Gender Mainstreaming in Development Programming – A Guidance Note (UN Women 2014)

Decision Theatres

  • Arizona State University Decision Theater in the U.S. (ASU 2015)
  • Huazhong University of Science and Technology in China (HUST 2015)
  • Decision Theatre at the Center for Interactive Research on Sustainability, University of British Columbia, Canada (UBC 2015)

References and Links

ADB and ILO (2014). ASEAN Community 2015: Managing integration for better jobs and shared prosperity. Asian Development Bank and the International Labour Organization.

ARE (2015a). Assessing sustainability within the federal government. The Swiss Federal Office for Spatial Development (ARE).

ARE (2015b). Assessing canton and municipal projects. The Swiss Federal Office for Spatial Development (ARE). Available at: 

ASU Decision Theater Network (2015). Arizona State University Decision Theatre.

Bertelsmann Stiftung (2013b). Winning Strategies for a Sustainable Future. Page 65. Verlag Bertelsmann Stiftung: Gutersloh. 

Bertelsmann Stiftung (2013c). Winning Strategies for a Sustainable Future. Page 109. Verlag Bertelsmann Stiftung: Gutersloh.

Crawford, J. (2015). Sustainable Development Planning and Strategy Formulation: An Integrated Systems Approach. Presentation delivered at the UNDESA Workshop on Integrated Approaches to Sustainable Development. 

Dalal-Clayton, B. and B. Sadler (2014). Sustainability Appraisal: A Sourcebook and Reference Guide to International Experience. Routledge: New York. pp 370.

ESDN (2012). Switzerland Country Profile. European Sustainable Development Network (ESDN).

ESDN (2015). Finland Country Profile. European Sustainable Development Network (ESDN).

FMS-ASG (2015). Sentinel Visualizer: Advanced Link Analysis, Data Visualization, Geospatial Mapping, and Social Network Analysis. FMS Advanced Systems Group.

GNH Centre (2015a). Bhutan’s Gross National Happiness (GNH) approach. Bhutan’s GNH Centre.

GNH Centre (2015b). The Gross National Happiness Policy Screening Tool. The GNH Centre. 

GNH Centre 2015c). The Gross National Happiness (GNH) Commission

GNH Commission (2015). Bhutan’s Gross National Happiness Commission

Howells, et al. (2013). Integrated analysis of climate change, land-use, energy and water strategies. Nature Climate Change 3, 621–626.

Huisman, Mark and van Duijn, Marijtje A.J. (2011). A reader’s guide to SNA software. In J. Scott and P.J. Carrington (Eds.) The SAGE Handbook of Social Network Analysis (pp. 578-600). London: SAGE. Listing of software for social network analysis supporting the chapter.

HUST (2015). Decision Theater Setup at Huazhong University of Science and Technology.

ILO (2011). Dynamic Social Accounting Matrix (DySAM): Concept, Methodology and Simulation Outcomes. The case of Indonesia and Mozambique. International Labour Organization.

MI (2011). Strengthening Institutional Capacity for Integrated Climate Change Adaptation & Comprehensive National Development Planning in Kenya – Final Report. Millennium Institute. 

MI (2015). Historical Development and Applications of the T21 Model. Millennium Institute.

Mrvar, A. and V. Batagelj (2015). Pajek, version 3 and 4: Programs for Analysis and Visualization of Very Large Networks – Reference Manual

Otte, E and R. Ronald (2002). “Social network analysis: a powerful strategy, also for the information sciences”. Journal of Information Science 28: 441–453.

Sánchez, M. (2015).  Modelling tools to support evidence-based policy decision making for sustainable development. Presentation delivered at the Workshop on Integrated Approaches to Sustainable Development, UN Department of Economic and Social Affairs, Division for Sustainable Development, New York, May 27-29. 

UBC (2015). Decision Theatre at the Center for Interactive Research on Sustainability, University of British Columbia, Vancouver, Canada.

UNDESA (2013). Strengthening Macroeconomic and Social Policy Coherence through Integrated Macro-Micro Modelling (2011-2013). 

UNDESA-DSD (2015b). Towards integration at last? The sustainable development goals as a network of targets. UN Department of Economic and Social Affairs.  DESA Working Paper No. 141. 

UNDG and UNDP (2015). Retreat report on early Country Experiences in Mainstreaming, Acceleration and Policy Support (MAPS) for the 2030 Agenda. United Nations Development Program., New York, 1-3 December 2015. Available at: 

UNDP (2012). Kenya Threshold 21 Dynamic Model Report. United Nations Development Program – Africa Adaptation Program

UNHSU (2015). Framework for Cooperation for the system-wide application of Human Security. Prepared by the United Nations Human Security Unit.

UNITAR (2015b). Module 3: Working Together on the Sustainable Development Goals. In Post 2015 National Briefing Package[UNCTs can log in as guest and use password “unitar”].

UNOSD (2014). Report of the 2014 Sustainable Development Transition Forum. United Nations Office for Sustainable Development. pp 13.

UNOSD (2014).  Incheon Communique – 2014 Sustainable Development Transition Forum. 9-11 April, Incheon, World Bank (2015). Maquette for MDG Simulations – MAMS. World Bank. 

UN Women (2014). Gender Mainstreaming in Development Programming – A Guidance Note. 

Wikipedia (2015). Social Network Analysis.

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Silo Fighters Blog

Innovation scaling: It’s not replication. It’s seeing in 3D

BY Gina Lucarelli | September 12, 2018

My brother is a mathematician and on family vacations, he talks about data in multi-dimensions. (Commence eyes-glazing over). But as the family genius, he’s probably on to something. Lately, in my own world where I try to scale innovation in the UN to advance sustainable development, I am also thinking in 3D, or, if properly caffeinated,  multi-dimensionally. As new methods, instruments, actors, mutants and data are starting to transform how the UN advances sustainable development, the engaged manager asks: when and how will this scale?  To scale, we need to know what we are aiming for.  This blog explores the idea that innovation scaling is more about connecting experiments than the pursuit of homogeneous replications. Moving on from industrial models of scaling innovation In the social sector, the scaling question makes us nervous because the image of scaling is often a one dimensional, industrial one: let’s replicate the use of this technology, tool or method in a different place and that means we’ve scaled. This gives us social development people pause not only because we can’t ever fully replicate [anything] across multiple moving  elements across economic, social and culture. Even if we could replicate, it would dooms us to measuring scaling by counting the repeated application of one innovation in many places.   Thankfully, people like Gord Tulloch have given us a thoughtful scaling series that questions the idea that scaling social innovation is about replicating single big ideas many times over. [Hint: he says scaling innovation in the public sector is less about copy-pasting big ideas and more about legitimizing and cultivating many “small” solutions and focusing on transforming cultures.]  Apolitical’s spotlight series on scaling social impact includes a related insightful conclusion: when looking at Bangladesh’s Graduation Approach as one of the few proven ways out of poverty, they suggest that while the personalized solutions work best, they might be replicable, but too bespoke to scale. So if scaling ≠ only replication, how do we strategize for scale? I’ve got a proposal:  what if we frame the innovation scaling question more about doing deep than broad? The scaling question becomes: How will we move from distinct prototypes managed by different teams at the frontier of our work to a coherent, connected use of emergent  experiments in programme operations? Scaling also means moving from fringe to core Scaling innovation in a large organization like the UN has a glorious serendipity to it. Did you hear that we are looking into impact bonds in Armenia? What about the food security predictor in Indonesia? Nice collective intelligence approach in Lesotho. Blockchain is being used for cash transfers in Pakistan and Jordan. Check out the foresight in Mauritius. UNICEF is using Machine learning to track rights enshrined in constitutions. UNHCR is using it to predict migration in Somalia. UNDP is testing out social impact bonds for road safety in Montenegro. These organic innovations are beautiful and varied and keep us learning, but we as a UN system are not yet scaling in 3D. These days, I’ve been talking to people (my brother’s eyes glaze over at this point) about how to see various methods of innovations not as distinct categories of experiments, but rather as connected elements of an emergent way of doing development. Towards a connected kind of 3D.  Yes innovation is more of an evolving set of disruptions than a fixed taxonomy of new methods, but if we narrow our scope for a moment to the subset of innovations which have passed the proof of concept stage, can we start thinking seriously about how they connect? [As an important side note, thinking in terms of taxonomies of innovations is not a panacea. Check out @gquagiotto’s slides for a more thorough story on how classification is trouble for public sector innovation because it means we limit our vision and don’t see unexpected futures where they are already among us.] Projectizing innovation without keeping an eye on the links among the new stuff won’t get us far, and might even be counter-productive.  Instead, what would it be like if innovations were deployed in an integrated way? A bit like Armenia’s SDG innovation lab where behavioral insights, innovative finance, crowd-sourced solutions and predictive analytics [among others] are seen as a package deal.  I am looking for collaborators to learn more about how are all these methods and tools related. Do they help or hinder each other? Are there lessons that can be learned from one area and applied to others? Should some new tech and methods not be combined with others? 9 elements of next practices in development work A few of us UN experimenters came together in Beirut in July to pool what we know on this.  We had a pretty awesome team of mentors and UN innovators from 22 countries. We framed our reflections around the 9 elements of innovation which I see as approaching critical mass in the field. This is by no means exhaustive, but it’s a start to moving these methods from fringe tests led by various teams to core, connected operations. Here are the “nine elements of next practice UN” we are working with: Tapping into ethnography, citizen science and amped up participation for collective intelligence to increase the accuracy, creativity, responsiveness and accountability of investments for sustainable development. Using art, data, technology, science fiction and participatory foresight methods to overcome short-termism and make sustainable futures tangible. Complementing household survey methods with real time data and predictive analytics to see emerging risks and opportunities and design programmes and policies based on preparedness and prevention. Building on the utility of “superman dashboards”  for decision makers to helping real people use their own data for empowerment, entrepreneurship and accountability. Leveraging finance beyond ODA and public budgets by finding ways to attract private capital to sustainable development. Evolving the way we do things and even what services we offer by managing operations through new technologies Applying psychology and neuroscience for behavioral insights to question assumptions, design better campaigns and programmes and to generate evidence of impact when it comes to people’s behavior. Carving out space for science and technology partnerships within the UN’s sustainable development work Improving how we support our national partners in managing privacy and ethical risks Moving from “that’s cool” to “aha it’s all connected” We need to start thinking of these 9 elements as connected. It might be that they reinforce each other - whereby focusing on data empowerment gives meaning, context and legitimacy to the use of big data to understand behaviors and online activity. Or that they undermine each other - in the way that citizen science can undermine innovative finance pay-outs, or behavioral insights are helping companies get around privacy regulations. Looking for the practical connections, here’s what we’ve got so far: Collective intelligence methods that listen to people organically can help determine whether your behavioral campaigns are resonating.  Because people’s intell is often more granular than statistics, they could also be used to test whether new forms of finance are making an impact on health, education and other development issues. Small scale and/or internal experiments in the UN to manage operations with new technology help us know what the next generation privacy and ethics risks are. Experiments in gray zones can then inform future-oriented regulatory frameworks. Keeping a focus on helping people use data for empowerment is a good northstar when using new data and predictive analytics to ensure that cultivating realtime sources of data isn’t deepening the digital or data privacy divide. Using foresight methods or predictive analytics can point to signals of where to invest with innovative finance instruments [Follow Ramya from IFRC innovations for more on this. Hence some early connections form a budding conspiracy theory! If you are thinking multi-dimensionally too, or using a few of these methods and see where this line of thinking can be improved, help me draw more lines on the innovation conspiracy board! [Or tell me why this is the wrong tree to be barking towards… That’s always helpful too.]   We’re working on a playbook to codify what we know so far in terms of principles and methods for each of these 9 elements. Stay tuned for that... and please do get in touch to throw your own knowledge in!

Silo Fighters Blog

Promise to data: What the SDGs mean for persons with disability in China

BY Marielza Oliveira, Elin Bergman | August 29, 2018

China has strong and capable statistical systems, no surprises there. After all, China is known for its ambitious Five-Year Plans, which have shifted focus from economic growth to policy planning, environmental protection, and social programmes for its population of 1.4 billion. What's different and unique about its 13th Five-Year Plan is that it's very much aligned with the 2030 Agenda for Sustainable Development. Even so, China faces a daunting challenge to implement Agenda 2030. For starters, it only has official data for less than 30 percent of the Sustainable Development Goals (SDGs) indicators, and much less when considering data that covers vulnerable groups, such as persons with disabilities. With more than 85 million, China has the largest population with disabilities in the world. The good news is that China keeps a record of people with disability, so the official data sources are up-to-date. To support the Chinese government’s efforts to improve monitoring of the SDGs addressing people with disabilities, we at UNFPA, UNESCO, UNRCO, UN Women and WHO came together to test innovative approaches to collect focused and disaggregated data. Starting in Qinghai We selected the Qinghai Province in Northwest China as the pilot location to test new ways of collecting data. In Qinghai, the estimated number of persons with disability is five percent of the total population, of which about 70 percent live in rural areas. There are about 150,000 people registered in Qinghai Disabled Persons’ Federation, the local chapter of China Disabled Persons’ Federation. Therefore, it was important for us to look at their administrative data, which are key for crosslinking data from various sectors, including public services data. To demonstrate how data collection in underdeveloped regions can be operationalized in a smart way, we collected, analyzed and crosslinked all the administrative data of people with a disability ID with the following big data sources: Data from the national survey of basic services and needs for people with disabilities which is developed and updated by China Disabled Persons’ Federation, the National Bureau of Statistics and local Disabled Persons’ Federations; Data from the public services and various sectors including health, education, employment, social security, poverty alleviation and community services. This type of data is gathered from crosslinking disability ID data with public services data. Data from internet-based platforms. It's possible to use big data to integrate and crosslink all data from the disability ID system, administrative data of disability services from China Disabled Persons’ Federation and the administrative data of public services. By expanding the existing official data with information from other sources, China has the potential to not only monitor the additional SDG indicators, but it can also compile additional disaggregated views of SDG progress to monitor specific groups and locations in need of support while strengthening “real-time” monitoring and analytics. During this process, we engaged the vulnerable groups in the analysis and interpretation of data. For us, knowing what people living with disabilities think and need is key. We carefully examined their views to highlight the SDGs indicators that could directly benefit their well-being. The hindrances of data collection We experienced a few setbacks throughout the process, but, we adopted coping mechanisms to address the issue of data collection and analysis: Quality control of data. The disability data available from different sectors uses very different standards and follows different collection approaches. Moving forward, we propose to check and purify the data using standard disability datasets and a data crosslink approach. We also optimized the timeliness and the mechanisms to update the data. Sharing data among sectors. The key index of disability and people with disabilities was determined using the disability ID. The data across sectors was crosslinked with key index such as disability ID and others. What we discovered The administrative data platform of people with disability was recently updated with the results from the annual survey of unmet needs and services for people with disabilities nationwide. This platform provides timely data for monitoring SDGs that address people with disabilities. Other sectors have developed big data platforms using citizens’ ID. To continue enhancing the administrative data records, it's important to collaborate with other stakeholders, such as health care and educational departments to extend the existing data sources. Household surveys can also be used to fill in the gaps of official disability statistics. We shared our discoveries with an expert panel, which included representatives from the Chinese government, the National Bureau of Statistics, China Disabled Persons' Federation and its Qinghai branch, Qinghai Department of Commerce, Institute of Rehabilitation Information/WHO Family International Classifications Collaborating Center China, China Disability Data Research Institute, Soochow University, Nanjing Special Education Teachers College, UN agencies, as well as Chinese IT giants What's next The methodology implemented in Qinghai province can easily be extended to other vulnerable groups since they also face similar challenges. Stakeholders can also adopt similar tactics to develop specific SDG indicators, data collection and analysis to evaluate their progress. As for next steps, the UN country team will continue to research protocols and methods to monitor disability-inclusive SDGs. We will also develop a knowledge platform in Chinese to promote capacity building for the implementation of Agenda 2030 and conduct an international comparative study of technical approaches of data collection and analysis. Data and internet-based surveys will also be developed to learn more about the needs of people with disabilities and improve services for them, while at the same time using those statistics to make sure that we leave no one behind. What methods are you disaggregate the SDGs to ensure data for action with people living with disabilities? If you have some tips, do tell! Photography: Jonathan Kos-Read. License by Creative Commons