Tags: UNDAF Companion Guidances

The new UN Development Assistance Framework (UNDAF) Guidance is complemented by eight companion guidance pieces, which elaborate the following elements:

The guidance pieces provide practical support in these eight areas across a range of contexts, including examples and case studies to illustrate country-level experiences.  They will be regularly updated and complemented with further good practice examples from the field.

Illustration-UNDAF

 

 

 

 

 

 

 

The graphic illustrates where the companion guidance pieces apply and relate to the main stages of the UNDAF cycle. Programming principles is at the centre of the graphic, and the three in the outer grey band—funding to financing, capacity development and communication and advocacy—are cross-cutting and relevant to all three stages of the UNDAF cycle. Four guidance pieces, namely common country assessment, vision 2030, theory of change, and monitoring and evaluation, relate to specific stages of the UNDAF process.

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Silo Fighters Blog

Dominican Republic: 5 Steps to Develop a SDG Data Innovation Lab

BY Mildred Samboy | February 8, 2018

Have you ever wondered how much hazardous waste is generated in your community, city, or country? What is the proportion of women who make their own informed decisions regarding sexual and reproductive health? Or how many people have declared themselves victims of discrimination or harassment in the last 12 months? Imagine if you could have access to this data in a country of more than 10 million inhabitants in the center of the Caribbean. In the Dominican Republic, only 37 percent of the indicators that make up the Sustainable Development Goals (SDGs) have data available for monitoring and 44 percent do not have information or sources for their measurement. This constitutes a challenge for the achievement of the 2030 Agenda for Sustainable Development (2030 Agenda). SDG 12: Responsible Consumption and Production is one of the biggest statistical challenges for the country. As established in the 2016 Rapid Integrated Assessment “there are significant biases in the integration of (SDG 12) indicators into the national development planning and their availability for an adequate monitoring and fulfillment of the fourth axis (sustainable development) of National Development” in the Dominican Republic [1]. All of this considered, how can we measure the SDG 12 indicator related to the generation and proportion of hazardous waste in the country? To figure this out, we joined forces with the National Statistics Office, the Ministry of Economy, Planning and Development and the Ministry of Environment and Natural Resources to come up with a strategy. The result was a data innovation lab built in five steps: Step 1: Select key stakeholders Which institutions are fundamental in the development of an SDG data innovation lab? Multisectoriality is essential to guarantee the richness of this exercise. Two things were paramount for this step: To bring the institutions in charge of statistics and planning (the National Statistics Office and the Ministry of Economy) on board. These institutions are part of other coordination structures, such as the National Commission for Sustainable Development (SDGs Commission), which is the 2030 Agenda coordination and advisory structure (See Decrees 23-16 and 26-17). In this exercise, the UN System in the Dominican Republic worked with the Technical Secretariat of the SDGs Commission to identify a proposal of indicators and criteria for this initiative. To include as many stakeholders as possible in the discussion; from representatives of the public sector (hospitals, General Customs Directorate), to the private sector, to Academia, to environmental organizations, everyone related to the disposal of hazardous waste was invited to participate. This exercise demonstrates the importance of challenging these structures to enforce the fluidity and comprehensiveness of the statistical systems, and their responsibility in the process, guaranteeing an effective relationship that helps bridge existing gaps. Step 2: Select the indicators Which indicators should be selected and prioritized for the development of a Data Innovation Lab? Prioritizing indicators at a national level means choosing them according to the country’s statistical needs. The parameters for this lab were: (A) Lack of source or measurement methodology (B) Indicators within the SDGs identified for the Voluntary National Review (VNR) for the High-Level Political Forum on Sustainable Development (HLPF 2018), in which the Dominican Republic will participate this year. Following these parameters, the Statistics Office presented a proposal with the following indicators: "Proportion of wastewater safely treated"; "Hazardous waste generated per capita and proportion of hazardous waste treated, disaggregated by type of treatment"; and "Number of companies that publish sustainability reports". Of these proposals, hazardous waste was prioritized, taking the Environmental Compliance Reports [2] as a starting point. Step 3: Build participatory and formative spaces How can sectors express and validate the challenges and opportunities for improvement related to the selected indicator? Following this initiative, two main consultation workshops were held with institutions related to the field. The results of the first consultation highlighted the challenges and bottlenecks that make it difficult for the indicator to be measured.  The second workshop aimed to find innovative solutions and improvement opportunities to the problems identified in the first workshop. In both workshops, over 20 young people from academia and civil society institutions volunteered, moderating and summarizing key findings and conclusions at each table discussion. Step 4: Check the possible sources of the indicator How to guarantee results and sustainability in the statistical development of the indicator? In addition to the consultations, a group of specialists were tasked with reviewing the Environmental Compliance Report. This source was important because it is an environmental Administrative Record (forms, reports, files, among others). This review led to a joint exercise by the Statistics Office and the Ministry of Environment to collect and analyze data regarding hazardous waste, together with the private sector, academia and hospitals. It also made it possible to generate technical, statistical and environmental capabilities linked to the indicator, and has created tools to formalize this practice within the institutional framework. Step 5: Systematize, develop and implement What can we do next? The final step is to follow up on the findings and conclusions of these exercises, by developing initiatives that could have a direct impact on the improvement, organization and visualization of the data related to the hazardous waste indicator. One of these initiatives would be a Hackathon to foster the creation of applications and software development for data collection and visualization. Another, which is already underway, is the elaboration of a technical data note (explaining the indicator metadata) by the Statistics Office. This note will be validated by several sectors that will have the opportunity to rethink together the statistical development structures of the indicator. At last, this team is also working with the culmination of the construction of the database of the Environmental Compliance Reports and its respective baseline. What we learned This experience shows that there is a link between the statistical development capacity of our countries and their needs, challenges, accomplishments and opportunities, which must consider the political and social dimensions. Implementing the 2030 Agenda in the field brought institutions from different sectors together to break existing barriers. While working together was as a challenge, it was also an opportunity to improve practices and actions. Strengthening the national statistical system will only be possible if the key sectors involved have the tools, the capacities and the will.     [1] The Rapid Integrated Assessment (RIA) Tool aims to support countries in mainstreaming the Sustainable Development Goals (SDG) into national and subnational planning, by helping assess their readiness for SDG implementation. Click here to access the Dominican Republic’s 2016 RIA elaborated by UNDP and MEPyD [2] The Environmental Compliance Report (ICA, its Spanish acronym) “is a technical report that explains the degree and quality of compliance of a facility, project, program or other activity by its operator or entity (company, NGO, government) with regards to environmental laws and regulations governing a certain place, resulting in a process of auto management.” (Dominican Republic Encyclopedic Dictionary of the Environment)

Silo Fighters Blog

Fusing datasets to track the impact of disasters in Indonesia and beyond… VAMPIRE is on it!

BY Anthea Webb, Derval Usher | January 25, 2018

When El Niño-induced drought placed huge pressure on communities across Southeast Asia, the UN in Indonesia quickly established an inter-agency focus group to monitor the impact. The World Food Programme, UN Global Pulse Lab Jakarta and the Food and Agriculture Organisation responded to the need for faster analysis with an integrated data tool called VAMPIRE! (The Vulnerability Analysis Monitoring Platform for Impact of Regional Events).  How’s that for an acronym! What VAMPIRE does: blend and visualize in near real time As climate affects food production and prices, it is a decisive factor in the health and welfare of millions of communities. The 2015 El Niño drought caused food prices to spike in Indonesia, stretching the budgets of poor families who already spend more than half their incomes on food. The situation was even more serious given 37 percent of Indonesian children are chronically malnourished. The project team had to move quickly to develop a data tool for the Government of Indonesia and partner agencies to decide where and how to allocate resources. The first iteration of VAMPIRE applied data science skills to automate the analysis of the extent of the drought and populations at risk. The tool is a multi-tier system that fuses several datasets. First, it visualizes the national socio-economic survey and WFP’s household food security surveys. This data provides information on the percentage and distribution of poor, agriculture-dependant populations, as well as food insecure communities. Second, it analyzes data on rainfall anomalies and the Indonesian Vegetation Health Index. Rainfall anomaly is a measure of the amount of rainfall in a period compared to the long-term average for that time of year, while the vegetation index is a proxy for drought. Based on the measure of economic vulnerability and exposure to drought, the tool identifies priority areas where people may require assistance. Government Uptake Collecting data on rainfall anomalies and food security is not a new or unique activity for governments. However, the platform adds value by dramatically reducing the time required to bring this information together and visualize it in high-resolution and in near real-time. VAMPIRE has been installed into the situation room of the Office of the President (Kantor Staf Presiden) of the Republic of Indonesia, its sustainable home. The Government of Indonesia has used the tool to measure drought impact and identify fire risks. It has developed it further to estimate the impact of past government programmes as part of their regular monitoring and oversight. These are encouraging user-innovations by the Government of Indonesia that we are trying to incorporate as the tool scales to other countries (more on this below). Under the Hood Building upon these initial successes, the tool has been upgraded to include new, more detailed analysis on drought. More granular estimation of affected areas has improved the tool’s ability to identify and prioritize risk. Additional indicators on meteorological drought, agricultural drought, population density and dependence on agriculture are improving the methodology. In addition to drought, we have developed flood impact analysis capabilities into the most recent iteration of the tool. We can now estimate floods six days in advance, including the risk to crops and populations. For both flood and drought, we now include extensive disaster history information and improved UX, enabling users to explore the insights at different administrative levels and generate reports on this basis. Sri Lanka, Papua New Guinea and Beyond Based on demand for the data tool from the Government of Sri Lanka, we contextualised the system to the country and embedded it within the Ministry of Disaster Management. The improvements made to the tool while shaping it to the context of Sri Lanka have informed its development elsewhere. This year we are in talks with the Government and UN Country Team in Papua New Guinea with a view to establishing a version of the system there, and we are in the process of open sourcing the tool to enable uptake elsewhere. We are also working to improve the notification and alert system for different users, as well as conducting further tests of the accuracy of alert thresholds, fine tuning them to sub-national needs and realities. We owe huge thanks to DOCO for its support of this project! And we hope that the development of the tool will take another leap forward now that VAMPIRE has been recognized as the winner of the 2017 WFP Innovation Challenge. We are delighted to have had the opportunity to develop a data tool in true partnership leveraging the expertise of each of our teams to produce an information system which is being used for policy making. We are always on the lookout for opportunities to scale the tool, so let us know if your UN Country Team could benefit from such a system and we will work out how we can best meet your needs. Photo: Neil Palmer (CIAT)

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