@techreport{chapela_trillo_partnering_2034, title = {Partnering with communities to co-design humanitarian health strategies: {A} {SeeChange} {CommunityFirst} {Framework} for implementation in {MSF} projects}, url = {https://www.seechangeinitiative.org/}, abstract = {The CommunityFirst Framework is intended to be implemented by field teams at MSF. The theoretical aspects and evidence presented on the importance of community engagement are intended for all MSF staff seeking to learn more about why and how to shift the way we work with communities as humanitarians. We believe this guideline, and other tools like it (including OCA’s Person-Centred Approach Guidance07, and MSF Vienna Evaluation Unit’s Guidance for Involving Communities08), to be an important contribution to the growing movement of communities and humanitarian actors who are pushing for changes in the humanitarian system that translate to dignity, health, justice, equity and self-determination for communities around the world. Specifically, the CommunityFirst Framework is intended to guide MSF teams to co-design health strategies with communities, throughout all stages of the project cycle, for exploratory missions, projects that are just opening, projects that have been running for some time, or those that are closing. At the time of publication, the CommunityFirst Framework has been tested in pilot projects in: (1) Madre de Dios, Peru (MSF OCP, August 2022), (2) Tonkolili, Sierra Leone (MSF OCA, November 2022) and (3) Anzoátegui, Venezuela (MSF OCB, February 2023) The experiences from these pilots (feedback from teams, implementation results, adaptations to each context, etc.) have informed the adaptation of the Framework. CommunityFirst builds on existing community engagement work inside MSF and contributes a practical framework for co-designing health initiatives with communities. To avoid duplicating efforts and resources around community engagement inside MSF, the appendices in this guideline largely refer to already existing MSF resources.09 This guideline is meant to be a living document that can evolve and be adapted given the experience of MSF staff and community members and diverse community contexts. This guide can be used by anyone in MSF who is interested in partnering with communities to improve the responsiveness and impact of their humanitarian programs. This is the first iteration of the document. Subsequent iterations will be published based on additional testing during future phases of the CommunityFirst TIC project.}, urldate = {2024-03-25}, institution = {MSF}, author = {Chapela Trillo, Violeta and Farber, Jessica}, month = mar, year = {2034}, } @techreport{clark_insights_2023, address = {Brighton}, title = {Insights for {Influence}: {Understanding} {Impact} {Pathways} in {Crisis} {Response}}, copyright = {This report is distribued under the terms of the Creative Commons Attribution 4.0 International licence (CC BY), which permits unrestricted use, reproduction or distribution in any medium, provided the original authors and sources are credited and any modifications or adaptations are indicated.}, shorttitle = {Insights for {Influence}}, url = {https://opendocs.ids.ac.uk/opendocs/handle/20.500.12413/18172}, abstract = {The Covid-19 Responses for Equity (CORE) programme was a three-year initiative funded by the Canadian International Development Research Centre (IDRC) that brought together 20 projects from across the global South to understand the socioeconomic impacts of the Covid-19 pandemic, improve existing responses, and generate better policy options for recovery. The research covered 42 countries across Africa, Asia, Latin America, and the Middle East to understand the ways in which the pandemic affected the most vulnerable people and regions, and deepened existing vulnerabilities. Research projects covered a broad range of themes, including macroeconomic policies for support and recovery; supporting essential economic activity and protecting informal businesses, small producers, and women workers; and promoting democratic governance to strengthen accountability, social inclusion, and civil engagement. The Institute of Development Studies (IDS) provided knowledge translation (KT) support to CORE research partners to maximise the learning generated across the research portfolio and deepen engagement with governments, civil society, and the scientific community. As part of this support, the IDS KT team worked with CORE project teams to reconstruct and reflect on their impact pathways to facilitate South-South knowledge exchange on effective strategies for research impact, and share learning on how the CORE cohort has influenced policy and delivered change. This report presents an overview of these impact pathways and the lessons learnt from a selection of the projects chosen to represent the diversity of approaches to engage policymakers, civil society, and the media to generate and share evidence of the effect of the pandemic on diverse vulnerable groups.}, language = {en}, urldate = {2023-11-13}, institution = {Institute of Development Studies}, author = {Clark, Louise and Carpenter, Jo and Taylor, Joe}, month = nov, year = {2023}, note = {Accepted: 2023-11-10T12:56:06Z Publisher: Institute of Development Studies}, } @misc{apgar_innovating_2022, title = {Innovating for inclusive rigour in peacebuilding evaluation}, url = {https://www.ids.ac.uk/opinions/innovating-for-inclusive-rigour-in-peacebuilding-evaluation/}, abstract = {Inclusive and rigorous peacebuilding evaluation is both vital and complex. In this blog we share examples of how we are innovating our methodologies to move towards participatory and adaptive practice.}, language = {en-GB}, urldate = {2022-04-22}, journal = {Institute of Development Studies}, author = {Apgar, Marina and Báez-Silva, Ángela Maria and Deng, Ayak Chol and Fairey, Tiffany and Rohrbach, Livia and Alamoussa, Dioma and Bradburn, Helene and Cubillos, Edwin and Gray, Stephen and Wingender, Leslie}, month = apr, year = {2022}, } @techreport{gray_difference_2022, address = {London}, title = {The {Difference} {Learning} {Makes} - {Factors} that enable and inhibit adaptive programming}, url = {https://www.christianaid.ie/sites/default/files/2022-12/the-difference-learning-makes-factors-that-enable-and-inhibit-adaptive-programming.pdf}, abstract = {Executive Summary When Christian Aid (CA) Ireland devised its multi-country and multi-year Irish Aid funded Programme Grant II (2017-2022), they opted to move away from a linear programme management approach and to explore an adaptive one. Across seven countries: Angola, Colombia, El Salvador, Guatemala, Israel and the occupied Palestinian territory, Sierra Leone, and Zimbabwe, CA and partner organisations support marginalised communities to realise their rights, reduce violence and address gender inequality. Since 2019, Adapt Peacebuilding has accompanied CA Ireland, CA country teams and partner organisations as they experimented with using a deliberate adaptive approach. The authors were also asked to follow up on an initial study by CA Ireland and Overseas Development Institute in 2018, which described the rationale for adopting this new approach and included early lessons from its first year of implementation. The aim of this study is to help deepen CA Ireland, CA country teams’ and partners’ understanding of (a) whether their application of adaptive programming has resulted in better development outcomes, and (b) how they can better understand the factors that enabled or inhibited the effectiveness of using this approach. Over the past three years, this study has found evidence and multiple examples that show adaptive programming contributed to better development outcomes. The main reasons cited were that these were made possible both from improvements to programming strategies based on proactive reflection and learning, as well as those that stem from the reactive capacity of adaptive programmes to change course in response to unanticipated changes in operating conditions. This study found that adaptive programming has enabled better development practice where organisations are enhancing their skills to better respond and be flexible to contextual challenges. 72\% of partners surveyed described adaptive programming as the most useful approach to programme management that they have used. The programme approach has meant that CA and partner staff were better able to explore the significance of change in the context and their contributions to them. It also enabled spaces for meaningful engagement with communities in learning and programme planning processes and encouraged opportunities for experimentation in programming. The study also found that adaptive programming has supported flexible delivery. This led to better outcomes that would not have been possible were the programme not able to make flexible adjustments. The main focus has been the analysis of nine factors that can determine the effectiveness and impact (or otherwise) of using an adaptive approach, flagging important issues for understanding. These factors are identified as: 1) Leadership; 2) Organisational culture; 3) Conceptual understanding; 4) Staff capacities; 5) Partnership approaches; 6) Participation; 7) Methods and tools; 8) Administrative procedures; and 9) The operating context. Together these can provide an analytical framework for assessing an organisation’s ‘adaptive scope’, which can be used as a tool for better understanding an organisation’s potential to generate improved development outcomes via adaptive programming and how to strengthen them. The study concludes with several recommendations for CA Ireland, all of which have relevance for a broader community of donors and implementing organisations interested in the potential of adaptive programming.}, urldate = {2024-01-29}, institution = {Christian Aid}, author = {Gray, Stephen and Carl, Andy}, month = feb, year = {2022}, } @article{albanna_data-powered_2022, title = {Data-powered positive deviance: {Combining} traditional and non-traditional data to identify and characterise development-related outperformers}, volume = {7}, issn = {2352-7285}, shorttitle = {Data-powered positive deviance}, url = {https://www.sciencedirect.com/science/article/pii/S2352728521000324}, doi = {10.1016/j.deveng.2021.100090}, abstract = {The positive deviance approach in international development scales practices and strategies of positively-deviant individuals and groups: those who are able to achieve significantly better development outcomes than their peers despite having similar resources and challenges. This approach relies mainly on traditional data sources (e.g. surveys and interviews) for identifying those positive deviants and for discovering their successful solutions. The growing availability of non-traditional digital data (e.g. from remote sensing and mobile phones) relating to individuals, communities and spaces enables data innovation opportunities for positive deviance. Such datasets can identify deviance at geographic and temporal scales that were not possible before. But guidance is needed on how this new data can be employed in the positive deviance approach, and how it can be combined with more traditional data to gain deeper, more meaningful, and context-aware insights. This paper presents such guidance through a data-powered method that combines both traditional and non-traditional data to identify and understand positive deviance in new ways and domains. This method has been developed iteratively through six development projects covering five different domains – sustainable cattle ranching, agricultural productivity, rangeland management, research performance, crime control – with global and local development partners in six countries. The projects combine different types of non-traditional data with official statistics, administrative data and interviews. Here, we describe a structured method for data-powered positive deviance developed from the experience of these projects, and we reflect on lessons learned. We hope to encourage and guide greater use of this new method; enabling development practitioners to make more effective use of the non-traditional digital datasets that are increasingly available.}, language = {en}, urldate = {2022-08-24}, journal = {Development Engineering}, author = {Albanna, Basma and Heeks, Richard and Pawelke, Andreas and Boy, Jeremy and Handl, Julia and Gluecker, Andreas}, month = jan, year = {2022}, pages = {100090}, } @techreport{dppd_dppd_2021, title = {{DPPD} {Handbook}. {A} step-by-step guide for development practitioners to apply the {Data} {Powered} {Positive} {Deviance} method}, url = {https://static1.squarespace.com/static/614dae085246883818475c39/t/619f7f163ed02a77d13fd1bd/1637842759939/DPPD+Handbook+Nov+2021.pdf}, abstract = {The Method Positive Deviance (PD) is based on the observation that in every community or organization, there are a few individuals who achieve significantly better outcomes than their peers, despite having similar challenges and resources. These individuals are referred to as positive deviants, and adopting their solutions is what is referred to as the PD approach¹. The method described in this Handbook follows the same logic as the PD approach but uses pre-existing, non-traditional data sources instead of — or in conjunction with — traditional data sources. Non-traditional data in this context broadly refers to data that is digitally captured (e.g. mobile phone records and financial data), mediated (e.g. social media and online data), or observed (e.g. satellite imagery). The integration of such data to complement traditional data sources generally used in PD is what we refer to as Data Powered Positive Deviance² (DPPD). The digital data opportunity Recent developments in the availability of digital data provide an opportunity to look for positive deviants³ in new ways and in unprecedented geographical and on temporal scales. A number of studies⁴ have described the challenges related to the application of the PD approach in development. Given these challenges, there are obvious opportunities for innovation in PD and our particular interest here is in the innovative opportunities offered by non-traditional data, following the increasing “datafication” of development and the growing availability of big datasets in a variety of development sectors⁵. DPPD builds on this and expands our ability to extract value from non-traditional digital data while providing a systematic process for leveraging local know-how and the collective wisdom of communities. Data Powered Positive Deviance The DPPD method described in this Handbook emerged from a process of research and testing and follows the same stages as the PD approach. The difference is that DPPD integrates pre-existing, non-traditional data across the five stages, requiring a series of new and specific methods and practices that are not required in the PD approach. The first stage is also somewhat different because it not only defines the problem, but it also checks if it is suitable and feasible to use the DPPD method for the proposed project. Table 1 lists the five stages of the DPPD method. This Handbook dedicates a section to each stage. Stage 1 Assess problem-method fit Stage 2 Determine positive deviants Stage 3 Discover underlying factors Stage 4 Design and implement interventions Stage 5 Monitor and evaluate}, urldate = {2021-11-25}, institution = {DPPD Initiative}, author = {DPPD}, month = nov, year = {2021}, } @techreport{pawelke_lessons_2021, title = {Lessons {Learned} from {Applying} the {Data} {Powered} {Positive} {Deviance}}, abstract = {This report presents six learnings from four pilot projects conducted by the Data Powered Positive Deviance (DPPD) initiative, a global collaboration between the GIZ Data Lab, the UNDP Accelerator Labs Network, the University of Manchester Center for Digital Development, and UN Global Pulse Lab Jakarta. The pilots seek out grassroots solutions to development challenges that range from the interaction between livestock farming and deforestation to gender-based violence and insecurity in dense urban environments in Ecuador, Mexico, Niger and Somalia. The learnings relate to the early stages of the DPPD method, originally proposed by Albanna \& Heeks [1], and focus mainly on the access to, and use of digital data. They are summarized as follows: 1. Remain flexible in the face of data unavailability 2. Leverage existing partnerships for data access 3. Map and fill know-how gaps early 4. Scale with caution 5. Look at deviance over time 6. Look beyond individual or community practices and behavior The report is written for development practitioners, data analysts, domain experts, and more generally anyone interested in using new data sources and technologies to uncover successful local solutions to development challenges.}, institution = {DPPD}, author = {Pawelke, Andreas and Glücker, Andreas and Albanna, Basma and Boy, Jeremy}, month = oct, year = {2021}, } @book{andrews_pdia_2021, address = {Cambridge, MA}, title = {{PDIA} in action}, url = {https://bsc.cid.harvard.edu/files/bsc/files/pdia_book_square_final.pdf}, abstract = {Learning from our experience in 2020, we asked the alumni of our HKS Implementing Public Policy (IPP) Executive Education program, if they wanted to work with our students on their nominated problems. Eight IPP alumni, William Keith Young, Adaeze Oreh, Milzy Carrasco, Kevin Schilling, Artem Shaipov, George Imbenzi, David Wuyep, and Raphael Kenigsberg, who had been trained on PDIA and implementation, signed up to work with our students. Thirty-seven students signed up to take the course beginning January 26th, 2021. The students worked across eight teams and adopted a problem driven approach to foster learning that could help their authorizers develop an action learning strategy to their nominated challenge. This book highlights the students’ work drawing from their blogs as well as the event series. There are 8 sections, one for each of the teams and the problems they worked on during the course. We hope you enjoy reading their stories! Scan the QR Code at the end of each section to learn more.}, urldate = {2021-12-16}, publisher = {Center for International Development, Harvard University}, editor = {Andrews, Matt and Samji, Salimah}, month = may, year = {2021}, } @techreport{von_schiller_applying_2020, address = {Bonn}, title = {Applying {Rigorous} {Impact} {Evaluation} in {GIZ} {Governance} {Programmes}: {Results} of a {GIZ} {Initiative} on {Impacts} in {Governance}}, url = {https://www.idos-research.de/uploads/media/giz2021-0020en-rigorous-impact-evaluation-giz-governance-programmes-results.pdf}, abstract = {Pressure is mounting on international development cooperation agencies to prove the impact of their work. Private and public commissioners as well as the general public are increasingly asking for robust evidence of impact. In this context, rigorous impact evaluation (RIE) methods are increasingly receiving attention within the broader German development system and in GIZ. Compared to other implementing agencies such as DFID or USAid, the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH has so far relatively little experience in systematically applying rigorous methods of impact evaluation. This is particularly true in the governance sector. In order to gain more experience and to understand which methods and formats are best suited for GIZ governance programmes, the Governance and Conflict division and the Africa department launched the ‘Impact Initiative Africa’ in 2016, a cooperative effort with several programmes in Africa. The Initiative set out to apply the experiences from GIZ governance programmes to design and conduct RIEs, and to use the results to steer programme implementation. Initially, the Initiative included three countries: Benin (Programme for Decentralisation and Local Development), Malawi (Support to Public Financial and Economic Management) and Mozambique (Good Financial Governance in Mozambique). During its implementation, the Initiative also benefitted from the experience of two additional governance programmes which had already undertaken RIEs, namely Peru (Citizen-oriented State Reform Programme) and Pakistan (Support to Local Governance Programme II). This report summarizes the insights gained from these experiences and discusses opportunities and limitations regarding the use and usability of RIEs in GIZ governance programmes as well as proposals on how to organise RIEs to maximise learning potential and benefits for the specific programmes and the GIZ Governance sector at large.}, urldate = {2023-03-28}, institution = {GIZ GmbH}, author = {von Schiller, Armin}, year = {2020}, } @techreport{oecd_case_2017, type = {{OECD} {Development} {Cooperation} {Policy} {Papers}}, title = {Case studies of results-based management by providers: {Canada}}, url = {https://www.oecd.org/dac/results-development/results-based-approaches/}, language = {en}, urldate = {2019-03-08}, institution = {OECD}, author = {OECD}, month = jul, year = {2017}, doi = {10.1787/544032a1-en}, } @incollection{storm_foceval_2017, edition = {1}, series = {Smart {Implementation} in {Governance} {Programs}}, title = {{FOCEVAL} – {Promoting} {Evaluation} {Capacities} in {Costa} {Rica}:: {Smart}(er) {Implementation} with {Capacity} {WORKS}?}, isbn = {978-3-8487-3738-3}, shorttitle = {{FOCEVAL} – {Promoting} {Evaluation} {Capacities} in {Costa} {Rica}}, url = {https://www.jstor.org/stable/j.ctv941tdt.12}, abstract = {The National Monitoring and Evaluation System of Costa Rica and its corresponding laws were established during the 1990s. Since then, the country has endeavored to implement monitoring and evaluation (M\&E) activities as part of its public policy framework. Nevertheless, hardly any systematic evaluations had been conducted, and monitoring activities had been reduced mainly to the institutional self-reporting of implementation compliance. Persisting regional disparities and growing levels of inequality among the population raised the level of pressure on the government to present reliable information on the effectiveness of public interventions. Hence, results-oriented evaluations were promoted by some Costa Rican departments as}, urldate = {2020-12-11}, booktitle = {Transformation, {Politics} and {Implementation}}, publisher = {Nomos Verlagsgesellschaft mbH}, author = {Storm, Sabrina}, editor = {Kirsch, Renate and Siehl, Elke and Stockmayer, Albrecht}, year = {2017}, pages = {175--194}, } @incollection{ossi_monitoring_2015, title = {Monitoring and {Adaptive} {Management}}, url = {https://doee.dc.gov/sites/default/files/dc/sites/ddoe/service_content/attachments/08%202015%20WildlifeActionPlan%20Ch7%20Monitoring%20and%20Adaptive%20Management.pdf}, urldate = {2019-02-25}, booktitle = {District of {Columbia} {Wildlife} {Action} {Plan} - 2015}, publisher = {Department of Energy \& Environment, Columbia}, author = {Ossi, Damien}, year = {2015}, } @techreport{terwilliger_consulting_2015_2015, title = {2015 {Rhode} {Island} {Wildlife} {Action} {Plan} - {Chapter} 5 {Monitoring} and {Adaptive} {Management}}, language = {en}, institution = {State of Rhode Island}, author = {Terwilliger Consulting}, year = {2015}, pages = {22}, } @techreport{harvey_salt_2011, address = {Eureka}, title = {Salt {River} {Ecosystem} {Restoration} {Project} - {Adaptive} {Management} {Plan}}, language = {en}, institution = {Humboldt County Resource Conservation District}, author = {Harvey, H.T.}, year = {2011}, pages = {57}, }