Convened by:

Track 4: Data and Resilience

Over the past decade there has been a heightened focus on fostering resilience and a consolidation of perspectives within developing countries and fragile contexts. Yet there remains limited empirical evidence on how market systems, including private-sector approaches, support resilience capacities. As a community, humanitarian and development practitioners are still grappling with how to measure change, particularly systems-level change. Because resilience is a multi-faceted concept, understanding how systems-level change supports or negatively impacts resilience adds to this challenge.

Sessions in this track will illustrate how we use proven and emerging measures, methods, and evidence for strengthening the resilience of households, communities and market systems and how we empower people with data. The committee is interested both in new data and ways of measuring, as well as new uses or analysis for existing datasets. Because different definitions of resilience are used by different organizations, if desired, you may provide your definition of resilience at the forefront of your proposal submission to allow reviewers to contextualize it and better understand your proposal

  • What are examples of innovative or successful partnerships for generating, sharing, and using data for building resilience at the market, community and household level?
  • How do we better leverage data from private sector sources to inform resilience strategies?
  • What unexpected data sets can inform markets systems approaches to build resilience? For example, how is data relating to climate, public health, market prices, soil, etc. being used?
  • What are the current uses of “newer” technologies (e.g., remote sensing, crowdsourcing, SMS data, modeling/predictive analytics, blockchain, etc.) for understanding and monitoring resilience at the system, community and household level? What are the benefits or limitations to such technologies? What are the risks and opportunities within fragile settings?
  • What is our responsibility as development practitioners for consistently cycling extracted data back to program participants? How can this be done in a way that fosters agency and supports household and community resilience?
  • What are the key attributes for ‘good’ evidence for measuring resilience of diverse market actors--and how do these attributes vary by actor group?
  • What is the current state of evidence on market systems and resilience? What exists, what are the gaps, what are the challenges to building the evidence base?
  • Demonstrate how data is made actionable for those most vulnerable to shocks and stresses in order for them to drive their own journey to self-reliance and sustainable livelihoods
  • Provide examples of how Big Data sources are being integrated into traditional program approaches to ensure interventions are more responsive to climate change, natural disasters, and other shocks experienced by markets, communities, and households
  • Present examples of the use of blockchain to document and track resilience of systems (value chains, for example), communities or households.
  • Lessons on how we can learn from community quality improvement processes; using conversations around data translation, learning and action to support more resilient markets
  • Illustrations of how locally-sourced data—where citizens are engaged in the process of data collection—can be relevant and timely at the scale at which decisions are made.
  • Examples of partnerships between practitioners and business-to-consumer, business-tobusiness, consumer-to-consumer or government actors who sell or make available data, such as satellite companies, national registries, MNOs, financial service providers, and climate and weather data companies.
  • Describing specific opportunities for the use of data and artificial intelligence in market systems in fragile and conflict-affected settings
  • Explanations of how to use imperfect data for development program decision-making. This includes examples of successful uses of incomplete data to inform program or policy decision-making; and identifying alternative analytical approaches for the future
  • Thinking outside of the box: providing examples of creative methodologies to test or analyze the link between market systems and resilience
  • Liberating data for use by market actors: taking stock of critical data gaps and pursuing data capture and use opportunities
  • Introducing promising practices in data translation—how development partners can reshape program data for use by program participants. Relevant content may provide insights on how program data can be used to:
    • foster agency and empowerment among program clients/participants
    • shape the architecture of decision-making among market actors
    • catalyze social and behavior change

We are currently accepting proposals from SEEP members for Peer Learning Sessions and abstracts for the Innovation Challenge. The deadline for submissions is May 31, 2019. 


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