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Approach to Challenge 1 - Cash & Big Data

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Cash and big data working group presentation presentation

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Approach to Challenge 1 - Cash & Big Data

  1. 1. Cash and big data
  2. 2. Mapping the problem
  3. 3. Problem tracks? 1. Automated guidance for response option analysis 2. Data mining for predictive modeling 3. Digital ID for financial inclusion 4. Track cash program in real time and adapt the response to better meet needs and fill gaps
  4. 4. Themes in tools & tech ● AI and machine learning ● Data mining ● Crowdsourcing ● Scenario-based planning
  5. 5. Goal Make use of available data to inform dynamic response analysis, including cash transfer programming options, for humanitarian coordination.
  6. 6. Success criteria Timely, right scale, inclusive, appropriate ● Overall success of a cash intervention based in lifting people to a minimum standard and then potential to elevate then beyond that. ● Increase efficiency of response ○ Decrease in # of days from onset of disaster to (start/completion) of cash transfer program ○ Decrease in programmatic overhead costs per $1 of distributed cash to affected population ● Increase appropriateness of response ○ Percentage of decisions that consider and comply with Sphere standards ○ Percentage of programs designed using participatory techniques with the affected communities ○ Increase in recipient satisfaction (based on post distribution monitoring)
  7. 7. Journey map ● Understanding the assessment process from perspectives of: ○ Affected individual ○ Humanitarian responder
  8. 8. Journey map Generalized for both sides.
  9. 9. Some solution ideas ● Take a visualization of the desired outcomes of a cash intervention to the intended recipient community for feedback. Mapping assumptions in an explicit and visible way, allows the community to better understand the desired outcomes and better inform us on how the program worked. ● Simplify some variables for more actionable analysis. ● Nested mapping of needs. For a visual way to explore the intervention plan and gaps. Update the visualization with feedback and new data. Easily observe progress on zoomed-out scale or down at individual level. ● Micro-payments for providing data or feedback.
  10. 10. Some more solution ideas ● Tie service delivery to accurate reporting of data (at a community level) in order to facilitate cooperation and aggregate incentive delivery. ● Using AI to analyze collected field notes. Having an open repository of shared field notes in order to improve analysis and response. ● New way to assess needs and gather feedback. For example, instead of a comment box something like a “how are we doing” button panel. ● Easy to understand and accessible summary of assessment results given to community for feedback and updates.
  11. 11. Solution mapping Value/ impact + Feasibility/ ease of implementation
  12. 12. Overarching themes 1. Inclusiveness and accountability 2. Collaboration rather than competition and building connections between stakeholders 3. Ability to predict and develop forward-looking analysis 4. Diversity of data for more robust situation awareness 5. Diversification of participants through engagement of non- traditional responders in the financial sector
  13. 13. Next Steps ● Assess sustainability of solutions (despite limited resources) ○ Incentives for stakeholders ○ Crowdsourcing ● Including this paradigm disruption into a humanitarian governance model ( new financial model, new decision making model, robo-advisor ) ● Adapting Humanitarian skills needed to address the new Humanitarian landscape (eg. ethicists, crowdsouring managers ) ● Consult with stakeholders to assess usefulness of solutions (eg. people of concern ) ● With more cash intervention, opportunity for more granularity on people of concerns and market

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