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
Themes in tools & tech
● AI and machine learning
● Data mining
● Scenario-based planning
Make use of available data to inform
dynamic response analysis, including cash
transfer programming options, for
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)
● Understanding the
from perspectives of:
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.
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.
Feasibility/ ease of
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
● Assess sustainability of solutions (despite limited resources)
○ Incentives for stakeholders
● 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
● With more cash intervention, opportunity for more granularity on people
of concerns and market