3. LUMA CONSULTING
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Define the solution space
Can you succinctly present a solution statement about the food security situation in Ethiopia in 2021?
Problem statement: Rainfall variability, locust invasion, COVID-19 pandemic and low inputs use negatively affecting
the health and food security of people in Oromia Regional state
Main Drivers and Intervention
COVID-19 pandemic
--------------------------
Public Heath
Campaign
Locust outbeak
----------------------------
Increase pesticide use
Climate variability
(rainfall)
---------------------------
Expand small-scale
irrigation
Limitted acces to
agricultural inputs
----------------------------
Improve ag subcidy
and marekt access
Shortage of feed for
livestock
---------------------------
Increase livestock
feed supply
Solution statement: Managing locust invasion and improving input supply (seed, fertilizer and feed) with public health
campaign can improve the health and food security of people in the Oromia Regional State
4. LUMA CONSULTING
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Scenario analysis
In terms of the problem statement and variables that your team has decided to focus on, what are the best, worst, and most-
likely scenarios for food security outcomes in Oromia in 2021 ?
• What are the ‘most likely’ and ‘worst case’ scenarios for food insecurity for 2021?
• What interventions can you explore to improve those scenarios?
Irrigation + fertilizer input increase Public health campaign-increase health
workers
Increase pesticide use Increasing livestock feed
5. LUMA CONSULTING
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Scenario analysis
In terms of the problem statement and variables that your team has decided to focus on, what are the best, worst, and most-
likely scenarios for food security outcomes in Oromia in 2021 ?
• Were you able to explore the interventions that you wanted to? YES
6. LUMA CONSULTING
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Recommendations
What are your final recommendations?
Consider these questions :
• What program or policy recommendations would follow from your analysis of the problem space?
• Increasing pesticide import for locust control
• Increasing crop production by enhancing inputs use through smart subsidies and improved market
access
• Expanding public health campaign to minimize the impact of COVID 19 and other diseases
improved the health and food security of people in the Oromia Regional State
• If there is nothing specific from the analysis you were able to do, what kind recommendations would you
hope to make in the future if the right data and models were available?
• Estimate the cost of each intervention
• Prioritize the interventions based on impact and cost feasibility
7. LUMA CONSULTING
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Recommendations
What are your final recommendations?
• Who would be you target audience for final recommendations?
• Ministry of agriculture (extension system)
• Regional Bureaus of Agriculture
• Zonal and Woreda Administrators and Bureau Heads
• Input and export companies
• Federal and Regional Research Institutions and HLIs
• Farmers organizations (Cooperatives and Unions)
• What additional functionality or data would you need to be able to incorporate these technologies into
your work around advising program, policy, and strategy development?
• Limited capability to do:
quantitative analysis
Trade-off analysis
Integrated analysis of integrating qualitative and quantitative data
8. LUMA CONSULTING
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Recommendations
Present screenshots from CauseMos for full exploration of the solution space to inform intervention recommendation
URL
• Did you add any additional intervention nodes did you add to your CAG? If yes, which and why? If no, were their
issues with finding what you would have wanted to add?
• Yes, Irrigation, market access, Fertilizer inputs and subsidy
• In model view, how did intervention nodes affect the outcomes you were interested in?
• The interventions affect the outcome in either positive and negative way YES
• Were their any models or scenarios available in dataview that gave you in insight into interventions or
recommendations? If yes, which? If no, what would you have wanted to see?
• Yes: Crop yield, rainfall, response to fertilizer and irrigation (DSSAT – Supermass)
• No: Cost and effect of input subsidies and irrigation infrastructure, crop residue for animal feed,
Food security
Human disease
9. LUMA CONSULTING
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Recommendations
Present screenshots from SuperMaaS intervention models
Consider these questions :
• Were their any models your team explored with intervention insight?
• YES, DSSAT and CHRIPS -
• but we depend mostly on CauseMos
• If yes, what did you learn from exploring them?
• Yield climate relationships, rainfall and drought conditions
10. LUMA CONSULTING
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Recommendations
Intervention and final recommendation snapshot
Day Six Outbrief – Interventions Full suite of tools; emphasis on intervention models
What technologies or models were most
helpful or relevant to the solution space your
team explored?
• CauseMos (Scenario Analysis , Matrix, data)
Were you able to make an actionable program
or policy recommendation? If yes, what? If
no, what was the main barrier for this?
• YES, but mostly on a qualitative basis
What did your team spend the most time on?
• Scenario exploration and analysis
Did you end up assigning roles or breaking
down the analysis between teammates? If
yes, how?
• The Team work together using Zoom meeting
Biggest frustration(s) with the technology?
• Limited integration between CauseMos and SupperMass
#1 feature request for these technologies?
• User friendly integration of CauseMos and Supermass for quantitative analysis of food
security
11. LUMA CONSULTING
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What would do you wish you could have found in the system (through SuperMaaS models or CauseMos)?
Smooth integration of CauseMos and SuperMass - still loosely connected
• CauseMos: is a nice tool for qualitative analysis
• Supermass: Provides rainfall, input and yield relationships but based only on predefined variables
