dgis: increasing effectiveness and efficiency through probabilistic decision modelling
TRANSCRIPT
DGIS
Increasing Effectiveness and Efficiency through
Probabilistic Decision Modelling
Keith Shepherd, Eike Luedleing, Jan de Leeuw, Grace Muinga
“The quantitative analysis of decisions and the supporting metrics will have a profound effect on intervention policy”
Decisions modelled• Integrated watershed management in the Tana River Basin in Kenya;
• Payment for environmental services scheme for Sasumua Dam in Kenya;
• Alternatives for water management on the Mekong river in Laos;
• Business case for manufacturing fertilizer from human manure in Ghana;
• Evaluation of a government irrigation scheme in Ghana;
• Design of a regional system of seed storage nodes for maintain agrobiodiversity in the Volta Basin;
• Evaluation of interventions for building resilience to drought in the Horn of Africa;
• Assessing Risk of Investment in Groundwater Resources in Sub Saharan Africa – case study of the Merti aquifer in Kenya.
Outputs
Replenishment
Irrigation growth
Initial irrigated area
Water use per hectare
Aquifer size
Natural water use
Importance threshold
Identification of high-value variables
Quantitative impact pathways
p
p p p
p
pp
p
pp p
p
p
n
n
nSLO 1SLO2SLO3SLO4
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Can we estimate these numbers?
Increasing effectiveness and efficiency of DGIS through decision modelling
•A coherent approach for representing and quantifying the project impact pathway, including activities and risks
• Entire project level• Country level • Individual intervention level
•Development of this approach in the DGIS project could lead to a whole new generic approach to project planning, monitoring & evaluation, and impact assessment.
• Capacity building opportunities
Some benefits
• Reveal important uncertainties in intervention design and impact pathway
• Improve intervention design to maximize impacts, reduce risks
•Define high value metrics for monitoring during project implementation
•Guide accumulated evidence for impact attribution
• Provides a solid business case to present to investors, donors
AIE Process
1. Decision Clarification Workshop2. Calibrated Probability Training Workshop3. Detailed Decision Modeling Workshop4. Risk/Return Analysis 5. Value of Information Analysis
Shepherd KD, Farrow A, Ringler C, Gassner A, Jarvis A. 2013. Review of the Evidence on Indicators, Metrics and Monitoring Systems. Commissioned by the UK Department for International Development (DFID). Nairobi: World Agroforestry Centre. http://r4d.dfid.gov.uk/output/192446/default.aspx
Clapp A, DauSchmidt N, Millar M, Hubbard D, and Shepherd K. 2013. A Survey and Analysis of the Data Requirements for Stakeholders in African Agriculturehttp://r4d.dfid.gov.uk/Output/193813/Default.aspx
http://www.hubbardresearch.com/training/
Resources