ISPC 13

1. Quantitative Priority Setting
(QPS) for the CGIAR
Gerald C. Nelson
May 2016
ISPC May 26, 2016
CIP Headquarters, Lima, Peru

2. What is QPS?
• A process to identify…
– CGIAR activities of highest value
– Opportunities to increase efficient use of
resources
– Whether funding is sufficient
• A critical piece of a monitoring and review
system
– Ex-ante, en-passant, ex post

3. Why Do QPS for the CGIAR?
• Funders are demanding this
• Center managers and scientists need guidance on
priority setting for investments
• National program partners demand this so they
can better see benefits of CG collaboration
• Current resources are limited and future budget
growth is uncertain
• The QPS is likely to demonstrate high returns for
more resources

4. First things first
• Goals determine priorities
– Does the SRF identify the right goals?
• Priorities for CGIAR activities are influenced by
– Goals
• Do we have the right goals?
– Capacities of the CGIAR (human, capital, spatial,
institutional)
• Do we have a good catalog of these?
– Who’s doing what (IARCs, NARS, private sector)
• Do we have a good inventory of the other actors and their
activities?

5. Elements of QPS
• Standardization of process. Common …
– Template for detailed, quantitative technology
description
– Modeling environment, using suite of models
– Set of metrics
• Explicit recognition and identification of limits

6. Proposed methodology step 1, common template
for technology evaluation
• Prepare a three level template for use by CRPs/Centers
to assess ROI for a new ‘technology’
– Innovator – technical nature of new technology, cost and
time frame for development; partners
– Adaptor – cost and time frame for modification for local
use, who is adaptor (public/private/NGOs), by location
– Disseminator – cost and time frame for adoption, rate of
update, who is disseminator (public/private sector), by
location
• Much of this information contained in CRP proposals
– See CGIAR Template Description V3.docx

7. Proposed methodology step 2: Standardized
evaluation of proposed technology
• Use common modeling suite and data
– Climate data from selected GCMs
– Hydrology and water supply/demand models
– DSSAT crop modeling suite with consistent soil data
– IMPACT
– Links to CGE (Globe model)
• Use standard qualitative scenarios and quantitative
components
– CMIP5 climate/weather data
– SSP GDP and population data
• Develop and use agreed quantitative metrics

8. Why Global Futures?
• Has already developed many of needed tools
– Detailed modeling suite with all CGIAR mandate
crops/animals
– Use of climate/SSP data
– Some metrics already developed (e.g. ROI, share
of population at risk of malnutrition)
• Partnership with all CGIAR centers

9. Financial quantitative metrics from the
IMPACT modeling suite
• Financial return on investment
– Internal rate of return
– Net present value
– Benefit cost ratio

10. Quantitative metrics from the IMPACT
modeling suite
• Investment-quantitative output ratios, average
and marginal, such as
– Adoption rates and yield increases ($ per household
adopting improved technologies)
– GHG emissions reductions ($ per MT reduction from baseline)
– Water use quantity ($ per MT reduction from baseline) and
quality ($ per MT reduction in nitrogen loading)
– Share of nutrient requirement met
• Baselines and results are spatially and temporally
disaggregated.

11. SRF Aspirational Target 1.1 and
Quantitative metric results
Amount
needed
(million $)
Target
Contribution
million households)
$ per
household
Total 919.2 196.9 4.7
A4NH 160.7 20.5 7.9
CCAFS 53.8 11.0 4.9
DCLAS 75.0 25.0 3.0
Fish 27.6 4.9 5.6
FTA 75.8 41.0 1.8
Livestock 35.8 6.5 5.5
Maize 119.3 15.0 8.0
PIM 100.0 10.0 10.0
Rice 17.0 16.5 1.0
RTB 134.1 8.0 16.8
Wheat 34.9 17.5 2.0
WLE 85.2 21.0 4.1
100 million more farm households have adopted improved varieties, breeds or trees,
and / or improved management practices by 2022
These results are not comparable!

12. Concerns about the approach
• General – its not able to capture relevant
benefits of investment; e.g.,
– NRM research benefits
– Fish and livestock research benefits
– Policy research benefits
• Missing elements of modeling
– Focus on the most important ones first

13. Improvements to modelling suite
needed
• Incorporate variability
• Improve existing metrics (kcals, share of
malnourished) and add new ones (nutritional
detail, etc.)
• Multiple consuming households (e.g., low and
high incomes; urban and rural)
• Update/improve trade distortion parameters
• Improve demand parameters

14. Where should development of QPS
elements be done, and how used?
• Standardized tools and processes
– Developed by individual centers/CRPs/outside experts
– Implemented and supported by consortium
• Identification of potential biological and
management technologies
– By biological scientists inside and outside CGIAR
• Tools use should guide funding allocation
decisions at
– CGIAR
– CRP
– Center

15. Examples of tools improvements by
specialists
• Climate change effects on agro-ecological
zones by CCAFS (climate analogue tool)
• Nutritional details by A4NH (e.g. food group
and nutritional adequacy definitions)
• Water use efficiency by WLE
• Global economic model improvements by
PIM/IFPRI

16. Back to the beginning:
Who identifies goals?
• Need a global process that
– Involves stakeholders from all walks of life
– Monitors progress
– Proposes changes in priorities over time