CRP Portfolio 2017 2022 Value for Money Analysis - Frank Rijsberman

1. CRP Portfolio 2017-2022
Value for Money Analysis
Frank Rijsberman September 2015

2. Dryland Cereals and Legumes systems
Agri-food system programs Global integrating programs
Coordinating programs / platforms
Gender
Capacity Development
G
e
n
e
b
a
n
k
S
+
+
Big data/ ICT
Fish agri-food systems
Forest and Agroforestry landscapes
Livestock agri-food systems
Maize agrifood systems
Rice agri-food systems
Roots, tubers and bananas systems
Wheat agri-food systems
N
U
T
R
I
T
I
O
N
&
H
E
A
L
T
H
P
I
M
Genetic Resources Policy
W
L
E
C
L
I
M
A
T
E
C
H
A
N
G
E

3. Breakdown of investments at the highest level
Agri-food system vs.
Global Integrating
SRF SLOs vs.
Crosscutting (Gender et al)

4. Breakdown of investments by
pre-proposal

5. Breakdown of investments by
SLO(*)
(*) Increased
Productivity
treated as its
own SLO and
represented
here as 0

6. Heatmap of pre-proposals by IDO

7. Second SRF Priority Framework:
2022 (and 2030) CGIAR Targets – link to SDGsREDUCED
POVERTY
100 million more farm households have adopted improved varieties, breeds or trees, and / or improved
management practices
30 million people, of which 50% are women, assisted to exit poverty
IMPROVEDFOOD
ANDNUTRITION
SECURITYFOR
HEALTH
Improve the rate of yield increase for major food staples from current <1% to 1.2-1.5% per year
30 million more people, of which 50% are women, meeting minimum dietary energy requirements
150 million more people, of which 50% are women, without deficiencies in one or more of the following
essential micronutrients: iron, zinc, iodine, vitamin A, folate and vitamin B12
10% reduction in women of reproductive age who are consuming less than the adequate number of food
groups
IMPROVEDNATURAL
RESOURCESSYSTEMS
ANDECOSYSTEMS
SERVICES
5% increase in water and nutrient (inorganic, biological) use efficiency in agro-ecosystems, including through
recycling and reuse
Reduce agriculturally-related greenhouse gas emissions by 0.2 Gt CO2-e yr-1 (5%) compared with business-
as-usual scenario in 2022
55 million hectares (ha) degraded land area restored
2.5 million ha of forest saved from deforestation

8. V4M combines analysis of outcomes and budgets of a proposal.
What outcomes does a 1 Bn $ investment buy?
The analysis aims to answer five key questions:
1. What share of the CGIAR targets is a proposal aiming for?
2. Are the outcome targets consistent across summary narrative,
Performance Indicator Matrix and Flagship detailed descriptions (and
reasonable? credible?)?
3. Are outcomes budgeted by Flagship and Outcome (reasonable?
credible?)?
4. Will the portfolio deliver on the SRF (cost? distribution? overinvestment?)?
5. Are there gaps?

9. What the V4M analysis is NOT:
• A complex economic analysis, or a complex technical calculation
• One single number of return on investment
• An assessment of the social benefits of the projects
• A monetization of the research outcomes
• An algorithm to maximize value-for-money

10. We evaluate the value of each preproposal at two different levels, by
analyzing their claims for how they contribute to the SRF Targets. We
map these claims against the corresponding non-crosscutting funding.
Overall
Most preproposals map their funding to the
sub-IDOs. To get to a SLO level aggregation
from the IDO level, we count the funding
allocated to “Increased Productivity”
twice: once against “Reduced Poverty”,
and once against “Improved Food and
Nutrition Security” (See SRF tree).
At the flagship level1 2
VALUE
Most preproposals provide a summary table
with their claim against the 2022 SRF
Targets.
MONEY
We count the funding allocated to an
outcome towards this outcome’s result
and add it up to the flagship level.
In the Performance Indicator Matrix, we
look for the individual outcomes with
results that closely match the SRF Targets.
We then add up these claims to the flagship
level.

11. 2022
SRF
TARGET
S
Reduced Poverty Improved Food & Nutrition Security for Health Improved Natural Resource Systems & Ecosystem Services
Total non
cross
cutting $
as a %
distributn
VALUE MONEY VALUE MONEY VALUE MONEY
100M HH
adopt
varieties
/
practices
30M
people
exit
poverty
% weight
in this
SLO
($ M(*))
Yield inc.
From
<1% to
1.2% to
1.5%/yr
30M
people
w/ min
diet
energy
150M
people
w/o
micronut
rdefcienc
y
10% less
women
w
insufficie
nt food
groups
% weight
in this
SLO
($ M(*))
5% inc. in
water
&nutrien
t use
efficiency
Reduce
Ag GHG
by 0.2 Gt
CO2/yr
55M ha
restored
2.5M ha
of forest
saved
% weight
in this
SLO
($ M(*))
LiveStck
2
12%
Dryld 20 40 60% (515) 1.5% 3 110 30% (265) 27 10% (89) 11%
RTB 8 20 50% (336) x 5M 40% (317) 2.5 10% (85) 8%
Maize1 8%
Rice 22 17 50% (473) 1.5% 30 40% (333) 5% 5% 10% (116) 11%
AgroFrst 100 25 35% (257) x 25 50 20% (170) 0.2 – 0.6 30 3 -9.6 45% (319) 11%
Wheat1 6%
Fish 5 2.5 40% (158) 5 1M 40% (172) 15% 20% (89) 6%
A4N 35 10% (66) 100 10% 90% (532) 0 10%
PIM 29.9 8.9 60% (271) 35% (154) 22.7 5% (25) 5%
Ccafs 12.5 3.75 50% (129) 25% (75) 0.2 (8%) 2 25% (68) 4%
WLE2 8%
Notes:
(*) Dollar figures only
include investments in
non cross-cutting issues.
“Increased Productivity”
counted twice
Comments:
1) Only 2030 targets were provided, but they are
written in alignment with the SRF
2) Targets by flagship only, not aggregated at the CRP
level.
Color legend
Green = good coherence of the contributions to SRF Targets
between overall preproposal’s and individual outcomes’ claims
Yellow= medium coherence of the contributions to SRF Targets
between overall preproposal’s and individual outcomes’ claims
Red = poor coherence of the contributions to SRF Targets
between overall preproposal’s and individual outcomes’ claims
Overall V4M Assessment by pre-proposals
AGRI-FOODGLBLINTEGRATING

12. 2022
Target
s in
SRF
Reduced Poverty Improved Food & Nutrition Security for Health Improved Natural Resource Systems & Ecosystem Services
100M HH
adopt
varieties /
practices
30M people
(50% women)
exit poverty
Yield inc.
From <1% to
1.2% to
1.5%/yr
30M people
(50%
women)w/
min diet
energy
150M people
(50% women)
w/o
micronutrient
deficiencies
10% reduction
in women w/
less than
adequate food
groups
5% inc. in
water and
nutrient use
efficiency
Reduce Ag
greenhouse
gas by 0.2 Gt
CO2-e yr-1
(50%)
55M ha
restored
2.5M ha of
forest saved
Total
Invt.
amnt
CCAFS Value Money Value Money Value Money Value Money Value Money Value Money Value Money Value Money Value Money Value Money $
FS1 11.5 45 45
FS2 8 25 25
FS3 10.8 30 0.2 50 2 18 98
FS4 x1 45 45
Total 30.3 100 x 45 0.2 50 2 18 213
Comments:
1) Not expressed in terms of SRF target
Number of organisations and institutions in selected countries/states
adapting plans and directing investment towards climate- and
nutrition-smart food systems to optimise consumption of diverse
nutrient-rich foods
Reduced Poverty $ 99M
Increased productivity 30M
Improved food and nutrition security 45M Improved natural resource and eco systems
68M
V4M at the flagship level for Climate Change, Agriculture and Food Security
Mone
yby
IDO
242

13. Heat map of
CCAFS
Flagships by
sub-IDO

14. 2022
SRF
Target
s
Reduced Poverty Improved Food & Nutrition Security for Health Improved Natural Resource Systems & Ecosystem Services
100M HH
adopt
varieties /
practices
30M people
exit poverty
Yield inc.
From <1% to
1.2% to
1.5%/yr
30M people
w/ min diet
energy
150M people
w/o
micronutrdefc
iency
10% less
women w
insufficient
food groups
5% inc. in
water
&nutrient use
efficiency
Reduce Ag
GHG by 0.2 Gt
CO2/yr
55M ha
restored
2.5M ha of
forest saved
Total
Invst.
Amnt
RTB Value Money Value Money Value Money Value Money Value Money Value Money Value Money Value Money Value Money Value Money $
FS1 x1 31 31
FS2 2.5 315 202 31 10%3 47 x8 33 142
FS3 x6 18 x6 18 1.7 40 76
FS4 3.52 15 2M4 18 33
FS5 x9 18 52 25 x9 18 1.2M7 15 0.5 21 97
FS6 0
Total 2.5+ 67 28.5 71 x 114 x 33 3.2M 33 2.2 61 379
Comments:
1) Amount of yield increase not quantified
2) Stated in terms of outcome increase, not poverty reduction
3) Target provided but not in terms that align with SRF
At least 5,000,000 HH increased their annual RTB yield by at least 10%
4) Target expressed in terms of diversity index increase for 2M HH
5) Budget amount shared with an outcome on post-harvest loss
reduction
6) Investments not described in terms of SRF targets
In areas affected by pests and diseases, yield restored to previous
infection conditions by 1,800,000 farmer HH, of which at least 25% are
female headed households
7) Target include small children and expressed as # of HH
8) Is this a play in micro-nutrient?
Annual production of RTB nutrient-rich varieties increased by 5-10% in
target countries
Reduced Poverty $ 85M
Increased productivity 251M
Improved food and nutrition security 66M Improved natural resource and eco systems
85M
V4M at the flagship level for Roots, Tubers and Bananas
Mone
yby
IDO
487
9) A play in both yield increase and
adoption?
Whole-farm productivity increased by
60% for at least 600,000 HH

15. Heat map of
RTB Flagships
by sub-IDO

16. Preproposal
Name
Total amount
for non-
crosscutting
(USD, M)
PIM amount
linked to SRF
targets
(USD, M)
PIM as a % of
Total
Agri-foodPrograms
Maize 435 n/a n/a
Wheat 324 n/a n/a
Dryld 634 500 79%
RTB 487 379 78%
Fish 376 285 76%
LiveStck 673 230 34%
Rice 616 202 33%
Frst 642 69 11%
Global
Integrating
Programs
PIM 317 284 90%
Ccafs 242 213 88%
WLE 435 206 47%
A4N 599 211 35%
Coherence between high level goals and outcome level goals
(PIM), as measured by % of total non-crosscutting investments
in the PIM that could be linked to a SRF target
Color assignment based on
“PIM as % of total”
This color code will be used
in the next slide
Green = good coherence of
the contributions to SRF
Targets between overall
preproposal’s and individual
outcomes’ claims
Yellow= some coherence of
the contributions to SRF
Targets between overall
preproposal’s and individual
outcomes’ claims
Red = poor coherence of the
contributions to SRF Targets
between overall
preproposal’s and individual
outcomes’ claims

17. Limitations of the V4M Analysis
• Value analysis: Not many “outcomes” are expressed in terms of the
SRF targets. And when they are, they use inconsistent language
making it hard to map to the SLOs.
• Money analysis: Inconsistencies on the level of budgeting in the PIM, by
outcomes or by sub-IDOs.
• Heat maps: does not capture that not all sub-IDOs are created equal.
Some receive higher level of priority from donors or from experts.
• Crosscutting investments: we don’t currently have a methodology for
assessing the V4M of those.
• Some investments contribute to multiple targets (“Increased
Productivity”, targets for IDOs or Sub-IDOs, “Reduction in GHG” in two
places).
• We don’t have a way to produce heat maps along the value chain
(upstream vs. downstream).
• Large volume of outcomes (315), flagships (71) and a framework for
collecting value information that is too loose.
• The money numbers in the PIM are often not credible and clearly not
backed up by detailed CoA budgeting.

18. Conclusions
• Priority setting:
1. Set targets linked to SDGs
2. Allocate funding to CRPs & platforms that are rated
“A” by ISPC and achieve the targets
• V4M analysis shows pre-proposals aim to deliver SRF
targets for 2022, by and large, if rated A and demonstrate
outcomes and budgets credibly in full prop.
• Many questions on consistency and credibility in
outcomes and budgeting – particularly in PIM-for full prop
• Reco: clearly separate outcomes from milestones

19. Consortium of International Agricultural Research
Centers