CRP Portfolio 2017-2022

Value for Money Analysis

Frank Rijsberman September 2015

Dryland Cereals and Legumes systems

Agri-food system programs Global integrating programs

Coordinating programs / platforms

Gender

Capacity Development

Genebank 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 TR I T I ON

&

HEA L TH

P I

M

Genetic Resources Policy

W L E

C L I

MAT E

CH A N G E

Breakdown of investments at the highest level

Agri-food system vs.

Global Integrating

SRF SLOs vs.

Crosscutting (Gender et al)

Breakdown of investments by

pre-proposal

Breakdown of investments by

SLO(*)

(*) Increased

Productivity

treated as its

own SLO and

represented

here as 0

Heatmap of pre-proposals by IDO

Second SRF Priority Framework:

2022 (and 2030) CGIAR Targets – link to SDGs

R

EDU

CED

P

OV

ERTY

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

IMP

RO

VED

FO

OD

A

ND

NU

TRIT

ION

SE

CU

RIT

Y FO

R

HEA

LTH

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

IMP

RO

VED

NAT

UR

AL

RES

OU

RC

ES S

YSTE

MS

AN

D E

CO

SYST

EMS

SER

VIC

ES

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

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?

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

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 level 1 2

VA

LU

E

Most preproposals provide a summary table with their claim against the 2022 SRF Targets.

MO

NE

Y

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.

2022 SRF TARGETS

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 micronutrdefcienc

y

10% less women

w insufficient food groups

% weight in this

SLO ($ M(*))

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

% weight in this

SLO ($ M(*))

LiveStck2

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

AG

RI-

FOO

D

GLB

L IN

TEG

RA

TIN

G

2022 Targets 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

Moneyby IDO

242

Heat map of CCAFS Flagships by sub-IDO

2022 SRF Targets

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

micronutrdefciency

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

Moneyby IDO

487

9) A play in both yield increase and adoption? Whole-farm productivity increased by 60% for at least 600,000 HH

Heat map of RTB Flagships by sub-IDO

Preproposal Name

Total amount for non-

crosscutting (USD, M)

PIM amount linked to SRF

targets (USD, M)

PIM as a % of Total

Agr

i-fo

od

Pro

gram

s 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%

Glo

bal

In

tegr

atin

g P

rogr

ams 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

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.

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

Consortium of International Agricultural Research

Centers