Input and
Output Marketsin Africa SAIOMA)
FINAL EVALUATION OF SAIOMA PROGRAM
Final Report
Natural Resources Institute - NRI
University of Greenwich
www.nri.org
Kate Wellard, Daimon Kambewa, Hannington Odame, Charles Muwe Mungule,
Tanya Stathers, Elijah Muange, Elsie Kangai, Mayamiko Kakwera
12 December 2016
Strengthening Agricultural Input and
Output Markets in Africa (SAIOMA)
SAIOMA Project Final Evaluation Report NRI
This report was made possible through support provided by the U.S. Agency for International
Development, under the terms of Cooperative Agreement No. AID‐OAA‐A‐12‐00061, and
implemented by The Alliance for a Green Revolution in Africa (AGRA) and its partners. The
opinions expressed herein are those of the authors and do not necessarily reflect the views of
the U.S. Agency for International Development. For more information, please contact:
The Alliance for a Green Revolution in Africa (AGRA)
4th Floor, West End Towers, Off Waiyaki Way
P.O. Box 66773 00800
Westlands, Nairobi.
Email: info@agra.org
SAIOMA Project Final Evaluation Report NRI
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Contents
List of Tables .......................................................................................................................................5
List of Figures......................................................................................................................................6
Acknowledgements............................................................................................................................7
Acronyms............................................................................................................................................8
Executive Summary................................................................................................................................9
Part I: INTRODUCTION .........................................................................................................................17
1. Background...................................................................................................................................17
1.1. Introduction ..........................................................................................................................17
1.2. Background and Context.......................................................................................................17
1.3. Objectives of SAIOMA final evaluation.................................................................................18
1.4 Scope of the evaluation ........................................................................................................19
1.5 Key Evaluation Questions .....................................................................................................20
1.6. Methodology.........................................................................................................................21
1.7. Challenges.............................................................................................................................24
PART II – RESULTS.................................................................................................................................25
2. PROGRAM DESIGN AND RELEVANCE...........................................................................................25
2.1. Quality and relevance of program design.............................................................................25
2.2. Relevance of countries..........................................................................................................26
2.3. Relevance of commodities....................................................................................................26
2.4. SAIOMA target group............................................................................................................27
3 PROGRAM PERFORMANCE – INCREASING SMALLHOLDER AGRICULTURAL PRODUCTION
THROUGH ACCESS TO IMPROVED INPUTS ..........................................................................................30
3.1 Overview ...............................................................................................................................30
3.2 Agro-dealer-led input delivery..............................................................................................30
3.3 Improved agronomic practices (demand-creation)..............................................................34
3.4 Agro-dealer performance .....................................................................................................35
3.5 Challenges.............................................................................................................................38
3.6 Lessons learned ..........................................................................................................................38
3.7 Conclusions and recommendations...........................................................................................38
4. PROGRAM PERFORMANCE – IMPROVING SMALLHOLDER ACCESS TO STRUCTURED MARKETS
40
4.1 Overview...............................................................................................................................40
4.2 Strengthening capacity on storage ......................................................................................40
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4.3 Training of smallholder farmers in improved post-harvest technologies..........................40
4.3.1 Postharvest Management Practices...................................................................................41
4.4 Marketing of SAIOMA commodities....................................................................................44
4.4.1 Farmer participation in output markets .......................................................................44
4.4.2 Facilitating linkages to structured markets............................................................................44
4.4 Country experiences.............................................................................................................48
4.5 Challenges.............................................................................................................................52
4.6 Lessons and Recommendations...........................................................................................52
4.7 Conclusions...........................................................................................................................53
5. PROGRAM PERFORMANCE – CROSSCUTTING ACTIVITIES: STRENGTHENING FARMER
ORGANISATIONS AND GENDER ...........................................................................................................54
5.1. Capacity of smallholder farmer organizations......................................................................54
5.1.1 Establishment and registration of FOs..........................................................................54
5.1.2 FO capacity building......................................................................................................55
5.1.3 FOs and aggregation .........................................................................................................55
5.1.4 Farmer perceived benefits from SAIOMA.....................................................................59
5.2 Women and youth participation in leadership positions .....................................................59
5.3 Challenges faced ...................................................................................................................61
5.4 Conclusions on crosscutting issues.......................................................................................62
6. PROGRAM PERFORMANCE – IMPACTS AND OUTCOMES AT SMALLHOLDER FARMER LEVEL ..63
6.1. Program goal.........................................................................................................................63
6.2. Objective 1 Improved Agricultural Production .....................................................................64
6.3. Objective 2 Improved smallholder farmers’ access to markets ...........................................69
6.4 Gender Disaggregated results.....................................................................................................70
6.6 Conclusions on SAIOMA beneficiary impact...............................................................................72
7. PROGRAM MANAGEMENT ..........................................................................................................74
7.1. SAIOMA consortium approach .............................................................................................74
7.2. Program monitoring..............................................................................................................76
7.3 SAIOMA partnerships and sustainability ....................................................................................76
7.5 Recommendations................................................................................................................78
APPENDIX 1 Stakeholders consulted during the evaluation.................................................................79
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List of Tables
Table 1 SAIOMA Impact and Outcome indicators ................................................................................20
Table 2 Sampled household characteristics..........................................................................................22
Table 3 Agro-dealers trained over the life of program.........................................................................30
Table 4 Agro-dealers receiving grants over life of project....................................................................31
Table 5 Agro-dealer profiles and activities ...........................................................................................35
Table 6 Sources and accessing of inputs..............................................................................................36
Table 7 Smallholder use of agro-dealers as sources of inputs (% sample)...........................................37
Table 8: Sources of information on improved varieties .......................................................................38
Table 9 SAIOMA program farmers trained in post-harvest technologies by sex of household head (%)
..............................................................................................................................................................41
Table 10 Farmers adopting improved post-harvest technologies (%)..................................................42
Table 11 Maize grain damage at beginning and end of storage 2015..................................................43
Table 12 Grain loss at storage stage (%)...............................................................................................43
Table 13 Households marketing SAIOMA crops (%) .............................................................................44
Table 14 Farmers marketing grain through formal markets (% growers) ...........................................47
Table 15 Grain aggregation and sales at Wamunyu GAC .....................................................................56
Table 16 Aggregation by Makutano GAC (Main store) MT...................................................................57
Table 17 Prices received by Makutano GAC .........................................................................................57
Table 18 SAIOMA performance against impact indicators...................................................................63
Table 19 Distance to nearest input supplier against LOA target: SAIOMA beneficiaries (km).............65
Table 20 Awareness of improved crop varieties by smallholder farmers (%) ......................................65
Table 21 SAIOMA beneficiaries using improved technologies vs. targets (%)......................................66
Table 22 Households using improved technologies (% growers) .........................................................67
Table 23 Farmers growing SAIOMA crops (%) and Area allocated to crop (Ha)...................................68
Table 24 Mean household yields of SAIOMA crops (MT/Ha) ...............................................................68
Table 25 SAIOMA sampled beneficiary per capita expenditure versus targets (USD per day) ............69
Table 26 Per capita income and expenditure of targeted program and control households ..............69
Table 27 Mean post-harvest losses at household level for maize and pigeonpea, 2015 (%)...............70
Table 28 Gender differences in adoption of improved technologies in 2015 (% respondents)...........71
Table 29 Gender differences in adoption of improved post-harvest technologies (% sample)...........71
Table 30 Gender differences in household incomes and expenditures (units in local currency).........72
Table 31 SAIOMA Key indicators: Targets and Level of achievement at end of program 2015/16 .....73
Table 32.SAIOMA partners by country .................................................................................................74
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List of Figures
Figure 1 Actors and linkages in SAIOMA program Theory of Change...................................................25
Figure 2 Farmer groups targeted under SAIOMA .................................................................................28
Figure 3 Mr. Grevin Hamis’ Agro-dealer shop in Zomba, Malawi renovated under SAIOMA..............32
Figure 4 Farmers selling SAIOMA crops 2013 and 2015 (%).................................................................44
Figure 5 Buyers for smallholder crops for 2013 and 2015 (% farmers)................................................46
Figure 6 Mode of payment for crop purchases ....................................................................................48
Figure 7 Kenyan smallholder farmers aggregating grain ......................................................................58
Figure 8 Benefits from SAIOMA membership (% members interviewed)............................................59
Figure 9 Perceptions of women's involvement in decision-making on produce sales (% women)......60
Figure 10 Perceptions of women's involvement control over income from sales (% women)............61
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Acknowledgements
The SAIOMA Final Evaluation team led by the Natural Resources Institute, University of Greenwich,
would like to express their gratitude for the support received during the assignment from SAIOMA
staff led by Team Leader, Anthony Ngosi, and M&E Lead, Nyasha Mhosva. We would also like to thank
AGRA Director, Markets Access Program, Anne Mbaabu, and M&E Director, David Sarfo Ameyaw, and
program staff for their inputs during the evaluation Inception and Validation meetings. We
acknowledge with thanks the support of the Global Development Alliance of USAID, AGRA, Bill and
Melinda Gates Foundation and the Swedish Government for the evaluation. Finally, we would like to
thank all SAIOMA partners and stakeholders met during the course of the study for sharing their time
and knowledge for the benefit of the evaluation: farmer organisations, government officers, agro- dealers, financial organisations and smallholder farmers in Kenya, Malawi and Zambia.
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Acronyms
AC Aggregation Centre
ACE Agricultural Commodity Exchange
AD Agrodealer
AGMARK Agricultural Market Development Trust Africa
AGRA Alliance for a Green Revolution in Africa
BMGF Bill and Melinda Gates Foundation
CABE Centre for African Bio-Entrepreneurship
CPI Capacity Performance Index
FGD Focus Group Discussion
FISP Farm Input Support Programme
FO Farmer Organisation
FOSUP Farmer Organisation Support Program
FtF Feed the Future
FUM Farmers Union of Malawi
GDP Gross Domestic Product
KII Key Informant Interview
LOA Level of Achievement
LUANAR Lilongwe University of Agriculture and Natural Resources
M&E Monitoring and Evaluation
MT Metric tonne
NASFAM National Smallholder Farmers Association of Malawi
NGO Non-Governmental Organisation
NRI Natural Resources Institute, University of Greenwich
PASS Program for African Seed Systems
RUMARK Rural Market Development Trust
SAIOMA Strengthening Input and Output Markets in Africa
SGA Sorghum Growers Association
SHP Soil Health Program
SPA Sorghum Pioneer Agency
UN United Nations
USAID United States Agency for International Development
USD United States dollar
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Executive Summary
Background and objectives of the evaluation
Strengthening Agricultural Input and Output Markets in Africa program is a multi-partner initiative
working to improve inclusive agricultural sector growth in Kenya, Malawi and Zambia through a Global
Development Alliance supported by the United States Agency for International Development, the Bill
& Melinda Gates Foundation, and the Swedish Ministry of Foreign Affairs. Alliance for a Green
Revolution in Africa (AGRA) is the prime recipient of the cooperative agreement.
SAIOMA pursued its overall goal through two primary program objectives:
1. Improved Agricultural Production through strengthening agro-dealer networks to improve
smallholder farmers’ access to improved agro-inputs and appropriate agronomic practices.
2. Improved smallholder farmers access to markets through investing in market development,
storage and services and direct procurement. The focus crops for market access activities
are greengrams, pigeonpea, cowpea, groundnuts, sunflower, sorghum, cassava, and maize.
The main objective of this final evaluation was to assess the overall program performance in relation
to its objectives, and to provide input into the new strategic directions or implementation
designs/strategies of future investments. The evaluation assessed what has worked, what did not
work very well, key lessons learned and what areas should be emphasized or adjusted, in future
programming. The evaluation covers the following three components:
(i) Programmatic impacts – assessment of what outputs have been delivered, what changes
(outcomes, both intended and unintended) have occurred among the beneficiaries, relevance of
program interventions, sustainability of the achievements to-date, government policies around farm
input and output markets and their implications on the program performance in each country.
(ii) Program delivery mechanisms – review of the approaches adopted by the program to achieve
program objectives, such as models for farmer organization strengthening, agro-dealer development
and various marketing approaches employed in the target countries: how successful these models
have been, what lessons can be drawn, whether these results are likely to be sustainable.
(iii) Project management for results- evaluation of management processes; assessing their adequacy,
efficiency and effectiveness, including: program structure; staffing; grant-making processes; quality of
grants funded; level of integration and alignment with other Feed the Future and AGRA projects.
The SAIOMA program final evaluation was carried out by the Natural Resources Institute and partners
between August-November 2016. It assessed SAIOMA performance since its inception in October
2012 and covered the three target countries of Kenya, Malawi and Zambia.
The evaluation used a mixed methods approach to address the evaluation questions, with collection
and analysis of both qualitative and quantitative data. The qualitative data analysis was used primarily
to address the relevance, effectiveness and sustainability of the program and the program theory of
change. It included assessment of context of the program and partnership and collaborations during
implementation. Qualitative methods involved review and analysis of relevant documents, Key
Informant Interviews and Focus Group Discussions. Quantitative methods were used to assess
program outcomes and impact at household level and inform Key Performance Indicators. A survey of
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1600 households (57 % women) was conducted in sampled program areas in the three target countries
together with a survey of 72 agrodealers. Performance of the program against key SAIOMA program
indicators used secondary data from World Bank/UN sources and primary data from the evaluation
household survey.
Key evaluation results
Program objective 1 – Increasing smallholder agricultural production through access to improved
inputs
SAIOMA’s program implementation strategy for Improved Agricultural Production was the rapid
development of agro-dealer networks in rural input markets to deliver appropriate technology inputs
and information to smallholder farmers. Under this objective, the focus was on strengthening agro- dealer networks in targeted areas in order to improve smallholder farmers’ access to improved agro￾inputs and appropriate agronomic practices.
Key achievements under Objective 1
• Training: The program trained a total of 1,286 agro-dealers against a target of 1,310 in the
life of the program, representing 98% achievement. • Grants: Micro-grants were provided to 169 agro-dealers against a target of 93, representing
182 per cent achievement. The grants aimed at stimulating faster business growth among
trained agro-dealers. • Hub-agro-dealers: SAIOMA supported the development of 92 agro-dealer hubs against a
target of 63 hubs which represented an achievement of 146%. • Access to credit access: The program facilitated 67 agro-dealers to access credit from
commercial banks by organizing business to business (B2B) meetings. This represented an
achievement of 100% compared to none at baseline. • Demonstration plots: SAIOMA facilitated establishment 629 demonstration plots against a
target of 282 which represented an achievement of 223%. • Field days and exhibitions: 208 field days were organised against a target of 150, representing
an achievement of 139% of the initial target. • Input and extension delivery: Program-supported agro-dealers sold a total of 44,175 MT of
improved seed against the target of 24,406MT which represented an achievement of 179%
above the target. SAIOMA-supported agro-dealers recorded a total sale of 14,446 tons of
fertilizers by project-trained agro-dealers against a target 41,760 MT representing an
achievement of 35%. • Access to inputs and extension: Farmers’ access to inputs and extension in terms of distance
they travelled to reach suppliers improved: Kenya was almost achieving an average target of
3 km whereas the project-supported farmers in Malawi covered shorter distances to access
extension services, compared to farmers who did not receive support.
A key question is how to sustain agricultural input markets in remote areas with thin demand? There
is need to improve infrastructure; create demand; promote subsidised support to agro-dealers to
strengthen associations (following some success in Zambia); market franchise and social capital (trust).
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Recommendations for SAIOMA and government and policy-makers: • Training of agro-dealers should be based on needs assessments and provide fresher courses
for already trained agro-dealers and full courses for vendors or seasonal agro-dealers. The
agro-dealer training should involve government agricultural extension workers and
agribusiness advisors to build their capacity for follow-up activities beyond the program. • Grants: Provision of grants to agrodealers without matching capital, but with potential to
reach difficult to reach rural markets, should be considered. Provision of bridging capital to
buy stock for those with good business plans should also be considered for this group. • Agro-dealer hubs are not all functioning as envisaged. The Sorghum Pioneer Agency (SPA) in
Kenya is a unique case with a history of working as both as a hub-agro-dealer and a grain
aggregator. Its hub agro-dealer model involved setting agro-dealer shops in which serve as
franchises linked to agro-dealer shops are aggregation centres. SPA is involved in both forward
and backward linkages through sorghum supply contracts to EABL and buyer contracts to
sorghum farmers. SPA provides several services to contracted farmers. This complex model is
supported by many development partners including SAIOMA in through capacity building and
linkages to markets and financial institutions. These are key elements for strengthening the
hub and spoke agro-dealer model. The recommendation is to support these linkages and
provide linkages to financial markets for larger ADs.
Recommendations for policy: • There is need to link agro-dealers to extension services to provide farmers with multiple
sources of information on inputs and practices and for business services. • Linkage of agro-dealers to Farm Input Subsidy Programmes (FISP): future programs should
take on a lobbying role to involve ADs in the government subsidy programmes, where they
have sufficient capacity. There has been some success in this by Nutri-Aid and partners in
Zambia. • Agro-dealer associations have a key potential role in monitoring and supporting ADs but are
generally weak. An exception was Chibombo agro-dealer association in Zambia where
SAIOMA partners established a platform for agro-dealers and input suppliers. The platform
strengthened relationships of actors in the sector -- and especially broadened the base of
input suppliers by bringing on board new agro-dealers. Future programs should consider
support for such platforms in other countries and regions.
Program objective 2 – Improving smallholder access to structured markets
The market access objective of SAIOMA aimed at training farmers in marketing their agricultural
commodities (largely grains), linking them to markets, and building their capacity with various skills
such as leadership and governance, postharvest management practices, and business and negotiating
skills to enable them to achieve higher value returns on their farming activities. It also aimed at
improving storage structures for grain aggregation at local district/sub county level.
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Different models for linking smallholder farmer to structured markets were promoted under the
program: on-spot buyers, bulk buyers, warehouse receipt system (Malawi), and agrodealers. Farmer
organisations were supported to engage with these markets. The theory of change behind linking
smallholder farmers to formal marketsis based on a number of assumptions,such as good information
and transparency in operations and good understanding by all market players of the financing and
management arrangements.
Key achievements under Objective 2: • Total grain storage capacity increased by 22,096 m2 under SAIOMA: 118% achievement of
target. • Program-supported farmers marketed 86,998 MT of SAIOMA commodities: 110%
achievement of target. • Number of farmers trained in improved post-harvest management practices was 96,673
(63,620 women and 33,053 men): 102% achievement of the target • Improved post-harvest storage practices were adopted by 61% of SAIOMA supported farmers
in Kenya, 69% in Malawi and 66% in Zambia: 93%, 99% and 109% of respective country targets. • Post-harvest storage losses were 6.5% for pigeonpea farmers in Kenya, 13.4% for maize
farmers in Malawi and 6.3% in Zambia. This represents 167%, 149% and 317% achievement
of targets.
Eighty-seven aggregation centres have been renovated under SAIOMA building storage capacity in
rural areas. However, the number of farmers involved in aggregation under the program to date is
44,793 against a target of 60,000 (75%). The shortfall is due to reluctance by farmers to deposit their
grains as a result of: poor harvests, mistrust within farmer organisations, higher prices offered by
informal buyers, and the need for smallholders to sell and receive payment immediately after harvest
due to pressing needs such as school fees and farm inputs. Sustainability of some of the aggregation
centres is in doubt where the centres are privately rented rather than not owned by the Farmer
Organisation or the government.
Adoption of improved post-harvest management practices by smallholder farmers was found to have
increased for technologies such as drying, sorting, improved storage bags and use of storage
pesticides. A key observation is that the main post-harvest losses continue to occur in other stages of
the value chain not targeted by the project: namely in-field losses. The training models adopted were:
direct training of farmer organisation leaders and aggregation centre staff, use of extension worker
trainers, and training of lead farmers as trainers. Adoption of some post-harvest practices has
improved but not significantly compared to control farmers. Extension staff and lead farmers were
generally not well supported in their on-training of farmers which has reduced uptake of some
technologies. Training in grading has not generally improved returns as differential pricing is not
practiced in many markets.
Recommendations on improving market access
1. All of the constraints to smallholder farmers’ participation in formal output markets need
to be considered including: farmer organisation governance to improve transparency and
trust so that farmers increase aggregation, and crop insurance in event of crop failure.
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2. All aggregation centres should be owned or leased on long-term arrangements (e.g. from
government) by the participating farmer organisations (not rented from private
individuals); where this is not possible, new warehouses could be built if assessed to be
cost-efficient.
3. Training on in-field post-harvest management is needed to address the main stages at
which losses are occurring.
4. Ongoing support forsmallholder farmersin post-harvest management is needed. This can
be provided through building capacity and buy-in of local service providers. Formal
inclusion of local extension services in training e.g. through MoUs or service agreements,
rather than ad hoc contracts, would improve trainer and farmer capacity and the
sustainability of the interventions.
5. Inclusion of non-SAIOMA potential crops such as pigeon pea and rice (in Malawi) would
have improved program performance indicators. 6. A longer period of program implementation (minimum 5 years) would sustain and
translate improvements in farmer postharvest and marketing knowledge to practice and
performance.
Cross-cutting activities - Farmer Organisation Capacity Building and Women’s Leadership
SAIOMA’s direct project interventions, extending and deepening input markets and improving output
markets, were supported by two crosscutting interventions: farmer organization (FO) capacity
building and gender activities.
Key achievements under cross-cutting activities: • Improved capacity of FOs using the Capacity Performance Index (CPI): 60% of FOs have
improved their CPI during the reporting period, with 59 % improving their CPI above the 43%
target. • Level of women representation in leadership of FOs is 56%, compared to a target of 60%: 93
% achieved. • Involvement by women in household decision-making on produce sales has stayed constant
or increased for 98% of SAIOMA women beneficiaries. For decision-making on control over
income from sales it has stayed constant or increased for 95% of women. Lessons
Farmer Organisation strengthening was a critical component for the overall success of SAIOMA and to
the sustainability of program outcomes. As a cross-cutting intervention in the program, its importance
was recognised in program design. However, this component received the smallest share of budgeting
and resources and this limited the scope of its activities.
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The Capacity Performance Index tool used by the program was useful in identifying broad levels of FO
capacity, but was not effective in identifying and addressing underlying management, governance and
accountability issues. The modular approach taken to training FO leadership faced similar challenges.
In some cases SAIOMA partners were able to provide backstopping to their FOs, but coaching and
mentoring would ideally have been an ongoing principal activity. Overall CPI scores for SAIOMA
supported FOs increased slightly over the life of the programs, which is commendable, however there
is a danger that this might not be sustainable with leadership turnover.
FO capacity building was provided by partners and sub-contractors as individuals, which has left FOs
without backstopping services. Long-term agreements with partners should be promoted to ensure
coaching and mentoring is available over the medium to long-term to enable FOs to survive and grow.
The SAIOMA program implemented gender activities to ensure participation of women and youth in
leadership position in the FOs. The main activities were gender training for program staff and gender
activities to encourage women in program implementation and leadership. Recommendations on FO strengthening
1. Farmer Organisation strengthening needs to be placed at the centre of any future market
strengthening program and provided with adequate resources and support
2. Assessment and interventions to support FO should be based on a wider measure than the
CPI to capture levels of accountability and trust: to encourage more smallholder farmers to
aggregate their produce through groups.
3. Formal collaboration with local partner organisations including Ministries of Agriculture and
Trade, and Department of Cooperatives (e.g. through service agreements) will enable follow- up and sustainability of FOs beyond the program.
Program management
Program activities were delivered successfully by prime, country leads and program partners despite
some challenges arising over the course of the program. The majority of LOAs were achieved.
Key management findings:
1. The consortium concept piloted under SAIOMA is innovative, combining strengthening input
markets, output markets and farmer organisation capacity building in one program. Initially
partners implemented activities in silos, though cooperation has improved significantly over
the course of the program with management support. For consortia to work successfully there
is need for clear working modalities agreed at inception, including lines of reporting.
2. More equitable support for the different components is needed to ensure sustainability.
Strengthening smallholder farmers to aggregate and enter formal markets requires more
emphasis on the foundations of the pyramid: capacity building of Farmer Organisations. This
was given the lowest priority in resource allocation of program investments. It is
recommended that guidelines for partners on allocation by objectives are considered.
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3. After initiation of program start-up activities the program effectively operated on the ground
for only two seasons: too short to see a significant shift by risk-averse smallholder farmers to
new marketing arrangements and to embed new processes in farmer organisations. Ideally,
an input and output strengthening program would have an inception stage, minimum of 3
years full implementation, and an exit phase to ensure sustained impact.
4. Contextual factors, particularly the weather, had a major impact on harvests and thus program
outcomes. Weather insurance schemes could be considered as part of future investments.
Program impacts and outcomes at smallholder farmer level
Performance against program impact and high level outcome indicators – to which the program would
be expected to contribute - is positive for change in agricultural GDP (indicator #3), although below
the target rate of 35%. For percentage of rural households living below the poverty line, the targets
were 91% and 80% met in Kenya and Malawi respectively, with Zambia lagging at 58% (#1). Per capita
household expenditure (#15) is well below the baseline level. Reasons for non-attainment of targets
are a combination of external factors (such as agricultural sector performance and government
policies on input subsidies and commodity trade) and high target levels.
On outcome targets, performance on distance travelled by smallholders to access agro inputs has
improved over the program period, and is close to LOA targets in Zambia (96%). Targets on use of
improved input (#10) were exceeded in Malawi and Zambia (118% and 122% respectively for improved
maize varieties). In Kenya targets were only 60% and 40% met: here local varieties are also in demand
(sorghum). Gender-disaggregated data shows that farmers in female-head households also exceeded
the targets in Malawi and Kenya, but trailed in Kenya, though the difference between male- and
female-headed households was not significant. Assessment of post-harvest storage losses at
household level shows that targets were significantly exceeded for the key commodities assessed:
pigeonpea in Kenya, maize in Malawi and maize in Zambia (#18). Finally, targets on SAIOMA
beneficiary smallholder adoption of improved post-harvest storage were met in Zambia, whilst in
Kenya adoption was 93% and Malawi (99%) (for at least one practice) (#21).
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SAIOMA Key indicators: Targets and level of achievement at end of program 2015/16
Indicators Kenya Malawi Zambia
# LOA
target
LOA
Achieved
% LOA
Targets
met
LOA
target
LOA
achieved
% LOA
Targets
met
LOA
target
LOA
achieved
% LOA
Targets
met
1
Impact Indicator:
Percent of rural
householdsliving below
poverty line 45% 49% 91% 45% 57% 80% 50% 78% 64%
3 OutcomeIndicator:
Percent changein
agricultural GDP 3.5% 6% 6.3%
4 Outcome Indicator:
Average distance travelled
byfarmerstoaccess
agroinputs 3 km 3.9 km 77% 3 km 7.6 km 39% 10 km 10.4 km 96%
10 OutcomeIndicator.
Percentoftargeted
farmersusing a.improved
seeds:maize/sorghum
b. fertilizers
73
73
44%
27%
60.3%
36.9%
73
73
86%
90%
117.8%
123.3%
65
65
79%
95%
121.5%
146.2%
15
OutcomeIndicator: Per
capitaexpenditures of
targeted smallholder
farmers (proxy for income) $5 $0.92 18% $4 $0.28 7% $5 $0.33 7%
18 Outcome Indicator: Post- harvest losses (pigeonpea
/maize) percent 11 6.6 167% 20 13.4 149% 20 6.3 317%
21
Outcome Indicator: Percent
of smallholder farmers
adopting improved post- harvest storage practices 65% 61% 93% 70% 69% 99% 60% 66% 109%
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Part I: INTRODUCTION
1. Background
1.1. Introduction
The Natural Resources Institute (NRI) of the University of Greenwich, in collaboration with Lilongwe
University of Agriculture and Natural Resources (LUANAR), Centre for African Bio-Entrepreneurship
(CABE) and Muwe Associates, was commissioned by the Alliance for a Green Revolution in Africa
(AGRA) to carry out a final evaluation of the Strengthening Agricultural Input and Output Markets in
Africa (SAIOMA) program. The evaluation was carried out in the three SAIOMA program countries,
Kenya, Malawi and Zambia, between August and November 2016. The report is structured as follows. Part I, Introduction, provides background to the program and the
evaluation, evaluation objectives and questions, and the methodology used by the evaluation team.
Part II presents Results of the evaluation. Chapter 2 givesfindings on Quality and Relevance of program
design. Chapters 3-5 present results by program objective: Chapter 3: Objective 1 - Improving
smallholder agricultural production; Chapter 4: Objective 2 -Improving smallholder access to markets;
and Chapter 5: Strengthening Farmer organisations and Gender. Chapter 6 presents findings on
Program Outcomes and Impact at household level against Program performance Indicators. Chapter
7 – SAIOMA Management, gives findings on program management. Additional information is provided
in the Appendices to the report.
1.2. Background and Context
The Alliance for a Green Revolution in Africa was founded through a partnership between the
Rockefeller Foundation and the Bill and Melinda Gates Foundation with a mission of improving the
productivity and incomes of resource poor farmers in Africa.
Strengthening Agricultural Input and Output Markets in Africa program is a multi-partner initiative
working to improve inclusive agricultural sector growth in Kenya, Malawi and Zambia through a Global
Development Alliance (GDA) supported by the United States Agency for International Development
(USAID), the Bill & Melinda Gates Foundation, and the Swedish Ministry of Foreign Affairs. SAIOMA
pursued its overall goal through two primary program objectives:
Program Objective 1: Improved Agricultural Production
The implementation strategy for Improved Agricultural Production is the rapid development of agro- dealer networks in rural input markets to deliver appropriate technology inputs and information to
smallholder farmers. Under this objective, the focus was on strengthening agro-dealer networks in
targeted areas in order to improve smallholder farmers’ access to improved agro-inputs and
appropriate agronomic practices.
The theory of change is that when producers use improved agricultural inputs and employ good
agronomic practices, they increase their yields and incomes. Demand creation activities for
agricultural inputs such as field days and demonstration plots are therefore important both for the
development of agro dealer businesses, and for farmer adoption of improved inputs and practices.
SAIOMA Project Final Evaluation Report NRI
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Program Objective 2: Improved smallholder famers’ access to markets
The Program Objective 2 addresses factors that hinder farmers from marketing their produce
profitably by investing in market development, storage and services and direct procurement. The
focus crops for market access activities are green grams, pigeon pea, cow pea, groundnuts
sunflower, sorghum, cassava, and maize. The overall approach included: • Strengthening the functioning of farmer groups/organizations with emphasis on improving
their storage capacities (through post-harvest crop management, aggregation and
improvement of storage infrastructure). • Facilitating linkages to structured markets for participating farmer organizations and training
them on commodity marketing (e.g. contract negotiations) and meeting the quantity and
quality requirements of the target markets. • Once the program succeeds in promoting crop aggregation of farmers’ surplus production, it
connects the farmers or aggregating entity (e.g. FO, agro-dealer) to large commodity bulk
buyers, including food processors, animal feed manufacturers and other industries.
Cross-Cutting Program Activities
a. Farmer Organization Capacity Building
SAIOMA used Farmer Organisations (FO) as the primary entry point for technology transfer to
smallholder farmers to increase their access to input and output markets. Furthermore, this allows
the FOs to benefit from economies of scale in service provision in activities such as input procurement,
bargaining with commodity buyers, collection of market information and produce marketing.
The program was intended to engage with different types of FOs from the lower level (Clubs, Clusters,
Farmer Based Organisations or FBOs) to the intermediate (associations, commodity associations) to
the higher level (apex, federation), depending on the country or the specific sub-sector or value chain.
The program focused on strengthening FO operational efficiencies and governance structures. It
executed a gender-responsive farmer organization capacity assessment and monitoring tool, the
Capacity Performance Index (CPI).
b. Gender Inclusiveness
Women farmers are often at a disadvantage in input purchasing and produce marketing as they may
have limited knowledge of the markets and ability to negotiate in their best interests. While women
manage marketing of agricultural produce in local markets, they have often been excluded from
participation in broader marketing activities.
SAIOMA intended to support the role of women and youth in increased access to input and output
markets by including women and youth groups among participating farmer groups wherever possible.
Other strategies included the timing of program trainings when women are not busy with house
chores, implementing affirmative action for women in the provision of micro-grant to start-up agro- dealers, and a gender-responsive farmer capacity assessment and monitoring tool, the Capacity
Performance Index (CPI).
1.3. Objectives of SAIOMA final evaluation
The main objective of the final evaluation is to assess the overall program performance in relation
to its objectives, and to provide input into the new strategic directions or implementation
designs/strategies of another phase should funds be available. The evaluation assessed what has
SAIOMA Project Final Evaluation Report NRI
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worked, what did not work very well, key lessons learned and what areas should be emphasized or
adjusted, in the second phase. The evaluation covers the following three components:
(i) Programmatic impacts – assessment of what outputs have been delivered, what
changes (outcomes, both intended and unintended) have occurred among the
beneficiaries, relevance of program interventions, sustainability of the achievements to- date, government policies around farm input and output markets and their implications
on the program performance in each country.
(ii) Program delivery mechanisms – review of the approaches adopted by the program to
achieve program objectives, such as models for farmer organization strengthening, agro- dealer development and various marketing approaches employed in the target countries.
Discern how successful these models have been, what lessons can be drawn, whether
these results are likely to be sustainable.
(iii) Project management for results- evaluation of management processes; assessing their
adequacy, efficiency and effectiveness, including: program structure; staffing; grant- making processes; quality of grants funded; level of integration and alignment with
other Feed the Future and AGRA projects.
1.4 Scope of the evaluation
The evaluation assessed SAIOMA performance since its inception in October 2012 and covered
the three target countries of Kenya, Malawi and Zambia. In Kenya SAIOMA was implemented in
four counties of Eastern Kenya: Machakos (Yatta and Mwala sub-counties), Kitui (Kitui Central
and Lower Yatta sub-counties), Meru (Tigania West sub-county) and Tharaka Nithi (Tharaka North
sub-county). The focus crops were sorghum, greengrams, pigeonpea and cowpeas. In Malawi
SAIOMA was implemented in the six districts of Balaka, Machinga, Zomba, Mangochi, Mulanje
and Phalombe, focusing on maize, soya bean, groundnuts and cassava. In Zambia the program
was working in six districts of Lundazi, Chipata, Katete, Petauke (Eastern Province) and Chibombo
and Mumbwa (in Central Province), with focus crops: soybeans, groundnuts, sunflower and
maize.
SAIOMA was implemented through a consortium approach and the evaluation covered the work
by all sub-partners in each program country. An in-depth review of program investments was
conducted to determine progress towards achieving its stated goal and objectives. Table 1 shows
the impact and outcome indicators assessed under the evaluation using household survey and
secondary data. USAID-required disaggregates were also considered when collecting data for
these indicators (USAID Feed the Future monitoring manual). The evaluation also examined
commodity exchange activities in Malawi, where the approach was piloted, including successes,
challenges and lessons learned.
SAIOMA Project Final Evaluation Report NRI
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Table 1 SAIOMA Impact and Outcome indicators
Objective Sub-Objectives Indicators Measurement
Methods
Improved
Agricultural
Production
Increased women
and men smallholder
farmers’ access to
agricultural inputs
Improved agricultural
practices among
women and men
smallholder farmers
• Percent change in agricultural gross domestic
product • Percent of rural households living below the
poverty line
• Average distance travelled by farmers to
access agro-inputs • Farmer awareness levels on promoted farm
inputs in target areas
• Review of
secondary
sources of
information – Central
Banks, WB,
UNDP, etc • Household
surveys
Improved
smallholder
farmers
access to
markets
Increased adoption of
improved post- harvest management
practices by
smallholder farmers
Improved marketing
structures and
linkages for
smallholder farmers
• Per capita expenditures of targeted
smallholder households (proxy for income) • Percentage reduction in post-harvest losses • Percentage of smallholder farmers adopting
improved post-harvest storage practices
• Review of
secondary
sources of
information – Central
Banks, WB,
UNDP, etc • Household
surveys
1.5 Key Evaluation Questions
1. Quality and relevance of program design
i. What were the major changes in program design, threats and opportunities which may
have occurred since the inception of SAIOMA, and which may have had implications on
the program performance?
ii. Assess program risks and test the underlying hypotheses and assess how these were
managed.
iii. What were the program strategies and how they respond to emerging risks and
national and USAID/Feed the Future priorities in target countries?
2. Program performance
i. Assess the extent to which program outputs, outcomes and objectives were achieved
at all levels.
ii. What were the positive and negative, direct and indirect, planned and unplanned
results of the program? Discuss factors that impacted outcomes positively and
negatively that cannot reasonably be attributed to the program.
iii. How effective were the program activities?
iv. What are the strategic importance of the program achievements and how it
interfaces with the next phase of the program tenure?
v. What are the challenges, lessons learned and best practices in program
implementation?
vi. What is the potential and options for future sustainability, scalability and replicability?
3. Management issues
i. What management issues such as the overall organizational structure of SAIOMA, staff
configuration, execution modalities, and quality of grant making and management
approach, arrangements for implementing grants, capacity gaps, utilization of the
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expertize of the SAIOMA team and AGRA Program Officers from AGRA programs such
as Markets, PASS and FOSCA in technical assistance and how all this affected program
results?
4. Lessons learned
i. What key lessons have been learned from SAIOMA?
ii. What has worked well and what has not worked well?
1.6. Methodology
The evaluation used a mixed methods approach to address the evaluation questions, with collection
and analysis of both qualitative and quantitative data. The qualitative data analysis was used primarily
to address the relevance, effectiveness and sustainability of the program and the program theory of
change. It included assessment of context of the program and partnership and collaborations during
implementation. Qualitative methods involved review and analysis of relevant documents, Key Informant Interviews
and Focus Group Discussions. Program documents including proposal, quarterly and end of program
reports, AGRA program reports, plus published reports and data from UNDP, FAO and National
Statistics Offices were reviewed. In depth key informant interviews and focus group discussions were
conducted with program stakeholders: consortium partners, agro-dealers, farmer organisations and
associations, warehouse operators, Ministry of agriculture staff and commodity exchanges (Malawi). A list of Key Informants is given in Appendix 1. Quantitative methods were used to assess program outcomes and impact at household level and
inform Key Performance Indicators. A household survey and agrodealer survey were conducted in
sampled program areas in the three target countries of Kenya, Malawi and Zambia.
Sampling
A sample of 600 households per country (total 1800) households was drawn based on several
statistical assumptions as shown in equation 2. This sample included both the beneficiaries (30 %) and
control farmers (60 %).
Following Ekesa et al. (2013), our sample size is determined by = [ (1 − )]/
where n is the survey sample, t is the confidence level at 95% (standard=1.96), p is the
proportion of households who have adopted the practices advocated by SAIOMA, or have
increased their market access, which we conservatively assume to be at least 20%, and m is
the margin of error, which we set at 3%. For the agro-dealer survey, p is the proportion of
agro-dealers who stock seeds and other inputs promoted by SAIOMA, which we
conservatively estimate to be at least 95%.
The final number of households sampled was reduced by 12% to 1605 households (due to time and
resource constraints). Of these, around 57% were women. The sample comprised 1114 (69.4%)
beneficiary households and 491 (30.6%) non-beneficiary households (control group). Table 2 shows
key characteristics of sampled households by country.
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Table 2 Sampled household characteristics
Variable
Kenya Malawi Zambia
Total SAIOMA Control Total SAIOMA Control Total SAIOMA Control
Total sample (n)
(%)
508 373
(73.4)
135
(26.6)
458 332
(72.5)
126
(27.5)
639 409
(64.0)
230
(36.0)
Respondents
Female (%) 72.9 74.7 68.2 65.1 67.5 58.7 37.9 34.7 43.5
Male (%) 27.1 25.3 31.8 34.9 32.5 41.3 62.1 65.3 56.5
County/District
Machakos 125 88 37
Kitui 153 98 55
Meru 112 101 11
Tharaka Nithi 118 86 32
Balaka 113 88 25
Machinga 244 182 62
Zomba 101 62 39
Lundazi 218 153 65
Chipata 210 125 85
Chibombo 211 131 80
Source: Evaluation survey
The study adopted a multi-stage sampling procedure to select respondents. In the first stage, we
randomly select beneficiary target areas (zones, Extension Planning Areas etc). The number of
targeted areas selected depended on the population of beneficiaries; hence, we used the ‘probability
proportional to size’ approach. Using the same approach, in the second stage we randomly sampled
the households and agro-dealers from beneficiary lists provided by the program and local Ministry
officials. We also identified suitable control villages around 10-20km from the program areas with
similar characteristics to SAIOMA villages and randomly selected the control households from them.
In addition to the smallholder household survey, the agrodealer survey surveyed 72 agrodealers for
interview in the selected beneficiary target areas. In Kenya, 22 agrodealers were interviewed, in
Malawi, 23, and in Zambia, 27. Thirty-three percent were women agrodealers. Participants were
selected from lists of SAIOMA-supported agrodealers held by SAIOMA Inputs support partners.
Survey Instruments
Several instruments were developed for data collection; • A household survey questionnaire
• An agro-dealer questionnaire
• Farmer Organisation focus group discussion checklist • A key informant interview checklist
The development of the questionnaire was based on evaluation objectives outlined in the request for
proposal and outputs/outcomes contained in the program’s logical framework and a review of
program documents (SAIOMA) to understand the how the evaluation objectives fit into the broader
objectives of the SAIOMA and AGRA’s mission, policies and projects.
Once the questionnaire was reviewed and accepted the questionnaire was piloted. We selected and
trained experienced research assistants to administer the questionnaire and used the pilot as part of
SAIOMA Project Final Evaluation Report NRI
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the learning process. The pilot exercise involved a small subset of households, key informants, and
FDG groups. Modifications to the questionnaire were carried out after reviewing the experience of the
pilots. Field plan
A field plan was developed by the evaluation team with assistance from SAIOMA staff. The evaluation
team then trained all field staff involved in executing the survey.
The training modules comprised: • Introduction to the Survey. Familiarization with the program and questionnaires. • Defining roles of the enumerator and the supervisor. • Understanding the survey and survey questions – question by question explanation and
discussion. • Interviewing techniques. Tips for good interviewing. • Practice Role Playing. Practice interviewing and recording responses. • Supervision and monitoring (for supervisors only). Review responsibilities; explain expectations
regarding enumerator, supervisor, and survey manager communication. Survey quality control
will be stressed. • Household selection process (for supervisors only) – based on sampling methodology. • Practice interviews – to give interviewers and supervisors practical experience. • Interview moderation (for FGD interviewers). This provided a practical environment to practice
how to moderate a discussion. • Review of survey process (for supervisors only). Overview of possible problems, causes, solutions,
example situations and how to deal with them, schedule review. • Quality control reviews (for supervisors only). With hardcopy questionnaires, supervisors and or
Field Survey Editors reviewed all questionnaires in the evening following enumeration. Anomalies
were identified at this time and corrected by the enumerator(s). This sometimes included having
to return to the household the next day.
Data quality control
Stringent measures were put in place for data quality control before, during and after data collection.
Before data collection, we ensured that the tools to be used were effective and enumerators well
trained on how to ask questions and minimize data recording errors. During data collection, we
ensured that there is minimum and timely coverage and appropriate engagement with the
respondent. After the data collection, entry of the data was supervised to ensure that the errors of
entry were minimized. Data corrections including missing values and extreme values were addressed
during data cleaning and analysis.
Key Informant and Focus group Discussions
To complement the primary household and agro-dealer data, we conducted key informant interviews
and focus group discussions. FGDs were organized with program participants spread representatively
over the program area. In addition, we interviewed traders dealing with grains to establish the market
dynamics within which the SAIOMA operates, including operators of agricultural commodity
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exchanges (Malawi). The key informants and FGD participants were purposively selected to target
respondents with substantial knowledge and experience of the SAIOMA program. Data entry and analysis
SPSS was used for data entry and maintenance of the database. Analysis was carried out in SPSS and
STATA programs with scripts saved and stored for replication of results. Analysis included descriptive
statistics, test of means and correlations. Differences-in-differences measures were used to compare
the effect of the intervention (SAIOMA program) on the beneficiary target group versus the control
group by comparing the change in a series of outcomes over the program period (before the start and
at the end of the program).
1.7. Challenges
A number of challenges were faced during the evaluation. The first set were related to the
baseline. The baseline household surveys conducted in 2013 in each country collected data on
the program indicators. However, the sampling frame appears to not have reflected the general
smallholder population as data on key variables in some cases (such as input use) seems
inaccurate. The evaluation team therefore used farmer recall for data from 2013 which was
triangulated where possible against the baseline findings.
A second challenge was the timing of the evaluation which was conducted in the final year of
the program before the end of the 2016 marketing season. This meant that data collected was
mainly on performance during the previous two years of the program. Field activities mainly
started in 2014 so the data captures only 1-2 cropping years. These experienced drought which
resulted in below average yields in all three countries.
Time and resource limitations were a third challenge which meant that the sample size had to
be reduced by 12 %. There was a particular challenge to find households to interview in areas
where the program had not had many activities. Nevertheless the sampling frame and results
remain robust.
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PART II – RESULTS
2. PROGRAM DESIGN AND RELEVANCE
2.1. Quality and relevance of program design
The program design effectively brought together three core components into the program, illustrated
in Figure 1 (constructed from program documents and discussions with program staff):
1. Improving input markets: increased supply of improved inputs from agrodealers (AD);
agrodealer hubs and facilitation of linkages between agrodealers and famer organisations
(FO); increased use of improved inputs by smallholder farmers (SH) resulting in increased
production. 2. Improving output markets: increased smallholder engagement with (structured) markets;
strengthening associations; training on post-harvest handling and engaging with markets;
improving storage facilities – structures and management; promoting aggregation through
farmer organisations; linking farmers with structured trade systems – commodity exchanges
(Malawi), warehouse receipt systems; top-of-supply chain buyers (food processors, animal
feed manufacturers etc.); promotion of access to finance. 3. Farmer Organisation Capacity Building: formalisation of farmer organisations (official
registration, establishing formal structures); capacity building of FOs in governance and
operational management.
Figure 1 Actors and linkages in SAIOMA program Theory of Change
SH
SH SH
SH
On-spot buyer
SH
Warehouse
SH
AD
FO
SAIOMA Project Final Evaluation Report NRI
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Each of the components is critical to achieving the goals of the program. Overall program performance
depended on efficient functioning of the separate components of the program together with an
efficient coordinating arrangement. The performance of the different and joint components are
discussed in subsequent chapters. Here, we note that the cross-cutting activities – Farmer
Organisation capacity building and Gender – were also key to the success of the whole program. Where capacity of farmer organisations was already strong or strengthened by the program, in
combination with favourable market opportunities, the program was able to achieve its aim of
improving smallholder farmers’ access to structured markets (see case study: Makutano Grain
Aggregation Centre, Tharaka North). In other cases, where not all components were fully functioning, combined with limited market opportunities, farmers were either unable or unwilling to sell through
structured markets (see case study: Machakos Wamunyu Aggregation Centre). As a result, overall
SAIOMA program targets for marketing were met in terms of quantity of grain aggregated, but below
target in terms of numbers of smallholders selling through structured markets (44,793 farmers
involved in produce aggregation against a target of 60,000: 75 % achieved vs. target). The approach of combining support to smallholder farmers through inputs, outputs and farmer
organisation capacity building activities is novel within AGRA and the experience of SAIOMA can
inform future programming.
2.2. Relevance of countries
Three countries were selected for SAIOMA based on four criteria (SAIOMA Program Document:17) • The critical need to improve agricultural incomes and address under‐nutrition in these countries; • The complementary role that the SAIOMA investments will have with the bilateral USAID Feed
the Future investmentstrategies; • AGRA’s experience in and knowledge of these countries; • The fact that these three countries represent diverse development stages and constraints so that
the lessons learned from the SAIOMA investments will have broad applicability to the varied
development needs of Africa.
These a priori criteria were met by the three SAIOMA countries, Kenya, Malawi and Zambia. All are
countries where Feed the Future and AGRA have extensive experience. This enabled SAIOMA to
build on existing relationships and partnerships (e.g. consortium leads) and investments (e.g. PASS,
Market Access and Agrodealer Programs) which contributed to the successful implementation of
the program within a short time period. The three selected countries represent a diversity of
development conditions and constraints so that lessons from SAIOMA can be applied to other FTF
and AGRA programmes within the region and beyond (though consideration of national and local
agroecological, social, economic, political and institutional contexts will also be critical).
2.3. Relevance of commodities
The selection of commodities for inclusion in SAIOMA - sorghum, greengram, pigeonpea and cowpea
in Kenya; maize, soya bean, groundnut and cassava in Malawi; and soybean, groundnut, sunflower
and maize in Zambia – was primarily on the basis of Feed the Future priority crops, which had
previously been agreed upon with national stakeholders.
In terms of individual national priorities for cereals, maize is a staple and priority food security crop in
Kenya and Zambia and sorghum, to a lesser extent in Kenya, particularly in the program Arid and Semi-
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Arid Land locations. For legumes and oilseeds,soya, groundnut and sunflower are emerging cash crops
in Malawi and Zambia and relevant to national priorities. The choice of cassava was not favoured by
program stakeholders in Malawi (inserted by IITA a previous consortium member) due to its specific
production and marketing characteristics. The Malawi programme adapted by linking up with a BMGF- supported project C:AVA to supply planting materials and link to markets (although there may be
sustainability issues beyond the life of the C:AVA project for cuttings).
In a few cases, the choice of commodities was not well matched to the agroecologies of SAIOMA
program areas. In Malawi for example, groundnuts and soya are not well suited to some of the
targeted Extension Planning Areas (EPA) of Balaka and Mangochi districts. Maize, whilst being the
major food crop in Malawi and Zambia, is generally not drought tolerant and was badly affected by
drought during two of three program seasons.
Other crops were preferred by smallholder farmers and markets in Malawi over SAIOMA commodities:
particularly rice (Zomba and Machinga) and pigeonpea. The quantities of these commodities
aggregated by Farmer Organisations – in program-supported storage facilities - were considerably
higher than for the SAIOMA crops: these are considered as unintended benefits of SAIOMA
investments and are documented in the Appendix.
2.4. SAIOMA target group
The main target groups for SAIOMA are not explicitly identified in the Program document. However,
following AGRA models, the main target group can be identified as market-ready smallholders (Figure
2: Participation pyramid). Commercial smallholders are also targeted indirectly as part of the
aggregation process. Vulnerable but viable smallholders with limited capital and highly vulnerable
smallholders, such as households headed by women, elderly people, children and people with
disabilities, with limited capacity to generate market surplus, are not explicitly targeted but some of
the project activities may spillover to bring benefits, particularly where they are able to join groups. Value chain actors and service providers, including agrodealers and farmer organisation officials, are
also targeted under the program. The rationale behind the choice of target groups is related to expectations over the ability of the
program to reach these smallholders and make a difference. For vulnerable but viable smallholders
the assumption was that that if they were organised into groups, provided with training and advice,
facilitated access to inputs and markets, they could transform their production and livelihoods. For
market-ready smallholders, the observation is that they are already using some improved inputs and
market some of their produce, so the aim would be to increase rates of commercialisation.
SAIOMA Project Final Evaluation Report NRI
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Figure 2 Farmer groups targeted under SAIOMA
Adapted from Investing in Soils, AGRA 2012
Gender
Women farmers are often at a disadvantage in input purchasing and produce marketing as they may
have limited knowledge of the markets and ability to negotiate in their best interests. In some cases
women may manage marketing of agricultural produce in local markets, but they have often been
excluded from participation in broader marketing activities. The program planned a number of
initiatives to support the role of women in increased access to input and output markets, including
(SAIOMA Program document): • Emphasis on the need for gender analysis and activities in requests for grant proposals. • Participation of gender specialists in technical review of all grants proposals. • Inclusion of gender analysis in implementationplanning. • Ensure that all training activities are structured to include both women and men. An example of
the importance of this approach was highlighted in the AGRA supported NutriAID activity in
Zambia, which found that men attended ADP training despite the fact that their wives usually
managed their small stores. The problem was the timing and location of the training and the fact
that the women could not to leave their families and also were often illiterate. This was resolved
by shifting to use of on the spot training in local languages. • Strengthen women’s farmer groups for bulk input purchasing and aggregated producesales
oviders
SAIOMA
alue
oviders
SAIOMA Project Final Evaluation Report NRI
29
using a cascading approach in which larger, more experienced farmer organizations will train
smaller ones. Activities were focused on training that strengthens their skills to access local,
national and even regional markets (including knowledge of trading regulations,
understanding of grades and standards, understanding consumer needs and how to meet
them) and linking to market information systems.
The program set gender-disaggregated targets to reach women smallholder farmers, agrodealers and
farmer organisation leaders. The impact of SAIOMA on women’s knowledge, practices, production
and livelihoods is assessed from the evaluation household survey (Chapter 6). This shows that, overall,
no significant differences were found between key outcomes for men and women farmers surveyed,
indicating that program activities (combined with other contextual factors and activities) have not had
a differential impact.
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3 PROGRAM PERFORMANCE – INCREASING SMALLHOLDER
AGRICULTURAL PRODUCTION THROUGH ACCESS TO IMPROVED
INPUTS
3.1 Overview
SAIOMA’s program implementation strategy for Improved Agricultural Production was the rapid
development of agro-dealer networks in rural input markets to deliver appropriate technology inputs
and information to smallholder farmers. Under this objective, the focus was on strengthening agro- dealer networks in targeted areas in order to improve smallholder farmers’ access to improved agro￾inputs and appropriate agronomic practices.
The program used a theory of change (ToC) that links producers’ increased yields and incomes to their
use of improved agricultural inputs and good agronomic practices. Following this ToC, SAIOMA
implemented a number of demand-creation activities for agricultural inputs such as demonstration
plots, field days and exhbitions geared towards the development of agro dealer businesses, and
farmer access and adoption of improved inputs and practices.
This chapter highlights findings and achievements against two sub-objectives namely, i) agro-dealer￾led input delivery, and ii) improved agronomic practices (demand-creation), challenges, lessons
learned, conclusions and recommendations.
3.2 Agro-dealer-led input delivery
The components of agro-dealer capacity building for input delivery include: training, grant giving,
supporting hub-agro-dealers and facilitating their access to credit from commercial banks. Although
not initially a component of this objective, the program encouraged agro-dealers to form agro-dealer
associations (final year of program).
Training
SAIOMA program aimed to train agro-dealers in business management skills to increase their incomes
through input-output marketing and sales as well as improved management of their business relations,
records and clients. The program also trained agro-dealers on good agricultural practices including soil
health, safe product handling and recommended application of agro-inputs. Table 3 shows that the
trained 1,286 agro-dealers were trained in Kenya against a target of 1,310 in the life of the program,
representing 98% achievement.
Table 3 Agro-dealers trained over the life of program
Country Male ADs trained Female ADs trained Total ADs
trained
Kenya 241 233 474
Malawi 249 60 309
Zambia 353 150 503
Total 843 443 1, 286
Source: SAOIMA Project Final Report, November, 2016
In Kenya SAIOMA project trained a total of 474 (241 Male, 233 Female) in five topics against a target
of 400 agro-dealers representing 119% achievement.
SAIOMA Project Final Evaluation Report NRI
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During Focus Group Discussions (FGDs) with agro-dealers in four counties and key informant
interviews (KIIs) with AGMARK Training Director M&E Officer, it was found that start-up agro-dealers
were required to go through all training topics, while already trained agro-dealers selected topics of
interest. However, some sent their untrained spouses or employees to the training. In the first phase
of training, only half of agro-dealers turned up. The subsequent trainings were well attended after
agro-dealers learnt of benefits of the training – particularly certification which would earn them
recognition by financial institutions and government programs.
In Malawi, the project trained 309 agro-dealers (249 Male and 60 Female) on the five topics. As in
Kenya, agro-dealers were registered and certified by the Pesticide Control Board. This legal recognition
strengthened their linkage to input suppliers while the acquired business skills enabled them to
identify business opportunities in remote areas and provide innovative service package including
setting up of seasonal shops.
In Zambia, the project trained 503 agro-dealers against target of 450 representing 112 % achievement.
The licensing of agro-dealers participating in the government subsidy electronic voucher scheme by
Zambia Environmental Management Agency (ZEMA) to trade in crop protection products triggered
another wave of demand for training activities. FGDs and KIIs confirmed that many agro dealers do
have the capacity to pay for demand driven trainings which they consider important for their business.
Overall, training enabled start-up agro-dealers to receive certification to qualify for SAIOMA grants
while existing agro-dealers received both refresher training and advanced business training. Grants
The SAIOMA grants were used for renovating agro-dealers shops - including improving interior
ventilation, business branding, and providing shelves. Grants were available only to those agro-dealers
who had received business skills training and were announced to prospective beneficiaries during the
various business management training sessions. Table 4 shows that the project administered micro- grants to 169 agro-dealers from a target of 93 representing 182 per cent achievement. The grants
aimed at stimulating faster business growth among trained agro-dealers.
Table 4 Agro-dealers receiving grants over life of project
Country Target no.
grants
Grants
administered
Level of
Achievement
Kenya 45 40 89%
Malawi 28 28 100%
Zambia 20 101 505%
Total 93 169 182%
Source: SAOIMA Project Final Report, November, 2016
In Kenya, the project provided micro-grants to 40 agro-dealers against a target of 45 grants
representing an achievement of 89 per cent.
The Evaluators (through KII with AGMARK project staff and agrodealers) found that AGMARK
negotiated for support to agro-dealer start-ups to use the grant of up to US$ 1,500 for infrastructure
only (renovation of premises, painting, window for aeration, burglar-proof door, shelves, pallets,
SAIOMA Project Final Evaluation Report NRI
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weighing scales, cash box, table, chair, and counter). The supported agro-dealer’s contribution was in
the form of paying rent, license fees, stocking the shop, and paying employees. This was aimed at
ensuring sustainability of the businesses.
In Malawi 28 grants were administered to renovate: an achievement of 100%. Each agro dealer
recipient received a micro grant averaging USD700. Of the sampled 24 agro dealers 11 agro dealers
had their shops renovated in this arrangement. One beneficiary was Grevin Hamis an agro dealer in
Zomba who had his shop painted; floor, shelves and counter constructed with the grant (Figure 3).
Figure 3 Mr. Grevin Hamis’ Agro-dealer shop in Zomba, Malawi renovated under SAIOMA
In Zambia, partners provided micro grants to 101 start-up agro-dealers from a target of 10 agro- dealers. As a result, the project reduced the amount of the grants to each grantee, which in turn
required the agro-dealers to put in more of their own investments. The evaluators found that start- up agro-dealers were also linked to input suppliers.
Hub-agro-dealers
SAIOMA identified existing agro-dealers with growth potential and supported the development of
agro-dealer hubs to strengthen links with seed suppliers who in turn would advance small amounts of
inputs on consignment basis to start-up agro-dealer retailers. The support included training in output
marketing in order for them to participate in crop aggregation. The project supported the development
of 92 agro-dealer hubs against a target of 63 hubs which represented an achievement of 146%. The
support to the agro-dealers hubs included training in various modules (viz. agro-dealer business
growth strategies, agro-dealer retail pricing strategies, business planning for agro-dealers, customer
service, advanced financial management, retail store management and strategic planning for hub agro- dealers). Some hub agro-dealers were aggregating crops and establishing forward linkages with
commodity buyers for output crop marketing (see below).
In Kenya, the program developed 12 agro-dealer hubs. The Sorghum Pioneer Agencies (SPA) is one of
the successful hubs. SPA works as a hub-agro-dealer hub and as a grain aggregator. It has 15 agro- dealer shops in Tharaka Nithi County which serve as franchises (see Box 3.1). It employs 12 staff. SPA
has 41 aggregation centres, with the main store at Mukothima – due to high demand by farmers to
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also to ease transportation to the buyers or main store. SPA provides a range of farmer support
services: ploughing, threshing and winnowing, and bagging and labour, input and service credit –seed,
ploughing, guaranteeing credit, transport, etc. According to an interview with the SPA owner, Beatrice
Nkatha, ‘’Before SAIOMA, farmers had very limited access to tractors for ploughing and threshers.
Also, through a SAIOMA grant, SPA has brought farmers’ to access this service closer to them --- sometimes at credit. SAIOMA introduced two mobile threshers per group which have eased labour
burden and encouraged farmers to plant more sorghum’’.
Box 3.1: : About Sorghum Pioneer Agencies
Sorghum Pioneer Agencies (SPA), owned by Ms Beatrice Nkatha, was registered in 2009. SPA was
contracted by East African Breweries Limited (EABL) in 2010 – and was initially linked to 400 farmers:
it is now working with 14,000 farmers. SPA is the main supplier of sorghum to EABL. Its supplies rose
from 1,450 MT in 1212 MT to 3,500 MT in 2016. Since 2014, farmers have been demanding contracts
with SPA forsorghum supply: in 2015 SPA signed 47 contracts with groups. Each group was to supply
on average 30 tonnes: most groups were able to supply above 30 tonnes after SAIOMA linked
farmers to Equity Bank to support production. SAIOMA also linked SPA to ROOT Capital who financed
the business as an agent of EABL – to support spot payments to farmers. SPA also serves as a grain
aggregator.
In Malawi, the program supported the development of 24 agro-dealer hubs. However, the evaluators
found that some hub agro dealers were essentially agro dealers with contracts with seed companies
under the Farm Input Supply program (FISP): during seasonal sales they supply some of their
contracted seed to fellow agro dealers to help them sell the stock quickly. None of hub agro-dealers
was selling both wholesale and retail products at the time of evaluation. The hub-spoke agro-dealer
arrangement contributed to reducing distances travelled by agro dealers to order their products.
In Zambia, the program supported the development of 56 hub agro-dealers. The program encouraged
agro-dealers to operate as aggregators. Based on a key informant interview with SeedCo, the company
reported that its market share had increased by 12% due to the SAIOMA. The project had also brought
healthy competition to input suppliers in terms of quality and pricing. The number of agro-dealers
defaulting on consignment credits and delaying payment has reduced.
Credit access
SAIOMA facilitated agro-dealers to access credit from banks by organizing business to business (B2B)
meetings: 67 agro-dealers to access loans from commercial lenders.
In Kenya, through an interview with AGMARk, evaluators found that the project increased access to
business credit by agro-dealers – with 55 agro-dealers accessing credit from local banks compared to
none at baseline. This achievement was attributed to the favorable environment in Kenya in terms of
existing interest rates that are reasonable. In addition, some banks (including Barclays Bank, Kenya
Commercial Bank and Equity Bank) have loan products targeting SMEs such as agro-dealers. In Malawi,
RUMARK investigated options of linking agro-dealers to commercial banks. However, the interest rates
offered were at commercial levels (35-40 percent) and it therefore concluded there was no business
case for linking agro-dealers to commercial credit.
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Agro-dealer Associations
Although not originally an activity of SAIOMA, this issue of agrodealer associations came up repeatedly
during FGDs and KIIs with agro-dealers and consortium partners. SAIOMA encouraged agro-dealers to
form associations after training to give agro-dealers a voice for negotiating with governments and also
help agro-dealers to police themselves and prevent unscrupulous traders from damaging genuine
businesses.
In Kenya, three associations were formed at County level – one each in Kitui, Meru and Tharaka Nithi;
Machakos County had an existing agro-dealer association. The program provided support in the form
of rent for some AD Associations.
In Zambia, SAIOMA partner Nutri-Aid facilitated the establishment of Chibombo agro-dealer
association as a platform for agro-dealers and input suppliers. It strengthened relationships of actors
in the sector – in particular, broadening the base of input suppliers by bringing on board new agro- dealers exposed farmers and agro-dealers to large input suppliers and potential produce buyers.
3.3 Improved agronomic practices (demand-creation)
The demand-creation activities for agricultural inputs included demonstration plots, field days and
exhbitions geared towards farmer access and adoption of improved inputs and practices.
Demonstration plots aimed to provide an important platform for smallholder farmers to learn
agronomic practices with specific focus on correct application and utilization of agro-inputs such as
seeds and fertilizers. These activities also provided good avenues for driving business to the agro- dealer shops.
SAIOMA project established 629 demonstration plots against a target of 282 which represented an
achievement of 223%. Demonstration plots were set up in collaboration with farm input supply
companies, Ministry of Agriculture, agro-dealers and FBO. The engagement of input companies and
agro-dealers to set up demos to a large extent increased the number of demos that were set up.
The project set up 125 demonstrations sites in Kenya; 121 and 383 demonstration plots were also
established in Malawi and Zambia, respectively. Project partners were commited to increasing farmer
reach by establishing demonstration plots and partnered with private sector companies who were
willing to support demos in areas where SAIOMA had organized farmers.
The purpose of Field days and exhibitions was to improve farmer’s knowledge on use of improved
agricultural inputs, technologies and agricultural management practises to improve on their farm
productivity and incomes. The project organized 208 field days against a target of 150, representing
an achievement of 139% of the initial target in Kenya, Malawi and Zambia.
In Kenya under AGMARK, the program supported 45 field days and exhibitions with 10,551 farmers
attending. Demos and field days were seen as effective by AGMARK key informants through being
practical, while exhibitions were effective through bringing many stakeholders together. Agro-dealers participated in field days and input fairs to promote use of improved inputs. These
demand activities provided opportunities for sharing ideas and as a source of markets for inputs and
commodities. In some cases, government extension staff and input suppliers also benefited from agro- dealer training.
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3.4 Agro-dealer performance
Agro-dealer profile and activities
Table 5 shows the profile of agro-dealership since 2013 in Kenya and Zambia from a survey of 72
agrodealers conducted under the evaluation. In Kenya, about 60% of the agro-dealers interviewed set
up their business in 2013; with about 77% selling fertilizer and 73% selling improved seeds. Among
those who set up businesses in 2013, about 87% have already obtained business licenses. In addition
to selling farm inputs, half of agro-dealers buy maize and green grams with the intention to resell later
when price rises. About 65% of agro-dealers who set up their businesses in 2013 became members of
agro-dealer associations.
Table 5 Agro-dealer profiles and activities
Variable Kenya Malawi Zambia
Change in agro-dealership since 2013 (% sample) • Started agro-dealer business 60.0 43.5 51.9
• Started selling fertilizer 77.3 26.1 37.0
• Started selling improved seeds 73.9 43.5 63.0
Started buying grain since 2013 (% sample) • Sorghum 16.0
• green grams 32.0
• Maize 36.0 30.4 29.6
• Cowpeas 16.0
• soya beans 4.3 22.2
• Groundnuts 8.7 12.1
• Sunflower 14.8
• Cassava 4.3
Other agro-dealer characteristics (% sample) • Buy grains from farmers 50.0 8.7 63.0
• Member of agro-dealer association 65.2 8.7 40.7
• Joined agro-dealer association since 2013 100 21.7 44.6
• Business licensed 87.5 47.8 100
Source: SAIOMA Evaluation Agro-dealer survey (2016)
In Malawi, about 43% of the agro-dealers interviewed set up their business in 2013. Of these, 26%
started selling improved seeds while 43% stocked fertilizer. About half (47%) were licensed with 30%
buying and reselling maize. Less than 22 percent of agro-dealers were members of agro-dealer
associations.
In Zambia, about 51% of the agro-dealers interviewed set up their business in 2013 and all have
obtained business licenses. About 63% of the agro-dealers started with selling improved seed with
only 37% selling fertilizer. Apart from selling farm inputs, 63% of these agro-dealers also buy maize
from farmers to resell later when prices appreciate. About 44% are members of agro-dealer
associations.
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Input and extension delivery
SAIOMA-supported agro-dealers sold a total of 44,175 MT of improved seed against the target of
24,406MT which represented an achievement of 179% against Level of Achievement target. This was
attributed to the impact of demand creation activities (such as demonstration plots, field days, input
fairs and linkages with farmer organizations) on agro-dealer sales of agro-inputs. Agro-dealers also
managed to get input loans which helped them have adequate stock.
SAIOMA-supported agro-dealers recorded total sales of 14,446 MT of fertilizers by project-trained
agro-dealers against a target 41,760 MT representing an achievement of 35 per cent. This below target
achievement was attributed to the fact that most farmers did not use fertilizers on SAIOMA-supported
crops such as groundnuts, sorghum, pigeon pea, sunflower and green grams, Also, selling of fertilizers
among start-up agro dealers was a challenge because many agrodealers did not have enough capital
to procure fertilizers.
Findings from the Evaluation household survey show that SAIOMA increased the number and spread
of agro-dealers – reducing distances travelled by farmers to access improved seeds and fertilizers.
Table 6 shows farmers’ access to inputs and extension in terms of distance they travelled to reach
suppliers and extent to which they bought inputs from suppliers. Kenya is close to reaching the
SAIOMA average target of 3km. Overall, there was little difference in distance to input supplier
between SAIOMA farmers and control farmers. One factor may be the location of control farmers and
the spillover effects of the SAIOMA investment in agro-dealers. Another reason may be the seasonality
of many agro-dealers: they only locate in rural areas during the rainy season and are not available at
other times of the year (for example, during irrigated farming activities). The majority of SAIOMA
beneficiary farmers made use of the input suppliers: 87.7 percent to access seeds and 71.7 percent
for fertiliser.
Table 6 Sources and accessing of inputs
Variable Kenya Malawi Zambia
SAIOMA Control SAIOMA Control SAIOMA Control
Distance to input supplier (Km)
Seed 3.9 3.9 7.6 6.7 10.4 9.3
Fertilizer 4.8 4.2 8.5 7.5 13.6 11.3
Agrochemical 4.1 4.0 7.9 7.6 13.5 11.3
Extension service 6.3 5.9 6.1*** 4.2 7.0 6.8
Use of input supplier (% sample)
Seed 87.7 84.9 98.5 100 84.5 82.5
Fertilizer 71.7 73.0 99.1 100 85.2 83.4
Agrochemical 91.6 92.9 96.3 99.2 73.1 67.8
Extension service 68.9** 56.8 97.8** 94.2 59.4 62.4
**, ***: difference between SAIOMA and control farmers is significant at 5% and 10% respectively
Source: Evaluation household survey (2016)
In Malawi, SAIOMA-supported farmers covered shorter distances (by about 2 km) to access extension
services, compared to farmers who did not receive support. There was also more use of extension
service by the SAIOMA-supported farmers. In Zambia, the distance covered by farmers supported by
SAIOMA was almost the same as that covered by farmers who were not supported. There was no
SAIOMA Project Final Evaluation Report NRI
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significant difference in the use of services provided by seed, fertilizer, agrochemical suppliers and
extension service provider between the two groups.
Table 7 shows smallholder farmers’ use of agro-dealers to source inputs at the before the start of the
program and in 2015. In Kenya, there was an increase in use of agro-dealers by both SAIOMA and
control farmers for all input types between 2013 and 2015. In Malawi, there was an increase by
SAIOMA beneficiaries in use of agro-dealers as a source of seed between 2013 and 2015 which was
significantly higher than the control group. In Zambia, SAIOMA beneficiaries saw a significantly greater
increase their choice of agro-dealer as a source of agro-chemicals compared to the group. Farmers in
Malawi and Zambia were slightly less likely to buy fertiliser from agrodealers in 2015 but this was not
found to be significant and may be related to the decline in numbers of Farm Input Subsidy
beneficiaries.
Table 7 Smallholder use of agro-dealers as sources of inputs (% sample)
Country and input 2015 2013 Difference in
SAIOMA Control SAIOMA Control differences
Kenya
Seeds 53.9 45.9 37.3 32.6 3.3
Fertilizer 25.5 30.4 22.0 21.5 -5.4
Agrochemicals 81.8 85.9 61.7 63.0 -2.8
Malawi
Seeds 66.6*** 45.2 48.8** 38.9 11.5
Fertilizer 34.3 24.6 35.2 30.2 4.7
Agrochemicals 42.5 37.3 36.1** 26.2 -4.7
Zambia
Seeds 46.2 50.0 26.9 27.0 -3.7
Fertilizer 17.8*** 27.0 18.6** 24.8 -3.0
Agrochemicals 10.0*** 3.5 5.6*** 0.9 1.8
**, ***: difference between SAIOMA and control farmers is significant at 5% and 10% respectively
Source: Farmer Survey (2016)
Agro-dealers as sources of information
Findings on new adopters’ (since the start of SAIOMA) sources of information on improved inputs
shows that in Kenya, new growers of improved sorghum and greengram varieties were more likely to
receive information through farmer organisations (35% and 43%) and training (27% and 33%) than
through field days and demonstrations (Table 8). Similarly in Malawi, 42% of the farmers received
information on improved varieties through farmer’s organizations, although demonstration plots
were also reported to reach 44% of new growers. In Zambia, very few farmers had taken up new
varieties since 2013 (only 2.7 percent of the sample). Here agro-dealers and farm input companies
play a role in disseminating information on new varieties. Overall, farmer organisations and training
are the most important sources of information for farmers on improved seed varieties. Field days and
demos offer opportunities were not important as sources for new information except demos for
maize.
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Table 8: Sources of information on improved varieties
Country/crop Kenya Malawi
(Maize)
Zambia
Sorghum Greengram (Maize)
New growers of improved varieties (% sample) 8.5 11.8 19.4 2.7
Source of variety information (% new growers)
SAIOMA/farmer organization 34.7 43.5 42.0 12.8
Agro-dealers/input companies 4.0 7.3 7.6 21.8
How farmer learnt of variety (% new growers)
Through demo 4.0 7.2 44.3 16.5
Through field days 6.5 5.1 2.4 9.8
Through training 27.4 33.3 4.2 3.8
Source: Household survey (2016)
3.5 Challenges • Training: Initially Training for agrodealers was only provided for existing agrodealers but
start-up agrodealers were also brought into the program. The training sessions were
found to be useful to agrodealers but many still lack capacity in the practice of managing
a business. Backstopping for agrodealers is a challenge. The program supports coaching
of start-up agrodealers by mature ADs. Agrodealer associations, Ministries of Agriculture
Agribusiness officers, Ministries of Trade, and Department of Cooperatives have potential
roles in providing ongoing support for rural agrodealers. • Capital: The program grant was for rehabilitation not for stock but the majority of small
agro-dealers lack capacity to buy or hold stock – and could not enter the market after
receiving training. Similarly, hub agrodealers lacked capital to offer wholesale prices. • Climate issues: Climate issues – in one year, there was near total crop failure which
affected program activities such as demos and grain aggregation
• Accessing data: Difficulty in accessing agro-dealer data on sales, profitability etc. make it
challenging to evaluate program performance. 3.6 Lessons learned
• Business coaching is needed to provide agribusiness advisory services
• Hub agro-dealer franchise models may be more workable; with contracts, personal contacts. • Policy lessons require bringing together training and certifying bodies for agro-dealers
• A systems of ongoing support involving established agrodealers, Ministries of Agriculture,
Trade and Cooperatives needs to be established to provide capacity building of agro-dealers, coordination of training, monitoring, backstopping. 3.7 Conclusions and recommendations
How to sustain input markets in remote areas with thin demand? In response to this question, there
is need to improve infrastructure; create demand; promote subsidised support to agro-dealers to
strengthen associations (following some success in Zambia); market franchise and social capital (trust).
The following recommendations can be discerned for SAIOMA and government and policy-makers:
SAIOMA Project Final Evaluation Report NRI
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Recommendations for SAIOMA: • Training of agro-dealers needs to go beyond training courses to tailored capacity building and
coaching. Ongoing support based on needs assessment and involving established agrodealers,
Ministries of Agriculture, Trade and Cooperatives needs to be established to provide capacity
building of agro-dealers, coordination of training, monitoring, backstopping
• Grants: Provision of grants to agrodealers without matching capital, but with potential to
reach difficult to reach rural markets, should be considered. Provision of bridging capital to
buy stock for those with good business plans should also be considered for this group. • Agro-dealer hubs are not all functioning as envisaged. The Sorghum Pioneer Agency (SPA) in
Kenya is a unique case with a history of working as both as a hub-agro-dealer and a grain
aggregator. Its hub agro-dealer model involved setting agro-dealer shops in which serve as
franchises linked to agro-dealer shops are aggregation centres. SPA is involved in both forward
and backward linkages through sorghum supply contracts to EABL and buyer contracts to
sorghum farmers. SPA provides several services to contracted farmers. This complex model is
supported by many development partners including SAIOMA in through capacity building and
linkages to markets and financial institutions. These are key elements for strengthening the
hub and spoke agro-dealer model. The recommendation is to support these linkages and
provide linkages to financial markets for larger ADs.
Recommendations for policy: • There is need to link agro-dealers to extension services to provide farmers with multiple
sources of information on inputs and practices and for business services. • Linkage of agro-dealers to Farm Input Subsidy Programmes (FISP): future programs should
take on a lobbying role to involve ADs in the government subsidy programmes, where they
have sufficient capacity. There has been some success in this by Nutri-Aid and partners in
Zambia. • Agro-dealer associations have a key potential role in monitoring and supporting ADs but are
generally weak. An exception was Chibombo agro-dealer association in Zambia where
SAIOMA partners established a platform for agro-dealers and input suppliers. The platform
strengthened relationships of actors in the sector -- and especially broadened the base of
input suppliers by bringing on board new agro-dealers. Future programs should consider
support for such platforms in other countries and regions.
SAIOMA Project Final Evaluation Report NRI
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4. PROGRAM PERFORMANCE – IMPROVING SMALLHOLDER
ACCESS TO STRUCTURED MARKETS
4.1 Overview
The market access objective of SAIOMA aimed at training farmers in marketing their agricultural
commodities (largely grains), linking them to markets, and building their capacity with various skills
such as leadership and governance, postharvest management practices, and business and negotiating
skills to enable them to achieve higher value returns on their farming activities. It also aimed at
improving storage structures for grain aggregation at local district/sub county level.
For this objective, the following were the main program components: • Strengthening capacity on storage
• Training in post-harvest management practices at farm, warehouse level. • Supporting crop aggregation
• Facilitating linkages to structured markets
4.2 Strengthening capacity on storage
Under the project, 87 storage facilitated were rehabilitated: 30 in Kenya, 33 in Malawi and 24 in
Zambia. This compares with a target of 96 improved stores: 91 % Level of Achievement vs. Target. The
shortfall was due to insufficient funding to develop the remaining stores.
Rather than embarking on construction of new facilities, the program undertook rehabilitation of
existing warehouses to enhance postharvest storage. This was a logical approach where there were
existing stores owned by the groups or loaned to them by local government bodies. These improved
structures served as aggregation centres and provided an opportunity for smallholder farmers to have
better market access as the structures guaranteed improved storage and served as avenues for
negotiated bulk selling. However, in a number of cases suitable stores were not available for the
groups. In other cases the location of the rehabilitated warehouses did not take into account the
location of FOs.
4.3 Training of smallholder farmers in improved post-harvest technologies
The program aimed to improve post-harvest management practices at both aggregation centre and
farmer household level. According to SAIOMA Final report (2016) 96,673 farmers were trained (33,053
male and 63,620 female) – exceeding the target of 95,000 farmers (102% LOA achieved vs. target).
Topics included: use of tarpaulins, cleaning and sorting of grain, use of moisture meters, use of
polythene or clean bags, siting of bags, improved stores, application of chemicals (following an
Environmental Assessment and development of an Environmental Management Plan) and farm
business skills. Initial training by SAIOMA partners took place at aggregation centres or training centres
for group leaders and some farmers. To reach other smallholder farmers, the approach taken was
trainer of trainers (ToT) or lead farmers who were inducted by program implementing organizations.
An individual ToT or lead farmer received training directly from the implementing agent and was then
required to pass on the training provided to 10 or more fellow farmers. In some cases (especially in
Zambia) the trainer farmer received training materials such as posters. The training approach had the
SAIOMA Project Final Evaluation Report NRI
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advantage of reaching a large number of farmers. The disadvantage was that the training they
received was mostly one-off and since local extension staff were not always involved in the initial
training, there was limited back-stopping available for the ToT, impacting on uptake and sustainability,
due to limited resources.
Findings on beneficiary farmers trained on different post-harvest topics is summarized in Table 9. In
Kenya and Malawi a large majority of SAIOMA program beneficiaries interviewed during the
evaluation survey were trained in at least one topic was highest in Kenya (99.2%) followed by Malawi
(91.7%). In Zambia only one-third of farmers had been trained (33.7%) in post-harvest management
practices. In Kenya, topics in which most farmers were trained were improved varieties (97%),
improved storage (86%), chemical application in storage (86%) and marketing (84%). In Malawi, the
topic on which most beneficiaries were trained was chemical application for stored grains (85%),
followed by sitting of bags in store (84%), farm business management (81%) and marketing (77%). At
least 67% of beneficiary farmers were trained on all topics. Beneficiary farmers in Zambia received
little training compared to other countries. About 25% were trained on improved varieties while 21%,
18% and 17% were trained on marketing, chemical application on stored grains and farm business
management, respectively. Only 3% were trained on improved storage for grains.
A gender disaggregated analysis shows that the proportion of farmers trained on each topic did not
differ significantly by sex of household head except for use of polythene bags and farm business
management in Kenya where women-headed households received less training, and farm business
training in Malawi where male-headed households reported less training than female headed
households.
Table 9 SAIOMA program farmers trained in post-harvest technologies by sex of household head (%)
Training Topic Kenya Malawi Zambia
Female Male Total Female Male Total Female Male Total
At least one topic 100 99.0 99.2 88.2 91.7 90.8 38.8 36.6 37.0
Improved varieties 94.1 97.9 97.3 76.3 68.1 70.1 28.6 24.4 25.1
Use polythene/clean bags 61.5*** 85.6 80.5 66.7 66.5 66.5 8.1 6.2 6.6
Siting of bags 75.0 80.2 79.1 83.6 84.3 84.1 18.0 15.4 15.9
Improved storage 94.7 84.0 86.0 67.9 73.1 71.1 3.4 2.6 2.8
Chemical application (grains) 88.6 84.7 85.6 81.0 86.9 85.4 14.8 18.3 17.7
Farm business management 69.7** 84.1 81.1 76.3 82.6 81.0 23.9** 15.2 16.9
Marketing 82.5 84.1 83.8 70.6 79.0 76.9 24.5 20.4 21.2
**, *** Differences between female- and male-headed households significant at 5% and 1% respectively
Source: SAIOMA evaluation household survey
4.3.1 Postharvest Management Practices
Farmers adopting improved post-harvest storage practices
Table 10 shows results for adoption of improved post-harvest technologies from the evaluation
survey. Across the three countries, the most adopted technologies were grain drying technologies
(plastic sheet, tarpaulin, and special stacks such as Mandela cock) and storage pesticides for either
grain dusting or fumigation. Adoption rates for grain drying technologies in Kenya and Malawi
exceeded 60% for SAIOMA farmers in 2015, but was below 40% in Zambia. SAIOMA increased
adoption grain drying technologies in in Kenya by 7.6 %age points. However, in Malawi, change in
adoption was higher among the control than beneficiary farmers. In Kenya and Malawi, use of grain
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storage pesticides increased for both beneficiary and control farmers. However, in Malawi, this
increase was huge, from less than 2% in 2013 to about 70% (76% in control group) in 2015. The use of
hermetic bags was almost zero in Malawi and Zambia, but in Kenya, it ranged from 2-3% in 2013 to
about 6% in 2015, with SAIOMA program impact being 1.2 percentage points. Overall, the net impact
of the program on SAIOMA program beneficiaries appears limited for the adoption of these
technologies. It should however be noted that in Kenya, the most commonly stored grain, maize, was
not targeted by SAIOMA, hence adoption of post-harvest technologies could be higher than reported
here.
Table 10 Farmers adopting improved post-harvest technologies (%)
Country and technology 2015 2013 Change 2013-15 Difference
in
differences
SAIOMA Control SAIOMA Control SAIOMA Control
Kenya
Drying grain on plastic sheet/tarpaulin 64.6 48.9 49.6 41.5 30.2% 17.8% 7.6
Raised store 6.4 5.2 5.4 4.4 18.5% 18.2% 0.2
Hermetic bags 6.2 5.9 2.1 3.0 195.2% 96.7% 1.2
Storage pesticide 60.6 69.6 56.8 60.7 6.7% 14.7% -5.1
Use moisture meter/salt-in-bottle test 9.1 6.7 2.4 1.5 279.2% 346.7% 1.5
Improved grain store 14.7 9.6 10.7 5.9 37.4% 62.7% 0.3
Malawi
Drying grain on plastic
sheet/tarpaulin*
63.0 61.9 19.0 13.5 231.6% 358.5% -4.4
Raised store 2.1 0.8 1.8 0.0 16.7% -0.5
Hermetic bags 0.0 0.0 0.0 0.0 0.0
Storage pesticide 69.0 76.2 1.8 0.8 3733.3% 9425.0% -8.2
Use moisture meter/salt-in-bottle test 3.6 0.0 0.3 0.0 1100.0% 3.0
Improved grain store 14.2 11.9 0.9 0.8 1477.8% 1387.5% 2.2
Zambia
Drying grain on plastic
sheet/tarpaulin*
32.3 29.1 nd nd
Raised store 1.7 1.3 nd nd
Hermetic bags 0.5 0.0 nd nd
Storage pesticide 65.5 61.3 nd nd
Use moisture meter/salt-in-bottle test 2.5 5.2 nd nd
Improved grain store 6.8 5.7 nd nd
* For Malawi and Zambia, this includes Mandela cocks for groundnuts nd = No data
Source: Evaluation household survey
Post-harvest losses
Post-harvest grain losses were estimated from surveyed farmer responses using visuals of grain
damage at the beginning and end of storage in 2015: Sorghum for Kenya and Maize for Malawi (Table
11). This shows that over 50 % of farmers experienced grain damage in store. In Kenya, the control
group experienced less damage than SAIOMA farmers in their stored sorghum (58.5 % seeing no
damage compared to 49 %), whilst in Malawi SAIOMA farmers were less likely to see their maize
damaged maize than the control group (46 % compared to 43 %).
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Table 11 Maize grain damage at beginning and end of storage 2015
Country/commodity Grain
damage (%)
2015 Beginning 2015 End
SAIOMA Control SAIOMA Control
Kenya - Sorghum 0 77.1 67.0 49.3 58.5
2 5.4 2.6 17.9 21.7
5 3.7 10.4 14.4 5.7
10 9.9 12.2 14.7 8.5
25 2.3 3.5 1.2 3.8
50 1.4 1.7 0.6 0.0
75 0.3 1.6 2.0 1.9
Malawi - Maize 0 94.8 87.9 45.7 43.1
2 4.3 5.7 30.4 26.8
5 0.9 4.0 12.0 10.6
10 0.0 2.4 9.2 14.6
25 0.0 0.0 1.2 1.6
50 0.0 0.0 0.3 1.6
75 0.0 0.0 1.2 1.6
Zambia - Maize 0 82.3 85.5 14.7 18.2
2 10.5 6.1 30.3 29.4
5 3.6 2.3 22.4 15.4
10 2.3 4.2 12.6 15.4
25 0.8 0.9 6.2 5.6
50 0.0 0.0 8.0 5.6
75 0.5 0.9 5.9 7.5
Stages of crop loss
Table 12 shows the reported crop losses at storage stage for both SAIOMA and control groups.
Sorghum and maize were used as case crops. Across the three countries, farmers reported most losses
in the field, during harvesting, and threshing. Losses in other stages were reported by less than 5% of
the growers. Therefore although the project intervention mostly focused on grain storage stage, these
results indicate that farmer training and support in post-harvest losses should ideally also include
harvesting stages.
Table 12 Grain loss at storage stage (%)
Source: Evaluation household survey
Country, crop and stage 2015 2013 Difference
in
differences SAIOMA Control SAIOMA Control
Kenya: Sorghum 10.9 24.5 11.7 22.9 -2.4
Malawi: Maize 12.2 8.9 15.4 26.4 14.3
Zambia: Maize 6.8 5.7 5.8 6.7 2.0
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4.4 Marketing of SAIOMA commodities
4.4.1 Farmer participation in output markets
Farmer participation in output markets has increased considerably for most crops in all countries over
the SAIOMA program period (Table 13). In Kenya, positive program impacts were achieved in pigeon
peas and cowpeas where the difference in SAIOMA market participation over the control group was
7.5 and 6.4 percentage points respectively. In Malawi, the impact of SAIOMA appears positive for all
crops except maize. The largest impact was in soya beans where SAIOMA farmers increased their
market participation by 35.1% over control farmers, followed by cassava (6.4%) and groundnuts (6%).
Results for Zambia show that SAIOMA had negligible impact on farmer participation in output markets.
Table 13 Households marketing SAIOMA crops (%)
Country &
crop
2015 2013 Change 2013-15 Difference in
SAIOMA Control SAIOMA Control SAIOMA Control differences %
Kenya
Sorghum 59.1 64.2 45.9 40.0 28.8% 60.5% -11.0
Pigeonpea 48.8 41.9 43.8 44.4 11.4% -5.6% 7.5
Green gram 63.6 67.6 60.7 62.1 4.8% 8.9% -2.6
Cowpea 44.9 52.3 41.8 55.6 7.4% -5.9% 6.4
Malawi
Maize 25.1 8.9 27.7 10.3 -9.4% -13.6% -1.2
Cassava 36.4 8.3 30.8 9.1 18.2% -8.8% 6.4
Soya Bean 39.4 - 4.3 - 816.3% - 35.1
Groundnut 39.9 8.3 37.4 11.8 6.7% -29.7% 6
Zambia
Maize 68.3 71.0 53.4 56.0 27.9% 26.8% -0.1
Sunflower 12.1 12.5 12.9 13.3 -6.2% -6.0% 0.0
Soya bean 18.4 20.8 12.4 9.7 48.4% 114.4% -5.1
Ground nut 23.8 17.0 12.8 6.1 85.9% 178.7% 0.1
Source: SAIOMA evaluation household survey
4.4.2 Facilitating linkages to structured markets
Crop marketing
While Malawi and Zambia have
only one rainy season, Kenya has
two, the main and short rainy
seasons. Not all beneficiary
smallholder farmers sold
SAIOMA promoted crops from
the 2013 and 2015 seasons as
can be seen from Fig 4. In
Malawi, 65% of the beneficiary
famers sold SAIOMA promoted
crops from the 2015 season and
62% from the 2013 season, in Figure 4 Farmers selling SAIOMA crops 2013 and 2015 (%)
SAIOMA Project Final Evaluation Report NRI
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Kenya, 51% and 66%, and in
Zambia, 58 and 71% respectively.
The upward trend in number of farmers selling SAIOMA promoted crops, particularly pulses in Kenya
and Malawi – pigeonpea, cowpea and soyabean - may be attributed to the impact of the project
interventions as regards promotion of these crops and the attendant perceived income from crop
sales.
Household marketing practices of smallholder farmers
While the findings showed that in Zambia crop marketing for both 2013 and 2015 seasons was mainly
an activity for male adults with 56% and 55% participation respectively, this was not the case for
Malawi and Kenya where female adults were the ones mainly involved in crop marketing. About 67%
of women were involved in crop marketing in Kenya for the 2013 season and the number rose to 70%
for the 2015 season. For Malawi, 37% of women were involved in 2013 and 39% in 2015. Not
surprisingly, children were the least involved in household marketing in all the three countries. The
control sample for all the three countries mirrored the same practice in terms of household marketing
practices. In comparison to the 2013 season, the number of actual participation of smallholder farmers
in marketing SAIOMA promoted crops in Zambia and Kenya increased in 2015 by 25% and 35%
respectively, while in Malawi there was almost no change.
Buyers for smallholder farmer produce
SAIOMA primarily used an aggregation approach for enhancing SHF’s access to structured markets. In
this respect, SHFs were to undertake collective selling of their produce in order to attract better prices
through bulk selling to structured markets. This was to be fostered through SHF’s respective FOs
linkages to large structured output markets. FOs were also linked to structured markets through some
agro-dealers.
The survey findings showed that the most frequent buyers for smallholder crops for 2013 and 2015
seasons were small traders in all the three countries while the large traders were the second most
important crop buyers in Kenya and Zambia as indicated in Figure 5. However in Kenya for the 2015
season there was an observable shift from small trader crop buyers to structured markets such as
SAIOMA group, farmer organisation, consumers, supermarkets, food processors, and millers.
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Kenya Malawi
Zambia
Figure 5 Buyers for smallholder crops for 2013 and 2015 (% farmers)
In Malawi, the use ofsmall traders reduced from about 70% in 2013 season to 50% in the 2015 season,
which also had a sharp rise in the use of other buyers such as large buyers, SAIOMA group, farmer
groups, food processors, and NGOs. In Zambia however, the trend was different showing an increase
in dealing with small traders from 42% in 2013 to 45% in 2015. The percentage of beneficiaries dealing
with large buyers in Zambia remained the same (29%) for both seasons, while there was a noticeable
reduction in those dealing with the FRA from 12% in 2013 to 9.4% in 2015. A few Zambian smallholder
farmers also managed to sell to supermarkets in the 2015 season.
These findings imply impact of the project on farmer market engagement through market awareness
and negotiating skills making it possible for the beneficiary famers to pursue options for better paying
buyers in terms of price, payment duration and convenience. In terms of date of sale for their crops,
SAIOMA Project Final Evaluation Report NRI
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the findings showed that most of the beneficiary farmers sold their produce within the year they
harvested their crop. The average selling date varied from country to country. In Zambia, the findings
showed that most farmers sold their produce from July to August with a good number still selling in
September, while in Kenya most of the farmers sold around March and August of the harvesting year
owing to the two seasons. In Malawi, peak crop selling in both the 2013 and 2015 seasons took place
from July to August of the harvesting year.
Farmer marketing of different AGRA commoditiesthrough structured markets (including large traders,
farmer organisations and agrodealers) is shown in Table 14. This indicates a general increase in the
percentage of farmers marketing through these channels over the project period for most crops
except greengram in Kenya and maize in Malawi. However, the increases were not highly significant
compared to the control group. This appears to reflect the challenges of low agricultural surpluses
during the project years, a wider move towards structured markets in some commodities (e.g.
sorghum in Kenya), and continuing attraction of informal sector buyers as a source of ready cash
income.
Table 14 Farmers marketing grain through formal markets (% growers)
Country and crop 2015 2013 Difference in
SAIOMA Control SAIOMA Control differences
Kenya
Sorghum 12.8 13.2 2.4 5.7 2.9
Pigeonpeas 5.4 1.2 8.8 11.1 6.5
Greengrams 16.8 18.9 17.4 9.1 -10.4
Cowpeas 12.3 9.3 5.0 6.2 4.2
Malawi
Maize 1.5 0.0 4.1 0.9 -1.7
Soyabeans 3.2 0.0 0.0 0.0 3.2
Groundnuts 3.8 0.0 1.6 0.0 2.2
Zambia
Maize 20.0 18.6 16.0 15.0 0.4
Sunflower 2.0 2.1 1.3 2.7 1.3
Soyabeans 6.4 5.6 1.0 1.6 1.4
Groundnuts 1.2 0.9 1.5 2.4 1.2
Source: SAIOMA Evaluation household
Payment for Crop Sales
In all the participating countries, the smallholder farmers were largely paid on delivery in both seasons
as indicated in Figure 6. For the 2015 season, the number of beneficiary farmers in Kenya paid on
delivery reduced from 95.3% in 2013 to 80%, while in Malawi the number reduced from 76% to 53%.
In both these countries there was also an increase in payments made in advance and later (after
delivery).
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Kenya Malawi
Zambia
Figure 6 Mode of payment for crop purchases
However, in Zambia the trend was different showing an increase in number of farmers paid on delivery
from 61% in 2013 to 84% in 2015, although there was a significant reduction in the total number of
smallholder farmers with produce to sell, an outcome that could be linked to poor rainfall in 2015.
There was also a noticeable reduction in number of smallholder farmers receiving payments in
advance and after delivery.
4.4 Country experiences
Case studies of aggregation centres visited during the evaluation and key informant interviews show
differentiated country experiences under SAIOMA’s improved access to markets.
In Kenya, farmers bring produce to aggregation centres where they are issued with a receipt showing
the quantity stored, but no immediate payments are made. There are however good performing
centres located in more productive areas such as Meru and Tharaka nithi. Once secured in the
aggregation centre the grain is dusted with pesticides or kept in hermetic bags. However, there are
challenges with level of aggregation in some centres. For instance, at Wamunyu grain aggregation
SAIOMA Project Final Evaluation Report NRI
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centre (GAC) the group aggregated 10.1 tons of grain in 2015 and 11.3 tons in 2016 (12% increase).
However, these figures translate into an average of about 20kg of grains per group member, indicating
a very low rate of aggregation. The most aggregated crop was greengrams followed by cowpeas.
Aggregation of cowpeas declined in 2016 compared to 2015 due to low prices encountered in 2015.
For sorghum, aggregation was negligible. Farmers cultivated little sorghum due to bird damage
problems associated with the popular varieties. Secondly, the crop did not attract buyers after harvest.
Demand for pigeonpeas was high, but the crop was attacked by blight. Moreover, farmers were
receiving indications of the possibility of a better price (Ksh 150) in Mombasa while the aggregation
centre was promising farmers only Ksh 80. This made many farmers not to aggregate. For beans, sales
were limited by the high prices set by the GAC. Another challenge in aggregation was that farmers
wanted spot cash upon delivery of their grains to enable them pay pressing bills such as school fees.
The aggregation centre did not have capital to pay farmers for grain delivered. As local traders offered
lower prices, grain was sold to bulk traders from Nairobi and Athi River Town. The GAC has been linked
to about 20 cereal companies and individual buyers. It is therefore hoped that these linkages will result
in more value for the smallholder farmers in future.
In Malawi, this component was supported by NASFAM and the Agricultural Commodity Exchange for
Africa. The program promoted three models for linking smallholder farmers to structured markets:
a. The direct buyer. Farmers were trained on the use of on spot markets and linked to direct
buyers.
b. NASCOMEX. This worked using the satellite warehouse system. Farmers could use this to
market to a direct buyer, NASCOMEX or district warehouse. This idea was to encourage trade
through increased volumes through farmer associations. On the cassava value chain the
program worked with Cassava Value Addition for Africa (C:AVA), which linked them with
UNIFARM (Carlsberg breweries was the ultimate buyer of the high-quality cassava flour).
c. Warehouse receipt system (WRS). An individual needed to have a minimum of 1500kgs. They
would then book and deliver it to the district warehouse where they received a warehouse
receipt. Text messages on prices were sent out to the farmers daily. Once a farmer was
satisfied with the price they could an issue instruction to sell. Balaka has a district
warehouse; in Zomba there is a warehouse at Mwandama; in Mangochi at Namwera;
Mulanje; and NASFAM offices. The district warehouses were operated by ACE and the
warehouse receipt system. Most of the volumes were channeled through the warehouse
receipt system. The WRS allowed farmers to pledge 70% of their deposited volumes to get a
loan to buy more grain and deposit again. Farmers were able to access bridging finance from
or through ACE. The financing was accessible to farmer organizations, although interest was
charged at market rates (Commercial lending rates in Malawi are above 40% in some banks)
The aggregated produce in Malawi was not only (or primarily) from member farmers: other traders
and farmers within the location could also bring their grain. For example, Nsanama emerged as the
best cooperative yet a sizeable proportion of its aggregated grain was not from members. Also the
aggregated quantity was generally low, making it challenging to attract bulk buyers. In Chikewo ACE
turned down produce (as it did not reach minimum quantity/standards), discouraging farmers: on
farmer dumped 60 bags of rice at the centre. Further, the process of price setting was not well
understood and transparent to some smallholder farmers, thereby raising suspicion. For example,
SAIOMA Project Final Evaluation Report NRI
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some farmers felt that ACE was delaying sales not because a market had not been found but so that
ACE could make a profit. WRS training by ACE only targeted leadership of cooperatives while
Cooperative training was more inclusive- people opted in/out. Farmers only became aware of the
deducted costs later in the transaction
The need by farmers for quick payment on their crop sales in order for them to attend to pressing
needs such as purchase of inputs and other necessities was the main factor behind their direct selling
to buyers: informal markets remained their main outlet for sales.
Some of the satellite warehouses in Malawi are rented or belong to government and are therefore
not owned by the farmer organisations. This is proving unsustainable as farmer associations fail to pay
rent after the end of SAIOMA. It was also observed that non-SAIOMA crops such as pigeon pea and
rice, turned out to be viable for aggregation – and more successful than the official SAIOMA
commodities. The unfavourable rainy season was a significant factor affecting production of maize
and other non-drought tolerant crops in Malawi.
Regarding aggregation in Malawi, indicative findings are: • It works very well with institutions and people who understand and can manage volume
business. The direct system is limited as direct buyers usually peg a price. The farmers’
negotiation powers are limited, especially for soya which is a first crop. The bridging finance
met with challenges of loan default. Some individuals opted to get the loan but did not deposit
their commodity to ACE. NASCOMEX had fewer defaulters as the beneficiaries were
traditional NASFAM members. • Farmers Union of Malawi supported the process of transformation of clubs to clusters to
associations (service provision) to cooperatives that are more into business. Cooperatives
have the capability of being a market for their farmers by using the capital, which they
obtained through bridging finance. This helped cooperatives to mobilize more members by
giving them incentives. However, not all groups were ready or willing to reach cooperative
status. • A question for further investigation is the prices received by farmers under the different
models: Did farmers who sold to structured markets /aggregators receive a higher price?
In Zambia, market access was supported by Frontier who endeavored to reach out to 35,000 farmers.
The approach involved conducting training and refurbishment of warehouses for grain aggregation.
The training approach initially involved the use of Camp Officers (COs), who are government
employees, to train farmers but this proved ineffective and unsustainable as the COs seemed not well
motivated in the absence of pecuniary benefit for them. Another approach involving the use of lead
farmers as trainer of trainers (TOTs) was introduced. The challenge with this approach was that the
TOTs faced transport problems, lacked motivation and it was also difficult to monitor them to ensure
training actually took place. To motivate TOTs, Frontier started giving ZMK100 for each lead farmer
per 100 farmers trained. An attendance list was used for verification. However some competitor
organizations paid their TOTs much higher fees for conducting similar training. The transport challenge
was overcome by opting for TOTs to conduct training within their respective locations.
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To assess farmer improvement arising from the training interventions, field trips were conducted by
Lusaka-based senior Field Officers. The findings revealed that knowledge retention by farmers tended
to be low largely due to low literacy levels, and because some farmers missed a number of training
meetings. This necessitated conducting refresher training for both the lead trainers and farmers. In
other instances, it was clear that retention had improved especially in areas around aggregation
centres.
The program’s approach for market access enhancement took into consideration the nature of the
Zambian structured markets for smallholders which did not set advance prices due to market volatility,
making it difficult to secure forward contracts. Therefore the approach taken was simply to link the
farmers to identified markets and then empower them through training.
Some of the key lessons learnt relating to the market access training interventions: • Leadership and governance are critical for cooperative development. • Repeated training is needed focusing on areas from input marketing to post harvest. • A relatively longer implementation period is likely to yield better results given the generally
innovative market approach and low literacy levels among the beneficiary smallholder farmers. • In future programs, there is need to conduct an assessment of incentives to the TOTs (lead
farmers).
Aggregation centres in Zambia were not effectively used during the 2015 season due to poor rains, as
well as smallholder farmers generally opting to sell their produce through the small traders who paid
on delivery and followed them to their respective locations to purchase the produce. The issue of
individual farmers paying for security of their produce while bulked at the aggregation centre, and
also the waiting period for securing bulk buyers and eventual payment for their produce were other
factors discouraging the farmers from bulking. As income from sale of their produce is their main
source of livelihood, smallholder farmers cannot wait long to receive payment once they have sold
their crop as they have numerous pressing needs and end up selling to small traders who normally
pay cash on delivery. This therefore meant that the aggregation centres were empty most of the time.
There were also challenges relating to leadership and governance of these aggregation centres.
SAIOMA attempted to address these through the leadership and governance trainings conducted.
However there were some benefits of the aggregation centres which were much admired by various
local stakeholders including government and the private sector. Alternative uses of the sheds by the
beneficiary farmers and other key stakeholders were being pursued even during project
implementation. For instance, the government through the Ministry of Commerce and Cooperatives
provided additional investment at the shed sites in Nkanyu, Zumwanda, Lusuntha, and Kabulinde by
installing solar milling plants. The sheds have also become attractive to agro dealers for input and
output marketing as well as value addition agro services. These alternative uses of the sheds by both
the government and private individuals will result in enhanced sustainability of SAIOMA investments.
It is also hoped that the acquired commodity marketing and negotiating skills (e.g. contract
negotiations) as well as the acquired knowledge on quantity and quality requirements of the target
markets will make it easier for smallholder famers to access structured markets.
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4.5 Challenges
Challenges faced in relation to Smallholder farmer market access included the following:
1. Crop aggregation: The created capacity was not effectively utilized due to a number of
aggregation challenges, such as poor rains and farmers wanting spot cash upon delivery of
their grains to enable them pay for their pressing needs such as school fees, sickness and
funerals. The aggregation centres did not have capital to pay farmers for grain delivered.
Furthermore, smallholder farmers were not prepared to pay for security for their aggregated
crops as they claimed they did not have cash to pay before crop sales.
2. Training in post-harvest management practices: The training approach for smallholder
farmers through trainer of trainers without building capacity for ongoing support is likely to
affect the sustainability of this activity as new post-harvest issues arise, such as new pests and
diseases.
4.6 Lessons and Recommendations
The following are considered as key lessons and recommendations on access to structured markets
by the targeted smallholder farmers.
1. All of the constraints to smallholder farmers’ participation in formal output markets need
to be considered including: farmer organisation governance to improve transparency and
trust so that farmers increase aggregation, and crop insurance in event of crop failure.
2. All aggregation centres should be owned or leased on long-term arrangements (e.g. from
government) by the participating farmer organisations (not rented from private
individuals); where this is not possible, new warehouses could be built if assessed to be
cost-efficient.
3. Training on in-field post-harvest management is needed to address the main stages at
which losses are occurring.
4. Ongoing support for smallholder farmers in post-harvest management is needed. This can
be provided through building capacity and buy-in of local service providers. Formal
inclusion of local extension services in training e.g. through MoUs or service agreements,
rather than ad hoc contracts, would improve trainer and farmer capacity and the
sustainability of the interventions.
5. Inclusion of non-SAIOMA potential crops such as pigeon pea and rice (in Malawi) would
have improved program performance indicators.
6. A longer period of program implementation (minimum 5 years) would sustain and
translate improvements in farmer postharvest and marketing knowledge to practice and
performance.
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4.7 Conclusions
Different models for linking smallholder farmer to structured markets were promoted under the
program: on-spot buyers, bulk buyers, warehouse receipt system, and agrodealers. Farmer
organisations were supported to engage with each of these markets. The theory of change behind
linking smallholder farmers to formal markets is based on a number of assumptions, such as good
information and transparency in operations and good understanding by all market players of the
financing and management arrangements.
Aggregation centres have been renovated under SAIOMA. However, they have not operated as
envisaged due to reluctance by farmers to deposit their grains as a result of poor harvests, mistrust
within farmer organisations, higher prices offered in some cases by informal buyers, and the need for
smallholders to sell and receive payment immediately after harvest due to pressing household needs.
Sustainability of some of the aggregation centres is in doubt where the centres are not owned by the
group or the government.
Adoption of improved post-harvest management practices by smallholder farmers was found to have
increased. However, this does not appear to have translated into reduced post-harvest losses on-farm
for all commodities. A key observation is that the main PHL continue to occur in other stages of the
value chain not targeted by the project: namely in-field losses. The training model adopted was trainer
of trainers: ToTs were not adequately supported in their training to farmers which is likely to affect
sustainability of uptake of some technologies. Training in grading has not generally improved returns
as differential pricing is not practiced in many markets.
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5. PROGRAM PERFORMANCE – CROSSCUTTING ACTIVITIES:
STRENGTHENING FARMER ORGANISATIONS AND GENDER
SAIOMA’s direct project interventions, extending and deepening input markets and improving output
markets, were supported by two crosscutting interventions: farmer organization (FO) capacity
building and gender activities. The sections below present the activities done under each crosscutting
intervention, the successes registered and the challenges encountered.
5.1. Capacity of smallholder farmer organizations
Farmer organisations are the structures underpinning the aggregation and marketing activities in
SAIOMA. The organizations were a necessary collective marketing strategy to enable smallholder
farmers to benefit from economies of scale, access competitive markets and reduce transaction costs.
In this regard smallholder farmers were to aggregate their produce through FOs and be linked to large
structured output markets. As such, there was a critical need for the program to understand the
capacity and functioning of individual FOs and build on these to develop sustainable outcomes for
their members. The main activities carried out under the FO component were: establishing and
registering FOs into associations and cooperatives, recruiting farmers into FO membership and
training of FOs in leadership and practices. 5.1.1 Establishment and registration of FOs
The project has worked with various types of FOs namely: clusters or clubs, marketing committees,
associations, cooperatives, community based organizations (CBOs) or aggregating centers. Some FOs
were already in existence before SAIOMA program, having been formed by organisations such as the
Ministry of Agriculture or other NGOs, while in a few cases the program formed its own. In Malawi the
program has worked with 31 FOs as associations and cooperatives. Before the SAIOMA program only
7 FO were registered but 15 more have been registered as cooperatives under the program. In Zambia
the SAIOMA program has supported the establishment of 24 marketing committees. These
committees have received hand over certificates of sheds to ensure proper ownership and also to
avoid ownership disputes. In Machakos County in Kenya there were 6 registered CBOs before the
program, growing to 14 by January 2016. As registered entities, FOs have constitutions, clear
structures comprising committees such as executive, production, savings and credit, marketing,
grading and discipline. The SAIOMA program has facilitated drafting of business and strategic plans to
guide the FOs to run as businesses.
While there is progress in terms of number of FOs established and registered the evaluation exercise
has revealed that there in some cases FOs do not appear to be functional and farmers are withdrawing
for various reasons. For example, in Malawi, of the 6 FOs visited only 3 could be declared functional,
one indicator being failure to conduct meetings by the FOs. The farmers who were claimed to be
members could not remember having attended any meeting with the FOs. In Machakos, Kenya, one
group has left the aggregation center because of conflicts.
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5.1.2 FO capacity building
The underlying assumption was that the SAIOMA project would use existing registered FOs. A rapid
capacity assessment was carried out using the Capacity Performance Index (CPI) tool to establish the
baseline level of FOs and identify the capacity gaps for training. The capacity indicators are
Accountability, Professional Capacity, Income Diversification, Strategic Potential, Production
Management, Marketing Strategy, Participation, Advocacy Capacity. The project has used this tool in
Continuous Performance Assessments (CPA) to capture progress and emerging issues over time. The
assessment is based on three different tier systems:
 Tier 1 (Level 1 – Not capable D (49% & below), C – (50-55%), C+ (56 – 59%)
 Tier 2 (Level 2 – Capable B- (60-64%), B+ (65 – 69%)
 Tier 3 (Level 3 – Very capable A-(70-75%), A+ (75 – 79%), A++ (80%+)
Based on capacity gaps identified, the leaders of the FOs have been trained in leadership and group
dynamics, record keeping, entrepreneurship, business management, member mobilization and
strategic planning. They have also participated in trade fairs and exchange visits. The final assessment
has shown that 60% of FOs improved their CPI, with 59% of FOs improving their CPI above the initial
target of 43%. This improvement has ended into FOs being able to access markets. In Zambia, capacity
building of FOs has made a fundamental change in the mindset of smallholder farmers who previously
joined cooperatives to access inputs, now they cooperate in crop marketing and other enterprises.
Despite progress on farmer mobilisation there are challenges related to disputes, mistrust and lack of
interest in FOs. In Malawi, a number of farmers knew little about their membership of FOs and its
affiliation to SAIOMA aggregation centres. These farmers had to be reminded about the day they were
called to a meeting to be informed about the program, indicating they are not working effectively as
groups. In some cases members felt as if they were being used by leaders of the FOs or the
implementing partners: on some occasions, farmers did not want to be interviewed during the survey
and expressed disappointment with the program. Unfortunately, underlying issues of mistrust,
disputes and transparency are not addressed in efforts on capacity building under the program. This
may be because capacity building is guided by the Capacity Performance Index tool which is not
designed to capture and address underlying issues such as governance and group dynamics. 5.1.3 FOs and aggregation
The ultimate goal of collective marketing was to link participating farmers to formal markets to
enhance marketing of cereals and minimize exploitation of farmers by middlemen. As discussed in
Chapter 4, SAIOMA promoted different models through which FOs can sell their produce: directly
selling to bulk buyers, to agrodealers and the satellite store through the Warehouse Receipt system.
A major SAIOMA activity was mobilization of smallholder members through the FOs to aggregate their
agricultural commodities. The project managed to mobilise 33,850 farmers to aggregate, representing
56% level of achievement (SAIOMA Final Report, 2016). Reasons for low levels of aggregation include:
insufficient produce for aggregation, lack of trust and uncertainty over the benefits of aggregation.
SAIOMA Project Final Evaluation Report NRI
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The case studies below from the three countries show different experiences of FOs which have been
organized and are aggregating produce at satellite stores.
Kenya
Aggregation centers in Kenya have varying experiences. Some have experienced challenges stemming
from low production, resulting in low aggregation (Table 15). In Machakos, aggregation of cowpeas
declined in 2016 compared to 2015 due to low prices the previous year. For sorghum, aggregation was
negligible. Farmers cultivated little sorghum due to bird damage problems associated with the popular
varieties. Secondly, the crop did not attract buyers after harvest. Demand for pigeon peas was high,
but the crop was attacked by blight. Moreover, there were rumours that the crop was fetching better
prices (Ksh 150) in Mombasa while the aggregation centre was promising farmers Ksh 80 which
discouraged aggregation. For beans, sales were limited by the high prices set by the GAC. Another
challenge in aggregation was that farmers wanted spot cash upon delivery of their grains to enable
them pay school fees and other pressing needs. The aggregation centre did not have capital to pay
farmers for grain delivered.
Table 15 Grain aggregation and sales at Wamunyu GAC
Crop Grain aggregated (Kg) Grain sold (Kg) Grain prices received
2014 2015 2016 2015 2016 2015 2016
Cowpeas 4,320 2,610 4,320 1,800 60-70 30
Green grams 2,610 5,220 2,610 5,220 90-100 80-90
Pigeonpeas 810 270 810 270 70-90 50
Sorghum 2 0 2 30 0 - Maize 90 1,170 90 0 26 - Beans 270 0 180 - 60-75 - Total 10,117 11,286 10,027 9,336
Makutano Grain Aggregation Centre
Established in 2014, Makutano GAC has currently has 260 members (with some drop-outs and new
members), with 13 committee members from all the 13 member groups. There are a total of 65 groups
across the whole sub-county – aggregating through 6 stores. The aim is to enhance marketing of cereal
and minimize exploitation by middlemen (including use of false weights and measures) and search for
markets and collective marketing. Under SAIOMA program the GAC held sensitization meetings,
conducted elections, and received training in post-harvest handling, entrepreneurship and collective
marketing.
Initially, most farmers were skeptical of the collective marketing until the returns were received. Each
group had different levels of adoption. After coming together as GAC, the group gained more
bargaining powers; it aimed at eradicating brokers - accessing market information and using it to
bargain. They have now accessed new buyers such as Imara Kenya Limited. GAC has established a
store (capacity: 4,000 90 kg bags) and are pursuing linkages with EAGC to be certified as a WRS by the
end of this season with credit facilities. It has 5 rented stores: 1 community owned and 1 owned by
the group. Total capacity is 1000 Bags in 5 stores & 600 bags in 1 store. Average time of storage: 1
week. Each member is deducted Ksh1 PER KILO to support admin expenses and other support services
(Now KS2). Aggregation is shown in Table 16. Members were originally paid cash but now each
SAIOMA Project Final Evaluation Report NRI
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member has an account for payment. The buyer negotiates with the marketing committee on pricing,
packaging, loading, quality, time of collection and payment. Most buyers pay within one week; Imara
Kenya Ltd within 24 hours. Prices received by the aggregation centre are shown in Table 17. Table 16 Aggregation by Makutano GAC (Main store) MT
Crops: 2014 2015 season 1 2015 Season 2 2016 main season
Sorghum 84 161 81 200
Green grams 200 140 375
Pigeon peas 150**
Cow peas 100 40 50
** has a contract of 700mt of pigeon pea with Imara Kenya Limited; also buys green grams
Other buyers are: Unga Kenya Limited –Green grams and sorghum; Sorghum Pioneer Agencies –mostly
sorghum; EABL/Through Mutegi Co. Ltd; WFP-Sorghum. Table 17 Prices received by Makutano GAC
Crops: Before 2013/kg 2014 2015 2016
Sorghum 18 29.5 28-35* 29
Green grams 60 70 80 81 –110b Pigeon peas 50 82a Cow peas 20 50 60 0
c *WFP bought at Ksh35 per kg a –contract price, yet to supply the 700mt b –sold 60mt to a trader –Munduve c- Did not aggregate any cowpea due to poor crop yields due to diseases
Why is Makutano so successful? The GAC has high levels of accountability and trust. In part this
appears to be due to good practices of accountability and transparency: issuing receipt (in triplicate)
for every delivery upon weighing and verification, stock cards to enhance reconciliation of daily
transaction. For CESS deductions members are sensitized on how the money is utilized and committee
members communicate all changes or decisions to their fellow members in their respective group. All
13 member groups are linked to anchor buyer Beatrice Nthaka with forward contracts. In case of
dispute, resolution is undertaken by GAC officials and if not resolved, is mediated by officials from the
Ministry of Gender Social Services. Sustainability elements include: Scaling up aggregation and
collective marketing, recruiting new groups for buy-in, a business plan for Aggregation, MPESA, Agro- vet; collection of CESS to support administrative services; monthly contributions enhance capital base;
search for more contracts for bulk-selling; governance skills are well entrenched in the GAC with
enhanced trust relations and conflict resolution. SAIOMA program has contributed to this success
story with equipment, training, forming strong market linkages, networking with other counties
producing similar crops; farmer exchange visits.
Gaps remain: more training is needed in entrepreneurship and post-harvest handling – training was
done between 2014 and 2015 so new members were not trained. Storage facilities are limited: there
is need to pursue cost-sharing arrangement for establishing stores: this will enhance ownership.
SAIOMA Project Final Evaluation Report NRI
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Figure 7 Kenyan smallholder farmers aggregating grain
Malawi
In Malawi, the Farmers Union of Malawi supported the FO capacity building component of the
program. Different types of FO have been supported under SAIOMA including existing NASFAM
Associations, Cooperatives and WALA groups. In terms of group mobilisation, some groups clearly
followed the transition from one program e.g WALA in Balaka Bazale EPA to SAIOMA. In some cases,
FUM supported the process of transformation of clubs to clusters to associations (service provision)
to cooperatives. Cooperatives have the capability of being a market for their farmers by using the
capital mobilised through membership and potentially through bridging finance, helping cooperatives
to mobilize more members by giving them incentives. However, NASFAM groups were ready or willing
to reach cooperative status so FUM could not to coerce associations into becoming cooperatives.
The Malawi experience with FOs supported under the program is mixed. Four FOs were found to be
very active in aggregating commodities, with between 50 and 100 members bringing soya and other
commodities for aggregation by NASFAM in 2016: three of these were in Mulanje district. One,
Mabuka, was an existing cooperative established by the Ministry of Trade. In other cases, FOs were
not active in aggregation for various reasons including the fact that production by members was low
to deposit in warehouses. By contrast, in Domasi, the Water Users Association had planned for rice to
be aggregated but the executive has not been transparent in the past with rice sales so farmers have
not deposited their produce. This indicates how trust issues compromise on aggregation.
Issues of governance appear to be critically impacting the performance of the FOs. For example, at
Likhomo Association, the chair is also the village chief and other association leaders are her relations;
members follow the chair blindly: they did not even know the name of their group or what its
objectives are. By contrast, in Chikwewo, Machinga, there is separation of power: keys for the
warehouse are kept by a separate individual from the chair and there is a clerk as a third check on the
SAIOMA Project Final Evaluation Report NRI
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store. Farmers at Chikwewo are committed to the group and are aggregating: other organizations are
now working with Chikwewo which is viewed as a successful case.
Zambia
In Zambia, the project worked primarily with existing cooperatives which had been set up around 2011
by the government as a conduit for the Farm Input Subsidy Program. For some groups this was their
primary interest and although members expressed commitment to the aims of the program there was
a gulf between aggregation targets and performance. In other cases (Uyanga Aggregation Centre: Case
study to be inserted) the FO had existing activities such as a group farm. Here group organisation and
member cooperation was much stronger and provided a good base on which the project could provide
capacity building support.
5.1.4 Farmer perceived benefits from SAIOMA
Surveyed farmers who have participated in the SAIOMA program indicated a range of benefits from
program activities (Figure 8). In all three countries, farmers indicated they have benefited from
training on farming with smaller numbers benefiting from training in post-harvest handing and
marketing. To date, few farmers surveyed have seen improvements in income from their participation
in the program.
Figure 8 Benefits from SAIOMA membership (% members interviewed)
5.2 Women and youth participation in leadership positions
The SAIOMA program implemented gender activities to ensure participation of women and youth in
leadership position in the FOs. The main activities were gender training among program staff and
gender activities to promote women’s participation in program implementation. Results of the
evaluation exercise confirm that women are the majority or participants in the program activities.
0 5 10 15 20 25 30 35 40 45
None
Capacity building for post-harvest handling
Training on marketing
Training on farming
Training on group dynamics
Improved incomes
Improved access to inputs
Table banking
Zambia Malawi Kenya
SAIOMA Project Final Evaluation Report NRI
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Some FOs were women-only while others were mixed: for example, in Machakos, Kenya, 7 FOs were
women-only while 3 were mixed. Women have been quite successful in securing leadership positions. For example, in Machakos, Kenya,
the Wamunyu CBO management committee comprises 5 men and 8 women and the ordinary member
committee, 22 women and 1 man. In Malawi, the Chair of Likhomo Cooperative is a woman: she is
also a board member of Farmers Union of Malawi. However, these achievements are not solely
attributable to SAIOMA since the FOs which form the aggregation centres were already in place at the
start of the program.
Several changes in women’s involvement in decision-making have been reported in the three
countries over the course of the program. Whilst, these changes cannot be directly attributable to
SAIOMA, they have occurred within the context of women’s participation in the program. Figure 9
shows SAIOMA program female participants reporting an increase in their involvement in household
decision-making on produce sales as: 36% in Kenya, 29% in Malawi and 26% in Zambia. These increases
were higher than for women respondents in the control group. Overall, a majority of women reported
there no change in their involvement in decision-making. Less than 1% indicated they had reduced
their involvement in decision-making over the program period.
Figure 9 Perceptions of women's involvement in decision-making on produce sales (% women)
Women respondents gave similar responses on their involvement in decision-making over income
from sales of crops: 36% in Kenya, 29% in Malawi and 23% in Zambia stating an increase over the
period of the program (Figure 10).
0
10
20
30
40
50
60
70
80
90
100
SAIOMA Control SAIOMA Control SAIOMA Control
Increased Decreased No change
Kenya Malawi Zambia
SAIOMA Project Final Evaluation Report NRI
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Figure 10 Perceptions of women's involvement control over income from sales (% women)
During focus group discussions women revealed that structured markets have enhanced transparency
whereby even if their husband is taking produce to the market wives now demand to see receipts to
confirm the sales. Again, by targeting women, SAIOMA has become a vehicle for the emergence of
businesswomen, who end up being in control of their business activities.
We also find that the CPI tool is designed as a gender-focused tool and includes gender disaggregated
scores. The SAIOMA program achieved its target on women in leadership roles (55 %). This is within a
context where a majority of group members are women and many groups had women officials before
the start of the program. Nevertheless, SAIOMA’s gendered targeting and gender specific activities
have contributed to building the leadership capacity of rural women which is commendable.
5.3 Challenges faced
A number of challenges were faced in supporting FOs, which could not be well handled by the CPI tool.
As indicated above governance and accountability were critical factors determining the effective
participation of farmers in the FO with resulting impacts on the performance of the FO/Aggregation
Centre. The CPI tool is administered to project leadership, without participation of members, so there
is no in-built mechanism for triangulation of results. Generally, project stakeholders felt that the tool
was a blunt instrument which could not assess issues of governance, participation, accountability etc.
Again, the CPI framework is useful in assessing the performance of FOs, but the focus is fairly general
(on leadership, financial management and governance etc.) rather than being a tailor-made needs
assessment for individual groups. Issues such as trust, relationships and transparency are critical areas
requiring in-depth coverage for numbers of groups.
Increasing the capacity of non-leaders was not a focus of the program: it was expected that this would
be achieved through a trickledown approach (in some cases trainer of trainers). In practice, there was
generally no effective mechanism for sharing learning outside the leadership committee. This had the
 -
 10.0
 20.0
 30.0
 40.0
 50.0
 60.0
 70.0
 80.0
 90.0
 100.0
SAIOMA Control SAIOMA Control SAIOMA Control
Increased Decreased No change
Kenya Malawi Zambia
SAIOMA Project Final Evaluation Report NRI
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disadvantage of limiting capacity building to current leadership, although committees changed
membership during the life of the project resulting in new members who were not trained. In some
cases the approach may have reinforced the underlying lack of transparency and trust which existed
in a number of FOs.
Overall, it appears the program did not invest sufficiently in understanding the past performance of
individual associations, so that existing mistrust and leadership issues remained unchallenged. An
institutional audit would have helped to uncover and help address inherent problems. Furthermore,
the training approach the ToT model as a training approach is limited unless those trained are
supported with resources go on and train others.
5.4 Conclusions on crosscutting issues
Farmer Organisation strengthening was a critical component for the overall success of SAIOMA and to
the sustainability of program outcomes. As a cross-cutting intervention in the program, its importance
was recognised in program design. However, this component received the smallest share of budgeting
and resources and this limited the scope of its activities. The Capacity Performance Index tool used by
the program was useful in identifying broad levels of FO capacity, but was not effective in identifying
and addressing underlying management, governance and accountability issues. The modular
approach taken to training FO leadership faced similar challenges. In some cases SAIOMA partners
were able to provide backstopping to their FOs, but coaching and mentoring would ideally have been
an ongoing principal activity.
Overall CPI scores for SAIOMA supported FOs increased slightly over the life of the programs, which is
commendable, however there is a danger that this might not be sustainable with leadership turnover.
Program targets on supporting women in FO leadership roles were met or exceeded.
5.5 Recommendations on crosscutting activities
1. Farmer Organisation strengthening needs to be placed at the centre of any future market
strengthening program and provided with adequate resources and support
2. Assessment and interventions to support FO should be based on a wider measure than the
CPI to capture dynamics of accountability and trust and encourage the participation of farmer
members for sustainability and transparency. 3. Formal collaboration with local partner organisations including Ministries of Agriculture,
Trade and Department of Cooperatives (such as through Memorandums of Understanding or
Service Agreements) will enable follow-up and sustainability of FOs and aggregation centres
beyond the program.
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6. PROGRAM PERFORMANCE – IMPACTS AND OUTCOMES AT
SMALLHOLDER FARMER LEVEL
The evaluation assessed performance of the program against key impact and outcome indicators
(Table 1 above) and a number of other relevant indicators. 6.1. Program goal
Rural households living below the poverty line
The SAIOMA program goal is to promote inclusive agriculture sector growth for a sustainable increase
in income and food security in selected East and Southern African countries by the end of September
2015 (revised to 2016). The program Impact indicators, to which the program is intended to
contribute, is the percent of rural households living below the poverty line ($1.25/day). UN Millennium
Development Goals data show the percentage of rural households living below the poverty line in
2014 to be 49.1% in Kenya, 56.6% in Malawi and 77.9% in Zambia (Table 18) (Comparative historical
data is not currently available). This equates to 91 % of SAIOMA Level of Achievement (LoA) target in
Kenya, 57 % in Malawi, and 78 % in Zambia.
Percent change in Agricultural Gross Domestic Product
The highest level Outcome under the Improved Agricultural Product objective is Percent change in
Agricultural Gross Domestic Product. This can also be viewed as an Impact indicator as the program
can contribute to, but not directly affect, this indicator. Agricultural GDP increased across the 3
countries between 2013 and 2014: by 3.5% in Kenya, 6% in Malawi and 6.3% in Zambia (2015 data are
not currently available). The program LOA target was 35 %, which was not achieved. However, the
LOA is positive against the program baseline of 3 %. Table 18 SAIOMA performance against impact indicators
Indicator
Kenya Malawi Zambia
2013 2014* %
change 2013 2014* %
change 2013 2014* %
change
Rural
households
living below the
poverty line (%)a 49.1 56.6 77.9
Agricultural
gross domestic
product (million
USD constant
prices)b 5587.3 5780.3 3.5 1728.8 1832.3 6.0 1188.9 1264.3 6.3
*2015 data not currently available
a Population below national poverty line, rural. Source: UN Millennium Development Goals
http://unstats.un.org/unsd/mdg/Data.aspx
b Gross Value added by Agriculture, Forestry, Hunting and Fishing at 2005 constant USD prices. Source:
data.un.org
SAIOMA Project Final Evaluation Report NRI
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6.2. Objective 1 Improved Agricultural Production
Increased smallholder farmer access to improved agricultural inputs
Average distances travelled by SAIOMA beneficiaries to access agro-inputs (improved seed) has
improved over the program period (Table 6.2a). In Kenya, average distance was 3.9 km against a target
of 3 km (77 % achieved); in Malawi it was 7.6 km against a 3 km target (39 % achieved); and in Zambia
it was 10.4 km, close to the 10 km target (96 % LOA met).
A comparison was also made between program beneficiaries and non-beneficiaries, and statistical
tests made to assess the significance of the differences between the two groups (Table 6.2b). Distances to agro-dealers in 2016 did not show statistically significant differences between SAIOMA
and control farmers. In Kenya, average distances to input suppliers ranged from 3.9-4.8 km for
program beneficiaries and 3.9-4.2 for the control farmers, down from 5.6km reported in baseline
survey, indicating a decline in distance travelled. Similarly in Zambia, distance travelled by farmers to
agro-input suppliers reduced from 20km at baseline to about 10-14 km for SAIOMA farmers to 9-11km
for non-beneficiaries. However, for Malawi, distances between farmers and input suppliers did not
change. At the end of program, the distances were 8-9 and 7-8 km for SAIOMA and control farmers
respectively, compared to the baseline value of 6 km.
Looking farmer utilization of nearest input supply facilities, we found no significant differences
between program beneficiaries and non-beneficiaries across the three countries, except for
agrochemicals in Malawi and extension services in Kenya and Malawi. Malawi also reported the most
utilization of input supply facilities. In Kenya, farmers utilized mostly agrochemical suppliers (92-93%
of the sample) followed by seed sellers (85-88% of the sample) and fertilizer sellers (72-73% of the
sample). In Malawi, utilization of nearest input supply facilities was highest for both seeds and
fertilizers (99-100%) followed by agrochemical dealers (94-98%). Likewise for Zambia, farmers utilized
more the nearest suppliers of seeds and fertilizers (83-85% of the sample) than of agrochemicals (68- 73% of the sample). Access to extension services was highest in Malawi, where 98% of SAIOMA
farmers and 94% of control farmers reported that they utilize extension services. Similarly in Kenya,
more program beneficiaries (69%) than control farmers (57%) accessed extension services. Higher
access to extension services among SAIOMA compared to control farmers may be explained by the
involvement of public extension staff in the program. Farmer access to inputs is shown in Table 19. Due to differences in sampling from the baseline data,
SAIOMA impact cannot be directly inferred from this analysis. However, a comparison was made
between program beneficiaries and non-beneficiaries, and statistical tests made to assess the
significance of the differences between the two groups. Distances to agro-dealers in 2016 did not
show statistically significant differences between SAIOMA and control farmers: this indicates that both
communities are within the agrodealer catchment area. In Kenya, average distances to input suppliers
ranged from 3.9-4.8 km for program beneficiaries and 3.9-4.2 for the control farmers, down from
5.6km reported in baseline survey, indicating a decline in distance travelled. Similarly in Zambia,
distance travelled by farmers to agro-input suppliers reduced from 20km at baseline to about 10-14
km for SAIOMA farmers to 9-11km for non-beneficiaries. However, for Malawi, distances between
farmers and input suppliers did not improve. At the end of program, the distances were 8-9 and 7-8
km for SAIOMA and control farmers respectively, compared to the baseline value of 6 km.
SAIOMA Project Final Evaluation Report NRI
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The target was to reduce distance travelled by program beneficiaries to input suppliers from 6km to
5km and 3km by the end of the program. The Year 2 target was achieved in Kenya; whilst in Zambia
significant progress was made in reducing distances. Only in Malawi were distances not reduced.
Table 19 Distance to nearest input supplier against LOA target: SAIOMA beneficiaries (km)
Variable Kenya Malawi Zambia
LOA target LOA
achieved
% LOA
target
met
LOA
target
LOA
achieved
% LOA
target
met
LOA
target
LOA
achieved
% LOA
target
met
Improved
Seed
3 3.9 76.9 3 7.6 39.5 10 10.4 96.2%
Source: SAIOMA Evaluation household survey
Farmer awareness levels on promoted farm inputs in target areas
The outcome indicator: farmer awareness levels of improved farm inputs, compared SAIOMA
beneficiaries and non-beneficiaries at the end of the program (Table 20). (Lack of baseline data
constrained rigorous impact analysis, hence the results should be interpreted as contribution of
SAIOMA assuming comparable levels of awareness between treatment and control groups at
baseline). In Kenya, at the end of the program, knowledge of improved pigeonpea and cowpea
varieties was 18.8% and 14% higher respectively by beneficiary than control farmers. However,
awareness of improved varieties of sorghum and green grams was higher among the control group. For Malawi, there were large differences in awareness of improved varieties between SAIOMA and
control farmers: more than twice the levels for cassava and groundnuts, and six times for soybeans.
For maize, the proportion of beneficiary farmers aware of improved varieties was 13.9 % higher
compared to non-beneficiaries. In Zambia, the proportion of SAIOMA beneficiaries aware of improved
sunflower and groundnuts exceeded that of non-beneficiaries by around 50 % and 10 % respectively.
For improved soya beans and maize there was little difference in awareness between SAIOMA
beneficiaries and non-beneficiaries: levels of awareness of improved maize varieties were high for
both groups.
Table 20 Awareness of improved crop varieties by smallholder farmers (%)
Country and crop
2015 % difference (SAIOMA
beneficiaries vs. control) SAIOMA beneficiaries Control group
Kenya
Improved sorghum 27.9 31.1 -10.3
Improved pigeonpea 15.8 13.3 18.8
Improved greengram 47.5 52.6 -9.7
Improved cowpeas 22.0 19.3 14.0
Malawi
Improved Maize 87.7 77.0 13.9
Improved Cassava 12.5 5.6 123.2
Improved Soya Beans 27.1 4.0 502.5
Improved Groundnuts 47.9 17.5 173.7
Zambia
Improved Maize 80.2 83.5 -4.2
Improved Sunflower 11.0 7.4 48.6
Improved Soya beans 7.8 7.8 0.0
Improved Groundnuts 14.4 13.0 10.8
Source: Evaluation household survey
SAIOMA Project Final Evaluation Report NRI
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These findings indicate that the program was successful in promoting awareness of improved
agricultural technologies for increased crop productivity in Malawi and Zambia, whilst in Kenya, there
were successes in pigeonpea and cowpea.
Improved agricultural production practices
SAIOMA’s impact on adoption of improved agricultural production technologies was first compared
to SAIOMA beneficiary LOA targets (Table 21), and then further analysed against baseline for
beneficiaries and against the control group the difference-in-differences method (percentage change
for beneficiaries compared to the control group) (Table 22). In Kenya, 44 % of SAIOMA beneficiary
farmers were found to be using improved sorghum varieties, whilst 27 % were using fertiliser: 60 %
and 37 % of LOA targets respectively. By contrast, in Malawi, 86 % were using improved maize seed
and 90 % were using fertiliser: 118 % and 123 % of LOA targets. In Zambia, the levels of achievement
was 79 and 95 % for improved maize seed and fertiliser respectively: 122 and 146 % of LOA targets.
SAIOMA beneficiary farmers showed increased use of improved agricultural production practices for
different crops among the three countries during the program period. Particular improvements were
seen in: Kenya in pigeonpea (54%), greengram (28%), fertilisers (30.6%) and agrochemicals (41.7%)
during the program period; Malawi in maize (16%), cassava (18%) and soybean (20.5%); and Zambia
in soybean (73%), groundnuts (14.6%) and agrochemicals (133%).
Using the difference in differences method, results imply that for Kenya, SAIOMA increased the
adoption of improved pigeonpea and greengram and cowpea varieties by 7.2 and 11.7 percentage
points respectively and agro-chemicals by 2.8 percentage points, by farmers targeted by the program
compared to the control group. However, adoption of sorghum and fertilizers was higher for non- beneficiaries than for beneficiaries, indicating non-program factors at play. For Malawi, SAIOMA
appears to have increased adoption of improved maize, cassava and soya bean varieties by 9.1, 15.7
and 143 percentage points respectively. However, the proportion of adopters of improved groundnut
varieties, fertilizers and agrochemicals increased more for the control than SAIOMA farmers. Results
for Zambia indicate that SAIOMA increased adoption of sunflower (2.6 percentage points) and soya
beans (3.4 points) and agro-chemicals (6.2 percentage points).
Table 21 SAIOMA beneficiaries using improved technologies vs. targets (%)
Variable Kenya Malawi Zambia
LOA target LOA
achieved
% LOA
target
met
LOA
target
LOA
achieved
% LOA
target
met
LOA
target
LOA
achieved
% LOA
target
met
Improved
Seed1 73 44 60.3 73 86 117.8 65 80 121.5
Fertilisers 73 27 37.0 73 90 123.3 65 94 146.2
Source: SAIOMA Evaluation household survey
1
Improved seed for maize/sorghum
SAIOMA Project Final Evaluation Report NRI
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Table 22 Households using improved technologies (% growers)
Country and
technology
2015 2013
% change
2013-15
SAIOMA
% change
2013-15
Control
Difference
in
SAIOMA Control SAIOMA Control differences
Kenya
Improved sorghum 43.6 41.5 43.5 22.9 0.2% 81.2% -18.5
Improved pigeonpea 21.9 11.6 14.2 11.1 54.2% 4.5% 7.2
Improved greengram 64.6 40.5 50.3 37.9 28.4% 6.9% 11.7
Improved cowpea 36.9 26.2 34.5 24.7 7.0% 6.1% 0.9
Fertilizers 27.3 28.9 20.9 20.0 30.6% 44.5% -2.5
Agrochemicals 87.7 86.7 61.9 63.7 41.7% 36.1% 2.8
Malawi
Improved Maize 85.9 76.4 73.9 73.5 16.2% 3.9% 9.1
Improved Cassava 72.7 50.0 61.5 54.5 18.2% -8.3% 15.7
Improved Soyabean 83.9 - 69.6 - 20.5% - 14.3
Improved Groundnut 65.8 75.0 66.7 70.6 -1.3% 6.2% -5.3
Fertilizers 90.1 96.0 88.6 88.9 1.7% 8.0% -5.6
Agrochemicals 53.0 54.8 49.1 44.4 7.9% 23.4% -6.5
Zambia
Improved Maize 80.2 85.2 80.2 75.1 0.0% 13.4% -10.1
Improved Sunflower 20.2 13.5 19.2 15.1 5.2% -10.6% 2.6
Improved Soya bean 14.2 13.9 8.2 11.3 73.2% 23.0% 3.4
Improved Groundnut 9.4 12.3 8.2 2.4 14.6% 412.5% -8.7
Fertilizers 94.1 85.7 84.8 76.5 11.0% 12.0% 0.1
Agrochemicals 15.4 5.6 6.6 3.0 133.3% 86.7% 6.2
Crop production
Impacts of SAIOMA on production of target crops were analysed using the proportion of farmers
growing the crops and area allocated to the crops as the key variables. The overall impacts are shown
in the difference-in-differences column of Table 23. The results suggest that in Kenya, SAIOMA increased the proportion of farmers growing pigeon peas
(8.6 percentage points), cowpeas (2.4 percentage points) and green grams (0.8 percentage points)
compared to control farmers. Further, program farmers increased their land allocation to sorghum by
0.22 ha, but for the other crops, area allocations showed slight decline. In Malawi, SAIOMA increased
the proportion of soya bean and groundnut growers by 2.2 and 5.1 percentage points respectively,
but the proportion of maize and cassava growers among SAIOMA beneficiaries declined. The crop area
allocated to maize, soya beans and ground nuts increased by 0.06, 0.14 and 0.1 hectares respectively.
However, the area allocated to cassava declined by 0.22 hectares. For Zambia, SAIOMA increased the
proportion of growers for all crops by margins ranging from 0.1 percentage points for maize to 6.5
percentage points for soya beans. The program also increased area allocations to maize (0.09 ha) and
soya beans (0.27ha), but reduced area allocated to sunflower and groundnuts.
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Table 23 Farmers growing SAIOMA crops (%) and Area allocated to crop (Ha)
Source: SAIOMA Evaluation household survey
Crop productivity
Results for analysis of SAIOMA impact on productivity of target crops between 2013 and 2015 are
presented in Table 24. The results show that SAIOMA farmers increased yields of all crops except
groundnuts in Malawi. Sorghum recorded the largest gain in yields in Kenya (0.63 tons/ha), followed
by cowpeas (0.19 tons/ha). The impact on green grams and pigeon peas yields was marginal at
0.07tons/ha and 0.06 tons/ha respectively. In Malawi, the greatest yield impact was in cassava (0.29
tons/ha), while soya beans and maize recorded minimal impacts of 0.06 and 0.04 tons/ha respectively.
For Zambia, SAIOMA impacts on yields was also small, ranging from 0.05 tons/ha for sunflower to 0.09
tons/ha for maize. Given that the period covered in the analysis was short (2 years), these results
suggest that productivity enhancing interventions were mostly effective.
Table 24 Mean household yields of SAIOMA crops (MT/Ha)
Country and
crop
Crop growers (% sample) Area allocated to crop (Ha) Difference in
2015 2013 2013 2015 2013 2015 differences
SAIOMA Control SAIOMA Control SAIOMA Control SAIOMA Control Growers Area
Kenya
Sorghum 29.4 39.3 22.8 25.9 0.42 0.55 0.47 0.82 -6.8 0.22
Pigeonpea 79.6 63.7 60.6 53.3 0.57 0.64 0.81 0.58 8.6 -0.30
Cowpeas 80.7 79.3 59.0 60.0 0.50 0.63 0.45 0.56 2.4 -0.02
Greengram 53.1 54.8 46.4 48.9 0.94 0.98 0.74 0.70 0.8 -0.08
Malawi
Maize 98.5 97.6 95.8 92.9 0.71 0.48 0.67 0.50 -2 0.06
Cassava 3.3 9.5 3.9 8.7 0.35 0.31 0.58 0.32 -1.4 -0.22
Soya Bean 9.3 0.2 6.9 0.0 0.40 - 0.26 - 2.2 0.14
Groundnut 47.6 19.0 37.0 13.5 0.44 0.26 0.30 0.22 5.1 0.1
Zambia
Maize 96.3 91.3 88.8 83.9 2.46 1.66 2.28 1.57 0.1 0.09
Sunflower 48.4 41.7 36.9 31.7 0.81 0.65 0.97 0.54 1.5 -0.27
Soya bean 34.5 31.3 23.7 27.0 1.47 0.82 1.20 0.82 6.5 0.27
Groundnut 62.6 46.1 47.7 36.7 0.94 0.81 1.39 0.72 5.5 -0.54
Country and crop 2015 2013 Difference in differences
SAIOMA Control SAIOMA Control
Kenya
Sorghum 1.44 0.67 1.12 0.98 0.63
Pigeonpeas 0.55 0.30 0.56 0.37 0.06
Cowpeas 0.79 0.47 0.52 0.39 0.19
Greengrams 0.56 0.51 0.52 0.54 0.07
Malawi
Maize 1.43 1.23 1.48 1.32 0.04
Cassava 2.17 1.41 1.07 0.60 0.29
Soya Beans 0.55 - 0.49 - 0.06
Groundnuts 1.22 0.86 1.40 0.43 -0.61
Zambia
Maize 1.74 1.65 2.31 2.31 0.09
Sunflower 0.67 0.50 0.50 0.38 0.05
Soya beans 0.75 0.30 0.63 0.26 0.08
Groundnuts 1.00 0.65 0.87 0.59 0.07
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6.3. Objective 2 Improved smallholder farmers’ access to markets
Expenditures and income
SAIOMA program activities were expected to impact on household income through improved
agicultural earnings. 2015/16 per capita expenditure of SAIOMA targeted smallholder households,
used as a proxy for income, was compared to LOA targets and control households (Tables 25 and 26). This is an impact target to which the program would be expected to contribute, but not directly impact
on. It is noted that semi-commercialising smallholders, such as the majority of SAIOMA beneficiaries,
produce food for home consumption as well as for sale and so expenditure measures may significantly
underestimate income estimates.
In Kenya and Malawi per capita non-food expenditure of program households was higher than control
households by 5.7% and 14.6% respectively, whilst in Zambia it was lower by 10.6 %. Food expenditure
(computed from weekly data) is higher slightly higher for SAIOMA households in Kenya and lower in
Zambia, whilst in Malawi food expenditure is significantly lower SAIOMA households. Given the
commercialization objectives of the household this could be considered positive. However, total per
capital expenditure was found to be higher for SAIOMA than control households in Kenya and lower
in Malawi and Zambia. Per capita income figures show a similar pattern: SAIOMA program households
recorded higher income than control households in Kenya (23.6%), similar in Malawi (7.3% higher),
whilst in Zambia they were slightly lower (by 3.6%). Income from crops was considerably higher among
SAIOMA beneficiaries than control households in Malawi (86%, though levels were low), similar in
Kenya (2.4% higher), and 15% lower in Zambia. Further investigation is needed before firm conclusions
can be drawn.
Table 25 SAIOMA sampled beneficiary per capita expenditure versus targets (USD per day)
Variable Kenya Malawi Zambia
LOA
target
LOA
achieved
% LOA
target
met
LOA
target
LOA
achieved
% LOA
target
met
LOA
target
LOA
achieved
% LOA
target
met
Per capita
expenditure
of targeted
households
5 0.92 18.4 4 0.28 7.1 5 0.33 6.6
Source: SAIOMA Evaluation household survey
Table 26 Per capita income and expenditure of targeted program and control households
Indicator Kenya
USD
Malawi
USD
Zambia
USD
SAIOMA vs Control
Difference (%)
SAIOMA Control SAIOMA Control SAIOMA Control Kenya Malawi Zambia
• Per capita non-food
expenditurea 229 217 41 36 82 92 5.7 14.6 -10.6
• Per capita food-expenditure 107 105 63 92 38 36 2.0 -31.4 5.5
• Per capita total expenditure 336 322 104 128 120 128 4.5 -18.6*** -6.1
• Per capita incomeb 256 207 65 61 147 152 23.6 7.3 -3.6
Per capita crop incomeb 79 78 26 13 73 86 2.4 91.3 -15.3
Source: SAIOMA Evaluation survey a 2015/16 data. b 2015 data
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Post-harvest losses
Promotion of improved post-harvest storage practices under SAIOMA has contributed to an increase
in percentage of smallholder farmers adopting improved drying, storage and grading technologies and
processes (Chapter 4). The impact on post-harvest grain losses at household level was also assessed
using farmer assessment of losses during storage (Table 27).
In Kenya, mean storage losses of 6.6% were reported for pigeonpea, the most significantly stored crop,
against a target of 11% (167% LOA vs. target). In Malawi, mean storage losses for maize were 13.4%
compared to the 20% target (149% LOA vs. target). In Zambia, maize storage losses were 6.3% against
the 20% target (317% LOA). This indicates low levels of grain storage losses for SAIOMA beneficiaries
across the three countries. Percentage grain losses for the control groups were also relatively for the
respective countries. The findings indicate that both SAIOMA beneficiaries and control farmers are
successfully implementing post-harvest storage practices (the latter through other service providers).
Another factor behind the relatively low levels of losses was the short period of grain storage: harvests
were generally low and farmers sold part of their crop, reducing in-storage losses at household level.
It should be noted that post-harvest losses are particularly difficult to measure at household level and
so the results should be treated with caution.
Table 27 Mean post-harvest losses at household level for maize and pigeonpea, 2015 (%)
Variable Kenya
pigeonpea
Malawi
maize
Zambia
maize
LOA target LOA
achieved
% LOA
target
met
LOA
target
LOA
achieved
% LOA
target
met
LOA
target
LOA
achieved
% LOA
target
met
Post- harvest
losses
11 6.6 167% 20 13.4 149% 20 6.3 317%
Source: SAIOMA evaluation household survey
6.4 Gender Disaggregated results
The evaluation also compared the effects of SAIOMA on adoption of improved technologies between
male- and female-headed households, results of which are shown in Table 28 (agronomic practices)
and Table 29 (post-harvest technologies). The results show that women-headed households who
participated in SAIOMA had significantly higher adoption rates for improved pigeon peas (Kenya),
improved maize varieties (Malawi) and chemical fertilizers (Zambia) compared to non-participants.
Male-headed households showed differences in adoption of more technologies between project
participants and non-participants, compared to women-headed households. In Kenya, men-headed
households that participated in SAIOMA recorded higher adoption of improved varieties of pigeon
peas, cowpeas and green grams than control households. For Malawi, participating men-headed
households had higher adoption rates for improved varieties of maize, soya beans and groundnuts,
while men-headed beneficiary households in Zambia adopted more improved varieties of sunflower,
fertilizer and agrochemicals, compared to non-beneficiaries.
For postharvest technologies, beneficiary women-headed households adopted less pesticides than
control households in Kenya. On the other hand, SAIOMA men-headed households showed more
adoption of grain drying technologies in Kenya and storage pesticides in Malawi. These results imply
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that SAIOMA created more impacts for men than women-headed households and agronomic than
post-harvest technologies.
Table 28 Gender differences in adoption of improved technologies in 2015 (% respondents)
Country, technology Women-headed households Men-headed households
SAIOMA Control SAIOMA Control
Kenya
Improved sorghum varieties 13.5 12.1 12.7 17.3
Improved pigeonpea varieties 23.0** 9.1 16.4** 7.1
Improved cowpeas varieties 35.1 27.3 28.4** 19.4
Improved green gram varieties 29.7 33.3 35.3*** 19.4
Fertilizer 24.3 15.2 28.1 33.7
Agrochemicals 85.1 81.8 88.0 87.8
Malawi
Improved maize varieties 82.6** 65.2 86.2** 77.8
Improved soya bean varieties 8.1 0.0 7.3** 2.1
Improved ground nut varieties 32.6 21.7 32.6*** 11.7
Fertilizer 90.7 95.7 91.0 96.8
Agrochemicals 44.1 43.5 55.8 54.3
Zambia: Maize
Improved maize varieties 70.0 58.3 79.1 84.3
Improved soya bean varieties 2.5 3.3 5.2 4.8
Improved sunflower varieties 6.3 8.3 10.5** 4.8
Improved ground nut varieties 6.3 3.3 5.8 6.6
Fertilizer 91.3*** 71.7 94.8** 90.4
Agrochemicals 6.3 1.7 17.5*** 7.2
**, *** differences between SAIOMA and control households significant at 5% and 1% respectively.
Source: SAIOMA Evaluation household survey
Table 29 Gender differences in adoption of improved post-harvest technologies (% sample)
Country and technology Women headed households Men-headed households
SAIOMA Control SAIOMA Control
Kenya
Drying grain on plastic sheet/tarpaulin 63.5 57.6 64.3*** 45.9
Raised store 4.1 3.0 7.2 6.1
Hermetic bags 2.7 6.0 6.5 6.1
Storage pesticide 64.9** 81.8 59.9 66.3
Use moisture meter/salt-in-bottle test 5.4 9.1 9.9 6.1
Improved grain store 17.6 9.1 13.7 10.2
Malawi
Drying grain on plastic
sheet/tarpaulin† 56.5 69.8 60.6 58.4
Storage pesticide 60.9 65.1 80.9** 70.4
Improved grain store 13.0 19.8 12.8 12.9
Zambia
Drying grain on plastic
sheet/tarpaulin† 32.5 26.7 32.3 29.5
Storage pesticide 52.5 56.7 68.6 63.9
Improved grain store 2.5 2.8 7.4 6.0
† For Malawi and Zambia, this includes “special stacks” such as Mandela cocks.
**, *** differences between SAIOMA and control households significant at 5% and 1% respectively.
Source: SAIOMA Evaluation Household survey
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Differences in household incomes by sex of household head are shown in Table 30. The results show
that across all countries, there were no significant differences in household incomes and expenditure
between SAIOMA beneficiaries and non-beneficiaries, for women-headed households. However, for
men-headed households in Kenya, SAIOMA beneficiaries earned significantly more crop income (Ksh
16,857) than their non-beneficiary counterparts (Ksh 8,916). Similarly for male-headed households in
Malawi, SAIOMA beneficiaries earned significantly more income per capita (MK 25,221) than non- beneficiaries (MK 18,920), but spent less on food purchases. Although baseline data is unavailable, an
assumption of comparable baseline incomes would imply that SAIOMA increased per capita crop
incomes for male-headed households in Kenya by 89% and total incomesfor male-headed households
in Malawi by 33%.
Table 30 Gender differences in household incomes and expenditures (units in local currency)
Country, crop and stage Women headed households Men-headed households
SAIOMA Control SAIOMA Control
Kenya (KSH)
Per capita income 41551 36148 44075 40336
Per capita crop income 18236 9424 16857** 8916
Per capita non-food expenditure 25250 15229 27633 25229
Per capita food expenditure (7-day period) 216 185 193 211
Malawi (MKW)
Per capita income 24920 25451 25221** 18920
Per capita crop income 9475 11665 7358 6384
Per capita non-food expenditure 16318 19642 23757 22751
Per capita food expenditure (7-day period) 712 959 809*** 1139
Zambia: Maize (ZKW)
Per capita income 1771 1766 1487 1522
Per capita crop income 798 837 760 903
Per capita non-food expenditure 923 1116 845 884
Per capita food expenditure (7-day period) 6.6 6.7 8.0 7.5
**, *** differences between SAIOMA and control households significant at 5% and 1% respectively.
Source: SAIOMA Evaluation household survey
6.6 Conclusions on SAIOMA beneficiary impact
This chapter has assessed the performance of the program against key SAIOMA program indicators
using secondary data from World Bank/UN sources and primary data from the evaluation household
survey: Table 31 summarises the findings.
Performance against program impact and high level outcome indicators – to which the program would
be expected to contribute - is positive for change in agricultural GDP (indicator #3), although lagging
behind the target rate of 35%. For percentage of rural households living below the poverty line, the
target was 91% and 80% met in Kenya and Malawi respectively, with Zambia lagging at 58% (#1). Per
capita household expenditure (#15) is well below the baseline level. Reasons for non-attainment of
targets are a combination of external factors (agricultural sector performance) and high target levels.
On outcome targets, performance on distance travelled by smallholders to access agro inputs has
improved over the program period, and is close to LOA targets in Zambia (96 %). Targets on use of
improved input (#10) were exceeded in Malawi and Zambia (118% and 122% respectively for improved
maize varieties). In Kenya targets were only 60% and 40% met: here local varieties are also in demand
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(sorghum). Gender-disaggregated data shows that farmers in female-head households also exceeded
the targets in Malawi and Kenya, but trailed in Kenya, though the difference between male- and
female-headed households was not significant. Assessment of post-harvest storage losses at
household level shows that targets were significantly exceeded for the three commodities assessed:
pigeonpea in Kenya, maize in Malawi and maize in Zambia (#18). Finally, targets on SAIOMA
beneficiary smallholder adoption of improved post-harvest storage were met in Zambia and Malawi
(99%) whilst in Kenya adoption was 93% (for storage pesticides: adoption of other practices was lower)
(#21).
Table 31 SAIOMA Key indicators: Targets and Level of achievement at end of program 2015/16
Indicators Kenya Malawi Zambia
# LOA
target
LOA
achieved
% LOA
Targets
met
LOA
target
LOA
achieved
% LOA
Targets
met
LOA
target
LOA
achieved
% LOA
Targets
met
1
Impact Indicator: Percent
of rural householdsliving
belowpoverty line 45% 49% 91% 45% 57% 80% 50% 78% 64%
3 OutcomeIndicator:Percent
changein agricultural gross
domestic product 3.5% 6% 6.3%
4 Outcome Indicator:
Average distance travelled
byfarmerstoaccess
agroinputs 3 km 3.9 km 77% 3 km 7.6 km 39% 10 km 10.4 km 96%
10 OutcomeIndicator.
Percentoftargeted
farmersusing a .improved
seeds b. fertilizers
73
73
44%
27%
60.3%
36.9%
73
73
86%
90%
117.8%
123.3%
65
65
79%
95%
121.5%
146.2%
15
OutcomeIndicator: Per
capitaexpenditures of
targeted smallholder
farmer households $5 $0.92 18% $4 $0.28 7% $5 $0.33 7%
18 Outcome Indicator: Post- harvest losses (pigeonpea
/maize) Percent 11% 6.6% 167% 20% 13.4 149% 20% 6.3% 317%
21
Outcome Indicator: Percent
of smallholder farmers
adopting improved post- harvest storage practices 65% 61% 93% 70% 69% 99% 60% 66% 109%
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7. PROGRAM MANAGEMENT
7.1. SAIOMA consortium approach
SAIOMA was implemented through a consortium of partners, each taking responsibility for the
different program components – agrodealership, farmer training, farmer organisation capacity,
market development - with a lead partner in each country. This approach had the advantage of
drawing on expertise and strengths of each partner to offer farmer organisations and their members
a full package of services. Table 32 shows partners and responsibilities in each country.
Table 32.SAIOMA partners by country
Country Partner Responsibilities
Kenya
Agricultural Market Development Trust
(AGMARK) • Lead partner • Agro-dealer development • Oversight of work on gender mainstreaming
Cereals Growers Association (CGA) • Farmer organization mobilization and training
• Implementation of the output markets
component (including produce aggregation
and market linkages)
Cooperative Consultancy and Insurance
Agency Ltd (CCIA) • Capacity building for farmer organizations
Malawi
National Smallholder farmers’
Association of Malawi (NASFAM) • Lead partner • Responsible for coordination of the
consortium, they work on the output market
component with the Agricultural Commodity
Exchange (ACE).
The Rural Market development Trust
(RUMARK) • Executes the agro-dealer development work
within the input markets component.
Farmers Union of Malawi (FUM) • Farmer Organization capacity strengthening
component.
Zambia
Nutri-Aid Trust (NAT) • Lead partner • Responsible for agro dealer development and
consortium coordination.
Frontier • Implementing the output market component
Farmer Organization Support Program
(FOSUP) • Implementing the Farmer Organization
capacity strengthening component.
The consortia faced challenges at the beginning of the program, since most members had not
previously worked in this mode together, initially working in silos with SAIOMA implementing staff
reporting to their respective organisations. Another downside was that the organisations could
potentially be competitors: for example, both NASFAM and FUM support farmer organisations in
Malawi. Countries introduced different measures to improve consortium management. For example,
to improve reporting, Zambia introduced training and joint reporting in 2015. The arrangement
generally improved after the inception and partners were able to leverage each others’ strengths.
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Staffing and resources
Staff and resource allocations varied slightly between countries reflecting differences in their program
proposals. On transport, for example, two SAIOMA vehicles were allocated to each country, although
the consortia had 3-4 partner members and 4-6 districts/sub-counties to cover. The program was also
able to leverage previous investments by partners (for example, vehicles under Swiss MFA) in SAIOMA
implementation as part of the GDA.
Ideally partners could have harmonized activities such as fieldwork but this was not always possible
especially once field activities were underway. Some partners hired vehicles and used motorbikes but
transport was inadequate, especially for activities which required considerable travel and timely
monitoring such as management of field trials.
Program staff were generally well qualified and experienced in the work of the program, a number of
having worked on previous AGRA projects. However, staffing under SAIOMA was unbalanced and
inadequate in some program areas. Consortium partners had 3 full-time staff whilst other partners
such as FO capacity building partners had 0.5 persons. The consortium lead in Malawi had 1 field
officer based on Zomba who was unable to cover all districts and tended to prioritise NASFAM’s
SAIOMA activities. Partners tried to overcome this by using non-SAIOMA field staff but inevitably they
could not prioritise SAIOMA activities. In Zambia, Nutri-Aid had field officers in both provinces but the
input supply specialist had to double up as M&E officer; WASSA and FOSUP had no officers in other
districts. In some cases, partners had to rely on hired interns which compromised service delivery.
The overall observation is that the budget was not sufficient for all activities under the program. Some
partners had limited budget lines for salaries, which affected the commitment and availability of
partner staff.
The overall impact of the staffing and resource imbalance was that some key components, such as
monitoring and backstopping of activities such as group farmer training by ToTs - essential for
supporting activities and to scaling out and sustaining program results – were largely missing. More
staff and better complementarity by Lead Partner with other consortium members’ activities was
needed to cover all activities and districts. The alternative would have been for Government extension
workers to help with backstopping but this did not happen because extension workers did not
continuously engaged in the program. The reasoning was that government extension workers are
generally overburdened with activities, but in reality they are the coordinating stakeholder for
activities at community level.
Program management capacity
It was also the first time that AGRA had received FTF funding and it took time to set up financial and
reporting systems which delayed program start up. However, this may be considered an investment
in AGRA’s program management capacity. Country lead partners’ financial management capacity was
generally adequate and support was provided on USAID systems. Robust systems of accounting were
introduced. However, changes in accounting systems after activities had already started caused
confusion and delays. Together these factors effectively reduced the 3 year implementation period
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from 3 to 2 years - 2 agricultural seasons, of which one was very poor and the other mixed – too short
to embed activities, and impacting on progress towards targets and sustainability.
After a delayed start, funding was generally timing and sufficient until the last quarter of 2015 up to
the end of the program when payments from AGRA were delayed. The 2015/16 delays occurred while
waiting for donor approval of no-cost extension and related sub-award increases. There were
instances when SAIOMA partners had to arrange for alternative temporary financing due to funding
delays.
7.2. Program monitoring
Program monitoring and reporting was integrated into program design and implementation. Specialist
M&E staff were appointed in each country (0.5 person Zambia) by the lead partner and were generally
well supported in terms of timeliness of monitoring visits. Staff were familiar with SAIOMA targets and
key indicators. Monitoring reports were used by program staff to track progress and adjustments
made as necessary – particularly in activity targets.
Impact and outcome key indicators targets are useful in tracking SAIOMA progress. However, as
discussed in Chapter 6, some baseline LOA and end of program targets look unrealistic, for example
on increased crop yields and poverty levels.
7.3 SAIOMA partnerships and sustainability
SAIOMA investments were expected to make significant progress towards the program goal – to
promote inclusive agriculture for a sustainable reduction of poverty and hunger in the target
countries. However, as cited in the program Sustainability Plan (Program doc:24), achieving this long- term goal would involve further investments beyond SAIOMA’s lifespan. The Sustainability plan
envisaged a number of strategies and activities. These were expected to include: integration of
activities into existing AGRA programs; linkages with existing or established government/public and
private sector institutions; establishment and strengthening of the staple food value chain systems;
capacity building of the value chain actors; continued resource mobilization from traditional and non‐ traditional sources; and working with partner governments to create an enabling environment for
continued private sector investment in agriculture.
The sustainability plan outlined a wide-ranging set of activities and strategies to ensure sustainability.
However, it did not provide details on how these activities and strategies were to be implemented.
Additionally these activities/strategies do not appear to have been tracked in program reporting. The
following are the observations of the evaluation team.
Integration with existing AGRA programs
The AGRA programs most closely linked with SAIOMA are: Market Access program (Markets), Program
for Africa’s Seed Systems (PASS), Farmer Organisation Support Centre in Africa (FOSCA) and the
Agrodealer (sub) Program (ADP). Directors of these programs formed part of the program advisory
committee and contributed to program management. Learning from these AGRA programs was
incorporated into SAIOMA program design, notably capacity building for agrodealers and Farmer
organisations and Implementing partners through learning tours, quarterly and annual program
reviews at country and program levels respectively. Links with existing AGRA grantees and partners
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helped inform identification of SAIOMA consortium members and partners and these linkages
facilitated program take-off and implementation.
Whilst there were many positives in the linkages between SAIOMA and AGRA programs, more
opportunities could have been leveraged. On seeds, for example, there was no linking of agrodealers
to PASS-supported companies, despite the latter’s focus on SAIOMA commodities (except cassava)
which have traditionally been difficult to source, since large companies have not found them
commercially viable without government subsidies. Varieties were not reported by the program but
interviews with agrodealers and farmers show that seeds were mostly supplied by larger national
companies and international companies. Lessons from reviews of AGRA programs do notseem to have
been incorporated into the program, such as the need to build capacity of support systems for
agrodealers, for example through agrodealer networks. Linkages with other projects
SAIOMA has worked closely with other similar projects such as USAID supported PROFIT Plus, CRS- MAWA, Musika and as well as the USAID supported CIP Africa rising project. All these projects are
likely to continue supporting agro dealer development programs, especially in the Eastern province.
Nutri-aid has secured additional funds from other donors such as the Swedish International
Development Agency (SIDA), the Department of Foreign International Development (DFID) and
European Commission (EC) to continue capacity building efforts for agro dealers in Eastern, Central,
North Western and Southern provinces of Zambia. SAIOMA has also partnered with the IFDC on a
fertilizer quality study in shops across the entire agro dealer network developed by Nutri-aid and
partners in Zambia. Partnerships with national governments and public and private sector organisations
AGRA is expected to work with the Ministries of Agriculture and national and regional agricultural
training and research institutionsin the target countries. As these state institutions partner with AGRA
on SAIOMA common agenda and interests, synergies and capacities were expected to be built to
enhance their role in the agricultural sector and sustain performance (Program document).
SAIOMA engagement with public sector organisations has varied between countries and across the
life of the program. In the first year meetings were held with leadership in program sites as part of the
program inception. SAIOMA did not partner with state organisations directly. Grantees were non- governmental organisations and farmer membership bodies. Nevertheless the program contracted
government extension staff at local level to carry out training and provide short-term services. This
was ad hoc rather than mainstreamed within local government activities, limiting opportunities for
support and supervision. Local governments in each country have structures and staff (e.g. County
and District departments of Agriculture, Livestock and Cooperatives) who have responsibility for post- harvest and marketing activities in the district. Involving local managers in planning activities would
have improved coordination and likelihood of sustainability of program activities. Local extension staff
would have benefited from capacity building and refresher training to provide up to date information
and services to farmers.
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Policy environment
A number of key challenges in the policy environments in Kenya, Zambia and Malawi have impacted
on SAIOMA program activities and outcomes. The program envisioned AGRA working with
stakeholders to identify policies hindering agricultural growth and to facilitate discussions with policy
makers. However, given the wide range of stakeholders, both local and regional/international, and
competing interests, influencing policy is difficult. In input markets, one key policy challenge has been
the restriction on agrodealers’ participation in supplying inputs under the Farm Input Support
Programs (FISP) in Zambia, which has limited their market opportunities. In output markets, a series
of export bans have flattened markets for key commodities including maize and soya. A notable
success by the program was the sorghum campaign in Kenya.
7.5 Recommendations
1. The consortium concept piloted under SAIOMA is innovative, combining strengthening of
input markets, output markets and farmer organisations in one program. Initially partners
implemented activities in silos, though cooperation has improved significantly over the course
of the program with management support. For consortia to work successfully there is need
for clear working modalities agreed at inception, including lines of reporting.
2. More equitable support for the different components is needed to ensure sustainability.
Strengthening smallholder farmers to aggregate and enter formal markets requires more
emphasis on the foundations of the pyramid: capacity building of Farmer Organisations. This
was given the lowest priority in resource allocation of program investments. It is
recommended that guidelines for partners on allocation by objectives are considered.
3. After initiation of program start-up activities the program effectively operated on the ground
for only two seasons: too short to see a significant shift by risk-averse smallholder farmers to
new marketing arrangements and to embed new processes in farmer organisations. Ideally,
an input and output strengthening program would have an inception stage, minimum of 3
years full implementation, and an exit phase to ensure sustained impact.
4. Contextual factors, particularly the weather, had a major impact on harvests and thus program
outcomes. Weather insurance schemes could be considered as part of future investments.
SAIOMA Project Final Evaluation Report NRI
79
APPENDIX 1 Stakeholders consulted during the evaluation
Kenya
No. Name Organization/Business Title
Project implementers
1. James Mutonyi Agricultural Market Development Trust
(AGMARK) Managing Director
2. Steve Ngwalla AGMARK Director of training
3. Wilfrida Onono AGMARK M&E Officer
Collaborators/ Partners
4. Dionasia M’eruaki Meru County County Director of
Agriculture
5. JM Kariuki Machakos County County Director of
Agriculture
6. James Thuo Kitui Sub County Sub County Director of
Agriculture
7. Stephen Mworia Tharaka Nithi Sub County Sub County Director of
Agriculture
8. David Munyao Mulu Mwala- Machakos MoALF- Mbiuni
9. Mugo Gatunga- Tharaka MoALF
10. Ngila Kimotho Dryland Seed Company Proprietor
11. Martin Mutisya Agri SeedCo Sales Rep
Beneficiaries – Farmers
12. Isabella Kaweria Thau Grain Aggregation Centre (GAC) Secretary
13. Joyce Karea Thau GAC Chairlady
14. Stella Musa Thau GAC Member
15. Catherine Thau GAC Member
16. Janai Mukwati Thau GAC Member
17. Festus Muthoka Wamunyu GAC Vice Chairman
18. Peter Muindi Wamunyu GAC Chairman
19. George Mutyanzui Wamunyu GAC Member
20. Eunice Ndinda Wamunyu GAC Member
21. Janet Muoka Wamunyu GAC Member
22. Linah Nzambia Kawongo GAC Chairlady
23. Nduku Muema Kawongo GAC Member
24. Elizabeth Mbithe Kawongo GAC Member
25. Jacinta Mutua Kawongo GAC Member
SAIOMA Project Final Evaluation Report NRI
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26. Jane Maingi Kawongo GAC Member
27. Martha Kairu Gatithini GAC Member
28. Jacob Muriungi Gatithini GAC Secretary
29. Catherine Mukina Gatithini GAC Member
30. George Kairanya Gatithini GAC Member
31. David Iguna Gatithini GAC Member
32. Jacob Muriungi Tharaka Cereal Growers Association Farmer
33. Christine Kirimi Farmer
34. Benjamin Thumba Farmer
Trainers
35. Fanuel Lihanda Commercial Trainer Agrodealer Trainer
36. Pauline Kuria Commercial Trainer Farmers Trainer
Beneficiaries –Agrodealers
37. Beatrice Nkatha Sorghum Pioneer Agency and Agrovet Proprietor
38. Allan Mutegi Kithome Kipcona Farm care Proprietor
39. Isaiah Mutwiri Farm Inn Agrochemical Agrodealer
40. Alice Marimba Mkulima General store Agrodealer
41. Josphine Karimi Farm Inn Agrochemical Kagaene Agrodealer
42. Onesmus Muguna Mulika farmers center Agrodealer
43. Bernard Mongela Miathene Medical center Agrodealer
44. Ngina Kimotho Dryland Deed Agrodealer
45. Janet Kyalo S&J Hardware&Agrovet Agrodealer
46. Lina Judy Julinza Agrovet Agrodealer
47. Alfred Kikuyu Solola Agrovet Agrodealer
48. David Mwiti Davi's Enterprise Agrodealer
49. Esther Nabea Esnick Agrochemical Agrodealer
50. Amos Thuranira Young farmers check point Agrodealer
51. Felix Muthamia Farm Pro Agrovet Agrodealer
52. Edwin Kaberia Huruma farmers choice Agrodealer
53. Pius Mwinde Vet Centre Agrovet Agrodealer
54. Irene Mutuku Umoja Agrovet Agrodealer
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55. Nguuti Ndambuki Nthongoni Grain Aggregation Center Agrodealer
56. Catherine Paul Kwa Kihui Agrovet Agrodealer
57. Charles Ngami Sinai Serials Agrodealer
58. Felistus Kamama Noilo Stores Agrodealer
59. Charity Thirindi Kimachia Agrovet Agrodealer
60. Priscillah Nkirate Kaboy Agrovet Agrodealer
Malawi
Key Informant Organization/Business Title
61 Mr Katunga Ministry of Agriculture, Irrigation and
Water Development
District Agricultural
Development Officer
62 Mr Tongwe Ministry of Agriculture, Irrigation and
Water Development
Extension Methodology
Officer
63 Mr Madalitso Mgombe Ministry of Agriculture, Irrigation and
Water Development
Agribusiness Officer
64 Ms. Brenda Magomba Ministry of Agriculture, Irrigation and
Water Development
Agribusiness Officer
65 Mr Palichi Munyenyembe Ministry of Agriculture, Irrigation and
Water Development
District Agricultural
Development Officer
66 Mr Changomba Southern Region Agro-dealers
Association
Chairperson
67 McPherry Masangano Rural Market Development Trust
(RUMARK)
Projects Coordinator
68 Fransisca Mabedi Rural Market Development Trust
(RUMARK)
Project Officer
69 Emmanuel Nasasala National Association of Smallholder
Famers in Malawi
Project Manager
70 Betty Chinyamumunyamu National Association of Smallholder
Famers in Malawi
Deputy Chief Executive
Officer
71 Joshua Masangano National Association of Smallholder
Famers in Malawi
Monitoring and Evaluation
Officer
72 Modester Tembo Farmers Union of Malawi Institutional Development
Coordinator
73 Alex Dingiza Ministry of Agriculture, Irrigation and
Water Development-Domasi Extension
Planning Area
Agricultural Extension
Development Coordinator
74 Jackson Juwawo Ministry of Agriculture, Irrigation and
Water Development-Ulongwe Extension
Planning Area
Agricultural Extension
Development Coordinator
75 Ignitus Chikaonda Ministry of Agriculture, Irrigation and
Water Development-Mbonechera
Extension Planning Area
Agricultural Extension
Development Coordinator
76 Frank Matita Talandira Cooperative in Ulongwe
Extension Planning Area
Chairperson and
committee members
77 Dinala Moses Jenala Cooperative Chairperson and
committee members
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78 Augustine Chapita Domasi Water Users Assosciation,
Domasi Extension Planning Area
Chairperson and
committee members
79 Nellie Chimanda Likhomo Cooperative, Nanyumbu
Extension Planning Area
Chairperson
80 Loveness Andiseni Nsanama Cassava Cooperative,
Mbonechera Extension Planning Area
Chairperson and
committee members
81 Frank Zagwa Namibawa Association in Bazale
Extension Planning Area
Chairperson and
committee members
82 Aubrey Kampake Mbonechera Cotton Cooperative Chairperson and
committee member
83 Mr. Makawa Nsanama Trading Centre - Machinga Agrodealer
84 Mr. Ntiya Nselema Trading Centre, Balaka Agrodealer
85 Mr. Yakiti Nselema Trading Centre, Machinga Agrodealer
86 Mr. Richard naula Liwonde Trading Centre, Machinga Agrodealer
87 Mercy Chatepa Liwonde Trading Centre, Machinga Agrodealer
88 Mercy Mleme Chikwewo Trading Centre, Machinga Agrodealer
89 John Innocent Ntaja Trading Centre, Machinga Agrodealer
90 Yahaya Kawanga Ntaja Trading Centre, Machinga Agrodealer
91 Mr. Mbalika Kupilira agro dealers, Chendausiku
Trading Centre, Balaka
Agrodealer
92 Fraction Chiwaula Mangochi Turn-Off, Balaka Agrodealer
93 Edwin Matewera Balaka Town Agrodealer
94 Mr. Waterford Symon Balaka Town Agrodealer
95 Mrs. Mliya Balaka Town Agrodealer
96 Mr. D Funsani Kankao Trading Centre, Balaka Agrodealer
97 Charles Makanjira Malosa Trading Centre, Zomba Agrodealer
98 EM Katundu Domasi Trading Centre, Zomba Agrodealer
99 Peter Dimba Chinamwali Trading Centre, Zomba Agrodealer
100 Mr. Useni Emanuel enterprises, Dzaone Trading
centre, Zomba
Agrodealer
101 Starlon Banda Green World Agrodealers, Nasawa
Trading Centre, Zomba
Agrodealer
102 Dinala Moss Jenala Trading Centre, Zomba Agrodealer
103 Peter Mombanya Mayaka Trading Centre, Zomba Agrodealer
104 Keston Nzeka Zomba Boma, Zomba Agrodealer
105 Greevin Hamis Sunuzi Trading Centre, Zomba Agrodealer
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Zambia
No. Name Name of Organization/Business Title
Project implementers – KIIs
1 Peter Manda Nutri-Aid Trust
Managing Director &
SAIOMA Zambia Chief of
Party
2 Gulam Banda Frontier Development Associates Chairman & SAIOMA
Zambia D/Chief of Party
3 Mukonde Siafunda Nutri-Aid Trust
M&E Officer/Input
Specialist (also in charge
of SAIOMA Central
Province office)
4 Nyambe Manyando Nutri-Aid Trust
Agro dealer/input
Market
Specialist/Commercial
Trainer (also in charge of
SAIOMA Eastern
Province office)
5 Billy Mozah Lungu Nutri-Aid Trust Finance Officer
6 Mike Muleba FOSUP Chief Executive Officer
7 Paul Chaaba FOSUP Program Coordinator
8 Emmanuel Mwale Frontier Development Associates Market Access Specialist
Collaborators/ Partners – KIIs
1 Machona Alpha SEEDCO Agronomist
2 James Chilufya MRI SEED Technical Marketing
Officer
3 Timothy Nguluka MONSANTO Market Development
Officer
4 Etambuyu Ahamela Ministry of Agriculture, Chibombo District Agriculture
Coordinator (DACO)
5 Borniface Chishimba Ministry of Agriculture, Chibombo District Marketing
Development Officer
6 Evalyn Zulu Ministry of Agriculture, Chipata
(Chimtwamazi) Camp Chairperson
7 Mainza Alex Ministry of Agriculture, Chibombo
(Shimukuni) Camp Extension Officer
8 Ephiwell Choolwe Nyati Ministry of Agriculture, Chibombo
(Keembe Ranch) Camp Agriculture Officer
9 Bufuku Ministry of Agriculture, Lundazi Camp Agriculture Officer
Beneficiaries (Farmers/FGDs)
1 Markson Muloongo Kuligwasha, Keembe Ranch Camp - Chibombo V.Secretary
2 Mundongo Kenneth Lusumpuko Multi-Purpose, Keembe
Ranch Camp - Chibombo Chairperson
3 Principal Malambo Mayota Agric. Coop, Keembe Ranch
Camp - Chibombo Secretary
4 Godfrey Ngandu Mayota Agric. Coop, Keembe Ranch
Camp - Chibombo Vice treasurer
5 Rose Muloongo Tuchatane, Keembe Ranch Camp - Chibombo Vice treasurer
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6 Christopher Chipikauka Nchename Multi-Purpose Coop,
Keembe Ranch Camp - Chibombo Chairperson
7 Mutumbu Luckson Mutachebuki, Keembe Ranch Camp - Chibombo Vice chairperson
8 Felix Mwiimbi Mayota Agric. Coop, Keembe Ranch
Camp - Chibombo Member
9 Ronah Kabumbwe ChuumaKweseka, Keembe Ranch
Camp - Chibombo Vice chairperson
10 Charles Muloongo Kuligwasha Agric. Coop, Keembe
Ranch Camp - Chibombo Secretary
11 Evans Nkata Mutachebuki, Keembe Ranch Camp - Chibombo Treasurer
12 Bridget Mphenza Tusebense, Keembe Ranch Camp - Chibombo Treasurer
13 Kay Hamaluba Shabukalu, Keembe Ranch Camp - Chibombo Chairperson
14 David Ngonga Chumakweseka, Keembe Ranch
Camp - Chibombo Secretary
15 Evans Katongo Lusumpuko, Keembe Ranch Camp - Chibombo Vice Treasurer
16 Vainius Mubaiwa Tulyetufube, Shimbilo Camp - Chibombo
Camp Zone
Representative
17 Chilukutu
18 Joyce Kaota Shimbilo Shed Marketing committee
- Chibombo Chairperson
19 Steven Mwandila “ Vice Chairperson
20 Simbarashe Tinago “ Secretary
21 Chester Muriwa “ Vice Secretary
22 Judy Masakala “ Treasurer
23 Charles Mukuka “ Vice treasurer
24 Finess Chinago Mwanawalila, Chibombo member
25 Violet Mulumbe Seskseka, Chibombo member
26 Sibanda Lameck Njuni, Chibombo member
27 Magret Chinyama Mwanawalila, Chibombo member
28 Chilukutu Shimbilo Village, Chibombo Senior headman Lyowa
29
30 Spywaleshi Kapata Funawalumamba, Shimukuni Camp - Chibombo Chairperson
31 Lackson Mupese Mukuni Utontola, Shimukuni Camp- Chibombo Secretary
32 Clement Chiko Chisanya, Shimukuni Camp- Chibombo Chairperson
33 Kakompe Cassius Sokacho, Shimukuni Camp- Chibombo Chairperson
34 Clever Chiiko Mubobo, Shimukuni Camp- Chibombo Chairperson
35 Losa Mutupa Kakoma Women’s coop, Shimukuni
Camp- Chibombo Chairperson
36 Prisca Sianjase Twilimune, Shimukuni Camp- Chibombo Chairperson
37 Omega Kapushaba Twalubuka, Shimukuni Camp- Chibombo Member
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38 Rona Chiko Kanuka Women Coop, Shimukuni
Camp- Chibombo Chairperson
39 Honest Kalaya Tusebense, Shimukuni Camp- Chibombo Chairperson
40 Jim Musukwa Kunkamulilo, Shimukuni Camp- Chibombo Chairperson
41 Lita Nyoni Adabwiseni, Chimtwamadzi AC,
Chipata Secretary
42 Voliet Shumba Ayambe, Chimtwamadzi AC, Chipata Treasurer
43 Edaward Chilinda Twikatane, Chimtwamadzi AC,
Chipata Chairperson
44 Emusi Mwanza Twikatane, Chimtwamadzi AC,
Chipata Treasurer
45 Fedson Shumba Chimpunda, Chimtwamadzi AC,
Chipata Chairperson
46 Benson Shumba Chimpunda, Chimtwamadzi AC,
Chipata Chairperson
47 Velentina Ngoma Anasi, Chimtwamadzi AC, Chipata Secretary
48 Lunza Nzima Adambwiseni, Chimtwamadzi AC,
Chipata Secretary
49 Mabvuto Ziba Adambwiseni, Chimtwamadzi AC,
Chipata Treasurer
50 Peter Zulu Chimtwamazi, Chimtwamadzi AC,
Chipata Chairperson
51 Edward Phiri Nkhanyu FO, Lundazi Chairperson
52 Ackim Zimba Nkhanyu FO, Lundazi Vice Chair
53 Shadrech Zulu Nkhanyu FO, Lundazi Secretary
54 Lameck Banda Nkhanyu FO, Lundazi Vice Secretary
55 Majory Tembo Nkhanyu FO, Lundazi Treasurer
56 Amos Mumba Lusuntha, Lundazi Chairperson
57 Denis Nyirenda Lusuntha, Lundazi Vice Chairperson
58 Amon Nyirenda Lusuntha, Lundazi Secretary
59 Leonard Mtonga Lusuntha, Lundazi Vice Secretary
60 Benny Nkhata Lusuntha, Lundazi Committee member
61 Aaron Nkhoma Lusuntha, Lundazi Committee member
62 Agness Phiri Lusuntha, Lundazi Treasurer
63 Kelliness Nyirongo Lusuntha, Lundazi Committee member
64 Beauty Nyirenda Lusuntha, Lundazi Committee member
65 Febian Mtonga Zumwanda, Lundazi Chairperson
66 Moses Banda Zumwanda, Lundazi Vice Chair
67 James Mwale Zumwanda, Lundazi Secretary
68 Mwanida Chirwa Zumwanda, Lundazi Treasurer
69 Edward Manda Zumwanda, Lundazi Committee member
70 Agathar Banda Zumwanda, Lundazi Committee member
71 Brenda Banda Kabulinde, Lundazi Chairperson
72 Kelvin Nyirenda Kabulinde, Lundazi Vice Chair
73 Charles Zulu Kabulinde, Lundazi Secretary
74 Janet Mbewe Kabulinde, Lundazi Treasurer
75 Sarah Mkandawire Kabulinde, Lundazi Committee member
76 Lameck Banda Kabulinde, Lundazi Committee member
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77 Petros Nyirenda Kabulinde, Lundazi Committee member
Agro-Dealers
1. Maritina Hara Mama Hara General Dealer Agrodealer
2. Grace Nyirongo Acson Zimba Lundazi Agro Coop Ltd Agrodealer
3. Partson Sambo Nthitimila Agro- Dealer Agrodealer
4. Rubir Maimba Rubie Agro Suppliers Agrodealer
5. Banda Modester Aunt Modester Agro Dealer Agrodealer
6. Salujinga Musumali Jackson Salujinga General Dealer Agrodealer
7. Kelson Songe Takusumbwa Trading Agrodealer
8. Hamainza Kelvin Gift Mubimba Agi-Vision Agrodealer
9. Fredson Mumba Shamwele Agro-Ent Agrodealer
10. Clement Chiko Cc Enterprise Agrodealer
11. Wilfred D. Mwale Dgm Agro-Chem Agrodealer
12. Timothy Mumba Mumba Agrodealer
13. Esnala Tembo Chosani Umphawi Agro Gen Dealer Agrodealer
14. Florence Jere Majere Agro Services Agrodealer
15. Joseph Sakala Iron Sharpens Iron Agro Agrodealer
16.
Patrick Daka
Daka Farmers Home& General
Dealers
Agrodealer
17. Benadette Ngoma Aunt Bena Agro Agrodealer
18. Njovu Edwin Ulimi Niweka Agro/General Dealer Agrodealer
19. Lungu Godwin Alexander Farmers And Gardeners Shop Agrodealer
20. Dorothy Chirwa Doliha Agro&Gen Suppliers Agrodealer
21. Fidess Kasonde Mama Kasonde Agrodealer
22. Lazarous Mwale Daily Needs Agro Dealers Agrodealer
23. Phiri Davy Bwenzi La Alimi Agrodealer
24. Jacob Banda Jacob Zale Agrodealer
25. Prince Thole.B. Kabilubilu Agros Agrodealer
26. Tembo Charles Manjase Farms& Gen Dealers Agrodealer
27. Mabvuto Nkhoma Amulauzi General Dealer Agrodealer