Page 1
JUNE, 2017
CONSULTANCY SERVICES FOR CONDUCTING A MID-LINE
IMPACT ASSESSMENT OF THE KENYA MARKET TRUST
PROGRAMMES
MIDLINE IMPACT ASSESMENT REPORT FOR THE
DAIRY SECTOR
(FINAL REPORT)
Prepared By:
AFRICAN RESEARCH AND ECONOMIC DEVELOPMENT CONSULTANTS LTD (AFREDEC)
House 6, Plot LR No. 1870/366/6, General Mathenge Drive, Off Parklands Ring Road
P.O Box 32499- 00600, Nairobi Tel: +254 721650460/0721782526
Email: [email protected]; [email protected] Website: www.afredec.com
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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TABLE OF CONTENTS
TABLE OF CONTENTS ........................................................................................... I
LIST OF TABLES ................................................................................................... IV
LIST OF FIGURES .................................................................................................... V
LIST OF ABBREVIATIONS AND ACRONYMS .................................................. VI
1 EXECUTIVE SUMMARY .................................................................. VII
1 CHAPTER 1: INTRODUCTION .......................................................................... 1
1.1 Background Information ...................................................................................................1
1.2 Program Objectives ...........................................................................................................1
1.3 Program Components .......................................................................................................1
1.4 Purpose and Objectives of the Midline Evaluation ........................................................3
2 CHAPTER 2: METHODOLOGY AND APPROACHES..................... 4
2.1 Evaluation Design ...............................................................................................................4
2.2 Sampling Design .................................................................................................................5
2.2.1 Sampling for Dairy Farmers........................................................................................................................... 5
2.2.2 Sampling for the Key Informants ................................................................................................................. 7
2.3 Data Collection Methods...................................................................................................7
2.3.1 Document Review of Secondary Data Collected .................................................................................... 8
2.3.2 Primary Data Collection ................................................................................................................................ 8
2.4 Data Entry and Analysis ....................................................................................................8
2.5 Limitations of the Evaluation............................................................................................9
3 CHAPTER 3: RESULTS AND FINDINGS ........................................ 10
3.1 Introduction ..................................................................................................................... 10
3.1 Dairy Hub’s Membership................................................................................................ 10
3.2 Age of Respondents......................................................................................................... 12
3.3 Dairy Farmers’ Socio-economic and Demographic Characteristics ....................... 12
3.4 Dairy Farming Experience ............................................................................................. 14
3.5 Dairy Farming Systems .................................................................................................. 14
3.6 Herd characteristics and Dynamics .............................................................................. 15
3.7 Results for Supply Chain Component .......................................................................... 18
3.7.1 Target Group Change Level for the Supply Chain Component ........................................................ 18
3.7.1.1 Milk Production ............................................................................................................................................... 18
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3.7.1.2 Milk Marketing Channels .............................................................................................................................. 19 3.7.1.3 Volumes of Milk sold ..................................................................................................................................... 21
3.7.2 Dairy Production Costs ............................................................................................................................... 23
3.7.3 Revenues and Gross Margins from Milk production ............................................................................ 25
3.7.3.1 Farmers Access to Information and Inputs .............................................................................................. 26 3.7.3.2 Frequency and Consistency of Information Access ............................................................................... 28 3.7.3.3 Level of Satisfaction with Sources of Information .................................................................................. 28 3.7.3.4 Level of Satisfaction with Supply Chain Services .................................................................................... 29 3.7.3.5 Level of Satisfaction with Inputs Provision ............................................................................................... 30
3.7.4 Market Systems Change Level for the Supply Chain Component .................................................... 30
3.8 Results for Improving and Promoting AI Service Component ................................ 32
3.8.1 Target Group Change Level for Improving and Promoting AI Service Component ................... 32
3.8.1.1 Awareness of Accredited AI Services ....................................................................................................... 32 3.8.1.2 Usage of Accredited AI Services ................................................................................................................ 33 3.8.1.3 Cost of Accredited AI Services .................................................................................................................. 33 3.8.1.4 Level of Satisfaction with Accredited AI Services .................................................................................. 34 3.8.1.5 Perceived Benefits of using Accredited AI Services............................................................................... 35
3.8.2 Market System Change Level for Improving and Promoting AI Service Component .................. 35
3.8.2.1 Success Rate of AI Services.......................................................................................................................... 35 3.8.2.2 AI Service Providers with Improved Customer Service and Business Skills and Investing in
Promotional and Marketing Activities with Relevant Market Actors ............................................... 36
3.9 Results for Commercial Hay Production ..................................................................... 36
3.9.1 Background of Commercial Hay Production Intervention ................................................................. 36
3.9.2 Target Group Change Level for Commercial Hay Production Component .................................. 37
3.9.2.1 Awareness of Quality Assured Hay ........................................................................................................... 37 3.9.2.2 Utilization of Quality Assured Hay ............................................................................................................ 37 3.9.2.3 Perception on the Quality of the Hay Purchased .................................................................................. 38 3.9.2.4 Types of Hay Purchased ............................................................................................................................... 38 3.9.2.5 Sources of Hay ................................................................................................................................................ 39 3.9.2.6 Level of Satisfaction with Quality Assured Hay ...................................................................................... 40 3.9.2.7 Perceived Benefits of Quality Assured Hay ............................................................................................. 41
3.9.3 Market Systems Change Level for Commercial Hay Production Component .............................. 41
3.10 Results on Program’s Impact on the Farmers/Target Beneficiaries ....................... 41
3.10.1 Most Significant Changes to Dairy Farming ............................................................................................ 41
3.10.2 Contribution of Dairy Hubs/Co-operatives to Most Significant Changes to Dairy Farming ..... 42
3.10.3 Resilience Analysis ......................................................................................................................................... 43
4 CHAPTER 4 ACHIEVEMENTS OF PROGRAM INDICATORS...... 45
5 CHAPTER 5: CONCLUSIONS AND RECOMMENDATIONS ....... 55
5.1 Summary of Findings and Conclusions ........................................................................ 55
5.2 Recommendations........................................................................................................... 60
6 APPENDICES ..................................................................................... 62
6.1 Appendix 1: Program Indicators ................................................................................... 62
6.2 Appendix 2: Data Collection Tools ............................................................................... 62
6.3 Appendix 3: DFID’s Livelihood sustainability framework ......................................... 62
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6.4 Appendix 3: List of Key Informants Interviewed ........................................................ 63
6.5 Appendix 3: List of Documents Reviewed ................................................................... 64
6.6 Appendix 4: Characteristics of the Treatment Dairy Hubs ...................................... 65
6.7 Appendix 5: Characteristics of the Control Group Dairy Hubs ............................... 71
6.8 Appendix 6: Characteristics of the Treatment Agro Vet Service Providers ......... 74
6.9 Appendix 7: Characteristics of the Treatment AI Service Providers ..................... 76
6.10 Appendix 8: Characteristics of the Commercial Hay Providers .............................. 78
6.11 Appendix 9: Characteristics of the BDS Providers .................................................... 80
6.12 Appendix 10: AAER Model for Supply Chain Intervention ....................................... 82
6.13 Appendix 11: AAER Model for Artificial Insemination Services Intervention ....... 84
6.14 Appendix 12: AAER Model for Commercial Hay Production Intervention ........... 85
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LIST OF TABLES
Figure 1.1: Strategic Framework for the Dairy Sector ...................................................................... 2
Table 2.2: Sample per selected Dairy Hub ........................................................................................... 6
Table 2.3: Sample Size for Key Informants .......................................................................................... 7
Table 3.1: Membership of Dairy Hubs ................................................................................................ 10
Table 3.2: Distribution of Membership Sampled by size ................................................................. 11
Table 3.3: Dairy Program Outreach .................................................................................................... 11
Table 3.4: Household Demographic Characteristics ....................................................................... 12
Table 3.5: Mean Household Size and gender distribution .............................................................. 13
Table 3.6: Number of Members in a Household in Different Age Category by Gender ........ 14
Table 3.7: Years of experience in Dairy Farming ............................................................................. 14
Figure 3.1: Main grazing system ............................................................................................................ 15
Table 3.8: Herd Characteristics and Dynamics ................................................................................. 17
Table 3.9: Milk Yields per Cow per Day ............................................................................................ 19
Table 3.10: Percentage distribution of quantity of milk sold by type of outlet.......................... 20
Table 3.11: Volume of Milk Sold per Day .......................................................................................... 22
Table 3.12: Average costs of production (variable costs) .............................................................. 24
Table 3.13: Average Milk Revenue for Treatment Group .............................................................. 25
Table 3.14: Average Milk Revenue for Control Group .................................................................. 26
Figure 3.2: Market Information and Participation in Marketing Activities .................................. 26
Table 3.15: Sources of Information ..................................................................................................... 27
Figure 3.3: Consistency and Frequency of information ................................................................... 28
Figure 3.4: Level of satisfaction on information received ............................................................... 29
Table 3.16: Level of Satisfaction with Supply Chain Services ......................................................... 30
Table 3.17: Level of Satisfaction with Inputs Provision ................................................................... 30
Table 3.18: Performance of the Intervention Dairy Hubs .............................................................. 31
Figure 3.6: Source of awareness of Accredited AI Services ........................................................... 32
Figure 3.7: Usage of Accredited AI Services ...................................................................................... 33
Table 3.19: Agreement Scale on Satisfaction with AI Services (Treatment) .............................. 34
Table 3.20: Agreement Scale on Satisfaction with AI Services (Control) ................................... 34
Table 3.21: Benefits of using Accredited AI Services ....................................................................... 35
Table 3.22: Success Rate of AI Services .............................................................................................. 35
Table 3.23: Trends in Provision of AI Services (No. of customers)............................................. 36
Table 3.24: Hay Production ................................................................................................................... 37
Table 3.25: Proportion of Farmers that Purchase Quality Assured Hay .................................... 38
Table 3.26: Quality of Hay Purchased by Season ............................................................................. 38
Figure 3.8: Types of Hay Purchased .................................................................................................... 39
Table 3.27: Sources of Quality Assured Hay ..................................................................................... 39
Table 3.28: Agreement Scale on Satisfaction with Hay ................................................................... 40
Table 3.29: Benefits of using Quality Assured Hay from farmers’ perception .......................... 41
Figure 3.10: Most Significant Changes in Dairy Farming ................................................................. 42
Figure 3.11: Role of Dairy Hubs in Most Significant Changes ........................................................ 42
Figure 3.12: Role of Dairy Hubs in Most Significant Changes ........................................................ 43
Table 3.30: Social and Economic Benefits .......................................................................................... 44
Table 4.1: Summary of Program Achievements per Indicators ..................................................... 47
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LIST OF FIGURES
Figure 1.1: Strategic Framework for the Dairy Sector ...................................................................... 2
Figure 3.1: Main grazing system ............................................................................................................ 15
Figure 3.2: Market Information and Participation in Marketing Activities .................................. 26
Figure 3.3: Consistency and Frequency of information ................................................................... 28
Figure 3.4: Level of satisfaction on information received ............................................................... 29
Figure 3.6: Source of awareness of Accredited AI Services ........................................................... 32
Figure 3.7: Usage of Accredited AI Services ...................................................................................... 33
Figure 3.8: Types of Hay Purchased .................................................................................................... 39
Figure 3.10: Most Significant Changes in Dairy Farming ................................................................. 42
Figure 3.11: Role of Dairy Hubs in Most Significant Changes ........................................................ 42
Figure 3.12: Role of Dairy Hubs in Most Significant Changes ........................................................ 43
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LIST OF ABBREVIATIONS AND ACRONYMS
AAER Adopt, Adapt, Expand and Respond
A I Artificial Insemination
ASL Associated Steel Limited
BDS Business Development Services
CPD Continuous Professional Development
DH Dairy Hub
DTA Dairy Traders Association
ICT Information Communication Technology
ILO International labour Organization
KCC Kenya Co-operative Creameries
KMAP Kenya Market Assistance Program
KMT Kenya Markets Trust
KIIs Key Informant Interviews
Ksh Kenya Shillings
LGSEA Livestock Genetics Society of Eastern Africa
LOL Land O’ Lakes
M4P Markets Work for the Poor
MAP Market Assistance Program
M&E Monitoring and Evaluation
SACCO Savings and Credit Cooperative Organization
SME Small and Medium Enterprises
SP Service Provider
TNS TechnoServe
UK United Kingdom
USIU United States International University
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1 EXECUTIVE SUMMARY
Introduction
Kenya Market Trust (KMT) in collaboration with TechnoServe (TNS) has been
implementing a Market Assistance Program (MAP) in the dairy sector since 2012. MAP
works in partnership with the private sector and government to transform how dairy sector
markets for increased competitiveness inclusive wealth creation for all players. KMT and
TNS use the "Making Markets Work for the Poor (M4P)" approach. This approach lays
emphasis on facilitating the realignment of the incentives, capacities, relationships and rules
which govern how markets work. The program activities were expected to trigger actions
by market actors like dairy hubs, milk traders and other service providers in the dairy
sector, and therefore result in desired systemic changes. Farmers would therefore be able
to better perform and get better returns operating within an improved system. The
programs interventions are in improving milk supply chain management and structures;
addressing issues of feed quality and supply; and improving animal health and genetics
services.
The overall purpose of the midline assessment is to measure and report the progress of the
KMT MAP’s dairy sector interventions performance at midline against the set targets over
the program period, and also use the findings from the evaluations to inform and improve
sector intervention strategies. More specifically the evaluation is to measure the impacts,
outcomes, outputs, validate evaluation framework, make recommendations and inform
logical framework targets.
Methodology
The midline evaluation used a quasi-experimental design that incorporated treatment group
as well as a control group. The study did not adopt the longitudinal approach proposed at
baseline as the population of interest had significantly changed. The changes included none
participation of some of the selected dairy hubs at the baseline, dropping off of some
participants midway, addition of new participants and delays in implementing some of the
program activities. The respondents comprised dairy farmers, dairy hubs, milk processors,
private based agro-vets, A.I providers, milk traders, commercial hay producers and feed
millers that were participating in the program as at March 2016, and comparison enterprises
not part of the program.
Both primary and secondary data were collected using qualitative and quantitative tools. A
household survey was conducted with 473 dairy farming households in twelve (12)
intervention dairy hubs as well 206 individual dairy farming households in five (5) non-
intervention/control hubs. Key Informant Interview (KII) schedules were also developed to
collect qualitative data from selected informants such dairy hub managers, milk processors’
managers, agrovets, A.I providers, milk traders, commercial hay producers, feed millers and
business development service (BDS) providers. Secondary data was collected in the review
of various project documents, program M&E data and other relevant literature. Midline is
compared with data from both the KMT dairy sector baseline study and the dip stick (early
impact assessment in 2014)
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Summary of Findings
The three years of implementation of the KMAP program 56,927 farmers from KMT
Monitoring and over 85,000 farmers as estimated by this evaluation benefitted from the
program with a wide range of impacts.
At the midline, the average yield per cow per day was 8.9 litres for the two seasons within
the treatment groups, against 8.4 litres for the control groups and 7.02 liters for the dip
stick survey (2014)
The average number of dairy cows per household for the treatment group was 3 and 2 for
the control group
For treatment group, gross revenue for milk sales per cow per day averaged Ksh. 334.2
during the wet season and Ksh 286.1, net revenues of Kshs. 196.5 during the wet season
and Kshs.148.4 during the dry season with overall cost of production at Kshs. 137.7 per
cow per day or Kshs.15.5 per litre
In comparison, net revenues per cow per day for control group averaged Kshs. 123.9 during
the wet season and Kshs. 98.7 during the dry season with overall cost of production
kshs141.6 per cow per day or Kshs 16.9 per litre.
This increase in incomes enhanced the farmers’ resilience to climate change; farmers
reported that they were able to invest more in their social, natural, human, physical and
financial livelihood assets/capitals according to the DFID’s Livelihood sustainability
framework. Perception of benefits accruing from dairy farming was measured for each of the
capitals using a likert scale of 1 to 5, where 1 represents least benefited and 5 represents
most benefited and both treatment and control groups scored above average across the six
livelihood assets 3.3 and 3.0 respectively.
In terms of achievement of targets set for the program indicators, there was an over 50% achievement for all indicators except those measuring the number of DHs and processors
investing in improved customer-centric distribution and retail strategies; new product
innovations and/or marketing strategies; and improved supply chain management practices.
Supply Chain Interventions
In the supply chain component, as a result of adoption of new innovations promoted by
KMAP thorough its implementers in the private and public sector such as adoption of
improved cattle and increased use of hay led to the increase in milk yields.
Volumes of milk sold to various outlets increased by 53.3% during the wet season and 35.7%
during the dry season. The increase in volumes marketed was associated both with the
increased yields and access to more reliable markets as well as support services.
Farmers preferred selling their milk through formal channels, mainly dairy hubs as indicated
by 93% of the farmers as compared to 70% during the baseline and above the target of 80%.
This is by virtue that most farmers interviewed were members of some hub and the reason
is dairy hubs offered the farmers integrated services including advance payments, quality
feeds and AI services on check off system and extension services in some cases.
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A total of 76% of the beneficiary farmers reported improved access to information and
inputs while 70% reported improved supply chain services, all these attributed to improved
distribution and retail channels. It was however, noted that the farmers considered the
prices of milk lower while that of inputs such as AI and Hay considerably high. Notably,
these concerns were not limited to farmers in the project implementation areas but can be
generalized to farmers in the whole country.
Supply Chain - Market actor changes
Five (5) of the intervention dairy hubs and 2 processors (63.6%) had adopted ICT based
systems to improve efficiency in operations. Three (3) ICT firms had developed hotlines,
authentication and rating platforms, and that 12 agrovets were already using such platforms
Five dairy (5) hubs and 2 processors, (KCC and Lattana) were active in investing in
improved customer-centric distribution and retail strategies and in improved supply chain
management practices, and another five (5) dairy hubs “crowded in”
As a result, dairy hubs exposed to professional hub management services continued to
improve their business operations and thus improving the performance. Overall nine (9) of
the intervention dairy hubs had membership numbers growing by 8% to 317%. The quantity
of milk handled also increased in seven (7) of the dairy hubs by 11% to 94%. Eventually,
annual turnovers had increased by between 2% and 100% in eight (8) of the dairy hubs.
Artificial Insemination
Usage of accredited A.I services has more than doubled from 35.3% at baseline to 72.7% at
the midline, thus exceeding the target set by 18%. Farmers that were strongly satisfied with
quality, availability and trustworthiness were 27.8%, 31.2% and 32.6% respectively as
compared to 15%, 19% and 19% respectively at the baseline.
According to farmers’ perceptions, benefits from use of accredited A.I services included
increased milk production for offsprings (77.5%); healthier calves (75.7%); high conception rates (68.6%) and increased incomes (63.2%).
The average price of A.I services was Ksh 1,578 against a set target of Ksh.1, 316. It was
however, noted that farmers were using more exotic semen including sexed semen which
was more expensive compared to the local semen.
These efforts bore fruit because Accredited AI service providers through KMAP’s
engagements with LGSA reported increased AI services provision by 61% between 2013 and
2016, implying an increase in number of farmers adopting A.I services.
Commercial Hay Production
Awareness of farmers on quality assured hay has increased from 9.1% at baseline to 41% by
midline survey. On average 77% (24,083) 1 of the beneficiary farmers accessed quality
assured hay during both the wet and dry seasons with 80% indicating they would be willing
to purchase hay as long as the quality is assured. According to the farmers’ perceptions, the
main benefits from the use of quality assured hay include: increased milk production (85.1%);
1 Exceeded the target set by 71%
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increased incomes (67.2%); healthier cows (66.7%) and less variation in milk production
(42.5%).
Two (2) commercial hay producers (Hay N Forage Company and Sochon) have shown the
viability of commercial hay farming. Scale up activities include New KCC promoting linkages
between smallholder farmers and commercial hay producers while the County
Governments of Laikipia and Narok had intentions to finance commercial hay production.
Recommendations
To further improve the implementation of the program, the following is recommended:
a) The dairy hubs are the most important source of inputs and marketing channels for
the farmers. In view of this, it is important for KMAP to continue empowering the
dairy hubs to be viable business entities which would be instrumental in propelling
smallholder farmers from poverty;
b) The use of key service providers for continuous professional development of dairy
hubs, milk traders, agrovets and other actors was noted as a good approach through
which challenges in supply chain management as well as delivery of A.I and animal
health services can be addressed. KMAP should therefore promote this approach to
the wider stakeholders in the dairy industry as a best practice and for wider impacts;
c) Benchmarking should be enhanced for dairy hubs and market actors that have
adopted and are implementing the program interventions well so that other actors
may learn from them. This may be done by developing case studies on the successful
dairy enterprises and organizing other dairy enterprises to learn from them.
d) The main challenges experienced by the AI providers are inadequate supplies, lack of
specialized semen handling facilities and equipment’s and facilities as well as
perception by farmers that AI services are expensive; and therefore slow uptake of
A.I in some areas. There is therefore need to provide assistance to the AI service
providers to acquire semen handling facilities and equipment as well as offering more
training and information on modern A.I services to dairy farmers focusing on the
value proposition for use of A.I services; e) KMAP in association with its partners should make efforts in enhancing appropriate
partnerships between the DHs, processors and private sector players as well as the
County Governments so as to improve on supply chain management, marketing and
retail strategies, improved customer-centric distribution and retail strategies as well
as scaling up use of ICT to improve on the services provided to farmers;
f) To ensure sustainability of the program interventions there should be concerted
efforts to involve the County Governments more intensely in the implementation of
the KMAP program. This is because implementation of livestock programs is a
devolved function;
g) In order to effectively inform the program’s theory of change, it is recommended
that for future evaluations, the same methodology applied in the midline assessment
should be applied in the end-line assessment to enhance comparability while the
findings from the midline assessment should be the basis for the setting the targets
for the end-line evaluation.
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1 CHAPTER 1: INTRODUCTION
1.1 Background Information
As at the end of 2016, Kenya Market Trust (KMT) in collaboration with TechnoServe (TNS)
has been implementing a Market Access Program (MAP) in the dairy sector since 2012.
Initially, SNV Netherlands and TechnoServe both had interventions to implement within the
dairy sector before -the latter- was awarded implementation of the entire dairy work while
SNV focused on water. The initial phase of the program ran from 2012 to 2015.
Technoserve’s engagement included three key components: Improving milk Supply chain
management and structures; addressing issues of feed quality and supply; and improving
Animal health and genetics services. There were however, delays in the initial stages of the program activities with only the feed component starting in 2012 though very slowly due to
contracting issues between KMT and TNS, while the Artificial Insemination (AI) component
started in May 2013. Activities within the supply chain component started informally in 2014
but formalized in 2015.
1.2 Program Objectives
The MAP program was designed to work in partnership with the private sector and
government to transform how dairy sector markets work so that they could become more
inclusive and more competitive. To achieve these objectives, the programme applied the
"Making Markets Work for the Poor (M4P)" approach. This approach is based on facilitating
the realignment of the incentives, capacities, relationships and rules which govern how
markets work. Further, KMT believes that the program activities trigger actions by other
actors and partners and therefore result to systemic changes that are reflected by the
actions taken by the partners or other stakeholders. This is as reflected within an Adopt,
Adapt, and Expand and Respond (AAER) framework.
1.3 Program Components
The program comprises of three broad components namely:
• Supply chain management and structures;
• Feed quality and supply;
• Animal health and genetics services.
One of MAP’s primary interventions in dairy is catalyzing the improvement of practices and
skills of milk supply chain management. This is done through improving both the formal and
informal milk supply chains. The formal milk supply chain the interventions include: Support
dairy co-operatives/dairy hubs obtain professional management and ICT services: Improve
retail and distribution of feed, breed and vet services through dairy co-operatives/dairy
hubs; Support investments in energy efficiency and optimization programs by dairy
enterprises; Support investments by processors in volume and quality based milk payment
systems. These interventions are expected to lead to increased professionalism in dairy
enterprise management through professional management services, new investors,
turnaround, energy efficiency and integration of better input services, products and
practices and improvements in the distribution and retailing strategies of key dairy inputs
and services through milk aggregation centers.
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Informal milk supply chain is the flow of milk from the producer to the end consumer
without undergoing any type processing (KDB, 2016). The milk in the informal sector is sold
raw which poses a safety concern. MAP has developed and is facilitating business strategies
to support the sale of safe, affordable milk by traders as well as enabling and increasing
access to quality dairy inputs by the farmers delivering to the informal chain. This
intervention seeks to create incentives to drive formalization from within the market system
through promoting investments by the traders to supply quality safe milk to the market and
from processors to capture informal milk and enhancing growth of interconnected services
(i.e., vet, AI, feed, etc.) to the farmers delivering to the informal sector.
On access to feeds and supplements, the project anticipated increased access to quality and
affordable feeds and supplements. This was to promote high productivity as well as reduce
fluctuations in milk production especially during dry seasons. The interventions in this
component include: Support commercial hay producers to improve production, expand
their business and adopt faster growing fodders (hay); support feed manufacturers to
develop formulation strategies based on quality fodder, concentrates and supplements; and
build the capacity of labs to market and co-brand quality feed.
The project also worked to improve practice in artificial insemination (AI) and animal health
services and ensure greater rural penetration through reduced cost and better
infrastructure. The Dairy sector intervention’s strategy is summarized in the strategic
framework in figure 1.1 below.
DAIRY SECTOR THEORY OF CHANGE
Facilitate change in distribution and retailing strategies of breed,
feed and veterinary services
Facilitate the turn around of underperforming dairy hubs, and support
alternative supply chain investment models
Professional, customer-oriented retail distribution startegies in use
by breed, feed, and veterinary service providers
Dairy hubs and other dairy processors are managed effficiently and have
improved supply chains
Increased number of farmers using improved and certified breed, feed and veterinary
services
Improved quality and quantity of milk supply
Increased demand for quality milk in formal markets
Increase in milk sales in formal milk markets
Increased dairy farmersdisposable income
IMP
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Figure 1.1: Strategic Framework for the Dairy Sector
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1.4 Purpose and Objectives of the Midline Evaluation
The overall purpose of the midline assessment is to measure and report the progress of the
KMT MAP for the dairy sector at midline against the set targets over the program period,
and also use the findings from the evaluations to inform and improve sector intervention
strategies. Prior to this assessment, KMT had conducted a baseline assessment in 2013 and
an early assessment in 2014 as a preamble to the midline and end-line assessment.
The objectives of the midline assessment are to:
i. Identify and measure impact among programme beneficiaries of the dairy
sector's work through an assessment of the selected market actors;
ii. Measure and validate outcomes among programme beneficiaries of the dairy
sector interventions through this assessment of the selected market actors
and beneficiaries;
iii. Measure and validate outputs among the selected market actors of the dairy
sector interventions through this assessment;
iv. Validate the framework provided from the baseline surveys and propose
improvement if any for future impact assessment/evaluations (end-line
evaluation);
v. Identify lessons learned and make recommendations to inform current KMT
dairy sector strategies, and future (climate change mainstreaming?)
programming in the application of market systems approaches in Kenya and
other countries; and
vi. Inform KMT’s logical framework targets.
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2 CHAPTER 2: METHODOLOGY AND APPROACHES
2.1 Evaluation Design
At the baseline, the evaluation design for dairy sector was based on a quasi-experimental design
where treatment and control groups were established. This approach allows for statistical
attribution of the causal impacts of the program on outcomes for the participants by collecting
before-and-after measures on outcomes of interest from both the treatment and the
comparison groups (Reichardt C.S, 2009)2.
At the time of conducting the baseline, a total of 15 dairy hubs were sampled as the treatment
groups while 14 dairy hubs were sampled as control groups. At this point, the comparison
group was used to represent the counterfactual i.e., what would have happened to the beneficiaries in the absence of the program. It was however, noted that this approach often
suffers from contamination of the comparison groups3.
The baseline also proposed that the research design for the midline and the end line include
longitudinal survey4 where the same respondents that were sampled at the baseline would be
sampled at the midline. Additionally, the baseline proposed to use of propensity score matching
(PSM) and difference in difference (DID)5 approach to measure the key impacts from the
program. It was however, noted that a lot of changes occurred during the first phase of project
implementation such that some of the targeted businesses during the baseline were no longer
participating in the program while new ones that were not initially targeted may have joined.
Further, some businesses that participated in the initial years have since dropped out for one
reason or another. These dynamics implies that it would be difficult to undertake a longitudinal
survey at the midline as had been envisioned at the baseline.
It is to be noted that although the baseline survey of 2012 proposed that a quasi-experimental
design using a longitudinal based survey for both the midline and the end line surveys (where
midline and end line were to target same respondents as those in the baseline), the
methodology at the midline was slightly adjusted to take care of the many changes that had
occurred between the baseline and midline. These changes included none participation of some
of the selected dairy hubs at the baseline, dropping off of some participants midway, addition of
new participants and delays in implementing some of the program activities. As a result the
study was not able to compare some of the indicator values from the baseline with the midline
values. In addition, some approaches used in the baseline such as the propensity score matching
(PSM) would not be possible at the midline. This necessitated the use of the dip stick (early
impact assessment in 2014) survey data as the baseline values for some of the indicators. The
2 Reichardt C.S, The SAGE handbook of quantitative methods (2009). 3 Ruffer, Tim and Elise Wach (2013) “Review of M4P Evaluation Methods and Approaches” ITAD Report Commissioned by the UK Department for International Development 4 Where the same respondents for the baseline are interviewed at the midline and the end line 5 This measures the net effect of the program interventions by netting changes from the control group from the changes in the treatment group so as to arrive as the “net change”
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
5
midline also used the difference in difference approach to compare changes over time and
across the treatment and the control group for the key indicators to the extent possible.
The midline evaluation still used a quasi-experimental design as proposed in the baseline. This
design involved a treatment and a control group. The preference of the design was so as to
allow the measurement of changes by comparing the control and the treatment groups as well
as over the implementation period. However, after noting the various changes that have
occurred between the baseline in 2012 and the midline in 20166, the methodology for the
midline disregarded the use of same respondents as those used in the baseline as well as the
use of PSM. In addition, the use of DID was applied to assess the various indicators only to the
extent possible. The overall indicators that were assessed are presented under Annex 1. The
midline also adopted the 2014 dipstick survey to fill in gaps for information that could not be
found in the baseline report of 2012. Further, the midline evaluation made a few additions
including a re-definition of the target respondents (either as the treatment or the control
group). For the purposes of the midline evaluation, the treatment group was defined as those
businesses that were still participating in the program as at March 2016. These businesses
included dairy farmers, dairy hubs, milk processors; private based agro-vets, A.I providers, milk
traders, commercial hay producers and feed millers.
2.2 Sampling Design
2.2.1 Sampling for Dairy Farmers
The midline evaluation sampled individual farmers/households from 14 out of 26 participating
dairy hubs for the treatment group and 6 control dairy hubs that were selected in consultation
with the client7. The selection of the dairy hubs to be interviewed was based on the following
criteria:
(i) Target components - Depending on the interventions that the program worked with.
These include milk value chain, feeds and A.I & genetics (1st Strata).
(ii) Regional distribution - Key regions include Central, Eastern and Rift valley (2nd Strata).
(iii) Random selection of dairy hubs.
(iv) Listing of active members of the dairy hubs stratified according to the milk collection
centres.
(v) Random selection of farmers from the list of farmers.
The study selected 14 treatment dairy hubs and 6 control dairy hubs8, totaling to 20 dairy hubs.
In each dairy hub selected, the numbers of milk collection centers per route were determined
with assistance from the dairy hub managers. After this, dairy farmers were randomly selected
from each of the milk collection centers.
6 KMT 2016 Dairy impact assessment inception report 7 The sampling was done through the guidance of KMT M&E Team and Technoserve 8 The consultant had proposed 14 control hubs but it was difficult getting all the 14 dairy hubs due to
contamination.
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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The sample size was calculated using the Yamane (1967:886) formula as below.
n =N/1+N (e)2
Where:
n is the sample size,
N is the population size. For this study, N was 91,865 (This was the number of farmer
beneficiaries of MAP as at March, 2016)9
e is the desired level of precision (For this study, we will use ±4%)
n=91,865/1+91,865(0.04)2= 807 farmers
This yielded a total sample size of 807 dairy farmers. This sample size was shared equally for
each dairy hub. This implied that for each dairy hub, 40 farmers were randomly selected to
participate in the study, totaling to 800 farmers (560 for the treatment group and 240 for the
control group).
However, the achieved sample size was 679 dairy farmers (473 for the treatment group and
206 for the control group). The main reason for the non-achievement of the proposed sample
of 800 farmers was because some of the dairy hubs such as Ndumberi and Kikuyu dairy
cooperatives were not willing to participate in the study10. In addition, Gatundu Dairy farmers’
cooperative was no longer in existence11. The achieved sample size per dairy hub is as
illustrated in Table 2.2 below.
Table 2.2: Sample per selected Dairy Hub
Comp
onent
Region Selected
Treatment
dairy hubs
Propos
ed
sample
size
Achieve
d
sample
size
Recommende
d Control
dairy hub
Propose
d
sample
size
Achieve
d
sample
size
Milk
supply
chain
Central Limuru 40 33 Kabete 40 41
Gatamaiyu 40 40 Kikuyu12 40 0
Gatundu
South13
40 0
Eastern Mkulima
Bora
40 40
Tumaini 40 40
Rugendo 40 40
Rift valley Torongo 40 39 Olbutyo 40 42
Ololunga 40 40
A.I & Central Nyala 40 39 Umoja 40 43
9 Source: Kenya Market Assistance Programme project closure report: Jan 2012 - Mar 2016 10 Ndumberi Dairy Co-operative Society and Kikuyu Dairy Co-operative Society 11 Gatundu Dairy Farmers Co-operative Society seized operations and did not participate in the program 12 Dairy hub not willing to participate 13 Dairy hub no longer exists
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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Comp
onent
Region Selected
Treatment
dairy hubs
Propos
ed
sample
size
Achieve
d
sample
size
Recommende
d Control
dairy hub
Propose
d
sample
size
Achieve
d
sample
size
Geneti
cs
Njabini 40 40 Nandrasi 40 41
Karati 40 40 Kahuru 40 39
Eastern -
Rift valley Siongiroi 40 42
Feeds Central Nyala Same as
above
Same as
above
Ndumberi14 40 0
Eastern Meru
Multipurpose
40 40
Rift valley -
Total 560 473 240 206
2.2.2 Sampling for the Key Informants
Key informants for this study were identified purposively based on the roles they played in the
program All the hubs that had been identified for dairy farmer sampling were enlisted for Key
Informant Interviews to understand the performance changes in those hubs which lay platform
for improved farmer performances. See summary in table 2.3 below.
Table 2.3: Sample Size for Key Informants
Category of respondents Targeted sample size Achieved sample size
Hub officials/ board members 21 16
Agro-vets 5 10
Independent A.I providers 21 10
Informal Milk buyers/ traders 2 2
Milk processors 4 2
Commercial hay producers 4 3
Feed millers 1 1
Hay input suppliers 1 0
Management firms 6 4
Total 65 51 Note: The names and contacts of organizations interviewed are in appendix 2
2.3 Data Collection Methods
Qualitative and quantitative evaluation techniques were employed to generate as much
information as necessary for assessing project performance as well as drawing lessons from the
project implementation. The main methods used were: document review; in-depth Key
Informant Interviews (KIIs); and household surveys.
14 Dairy hub not willing to participate
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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2.3.1 Document Review of Secondary Data Collected
Secondary data collection included a desk review of various project reports, M&E data and
other relevant literature. Literature reviewed provided some of the necessary information
required in achieving the objectives of the evaluation such as key monitoring data. Literature
reviews also allowed for identification of information gaps which was then incorporated in the
data collection tools developed. The findings of the desk review were triangulated with the
primary data. The list of documents reviewed is presented in Appendix 3.
2.3.2 Primary Data Collection
Primary data was collected using both quantitative and qualitative techniques depending on the
target respondents. Quantitative techniques using household survey questionnaires were used
to collect data from dairy farmers while qualitative techniques using key informant interviews
(KIIs) guides were used to collect in-depth data from key informants summarized in table 2.2
and appendix 2.
Prior to data collection, enumerators and supervisors were taken through a comprehensive
two-day training covering all aspects of data collection including a question-by-question review
of the data collection tools. Thereafter, a pre-test was conducted for the farmer questionnaire
in Gatamaiyu Dairy Co-operative, where 10 farmers were interviewed. The purpose of the pre-
test was to ensure that the tools were able to effectively capture the required data to meet the
objectives of the evaluation. To ensure data quality, each region had a supervisor overseeing the
data collection. Supervisors also conducted call backs, back checks and spot checks.
2.4 Data Entry and Analysis
Primary quantitative data was entered into Statistical Packages for Social Sciences (SPSS)
software by qualified data entry clerks. The data was cleaned to check for missing values,
incorrectly entered data, inconsistent data and outliers. The data was cleaned by running
frequencies on all variables in the dataset. From the frequency information “missing data” and
the extent to which data is missing was identified. Variables that have been entered incorrectly
were also identified by looking at the “value labels”. Measures of central tendency (mean) and
measures of dispersion (standard deviation) were also compared. Measures of distribution
(skewness and kurtosis) as well as visual inspection were used to show whether the data was
normally distributed.
Quantitative data was then analyzed to generate the required statistics using different methods
such as frequencies, descriptive statistics, cross tabulations and multiple responses analysis,
amongst others. Where necessary, data was re-coded and new variables generated, split or
merged to arrive at the required results. Analyzing the secondary and qualitative data involved
content analysis by reading through the interview or focus group transcripts and other data,
developing codes, coding the data, and drawing connections between discrete pieces of data.
We went through all the key informant interviews with an eye for common themes, categories,
and patterns.
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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To improve the quality (validity and reliability) of data, triangulation (comparison of data with
other sources), was applied as necessary.
2.5 Limitations of the Evaluation
Major limitations for the midline survey included the following:
i. The nature of the KMAP approach involves players willing to work with the program
during its implementation. It was noted that for some of them, engagement naturally
came to an end as the intended purpose was achieved while others dropped out of the
interventions prematurely. This meant that some of these respondents could not be
reached as there were no longer working with the program. To address this, the
midline study had to redefine the treatment and the control groups at the midline.
ii. It was also noted that some treatment groups were new entrants who came on board in
the later years of program implementation. While adaptation and some response started
happening in line with the KMT’s systemic change model, a baseline was not conducted
for the new baseline. This meant that comparison between the baseline values and the
midline values became difficult and therefore the use of quasi-experimental design
(QED) as envisaged in the baseline study was limited. Similarly, the use of the difference
in difference approach was only limited to indicators whose baseline values were
available. To address this challenge, the study approach was adjusted during the inception phase of the midline survey in consultation with KMT and TNS to enable
capture the real impacts of the program. For example, the dip stick survey of 2014 was
to be used in some instances as the baseline value. It is further recommended that for
future evaluations, the same methodology applied in the midline assessment should be
applied in the end-line assessment to enhance comparability while the findings from the
midline assessment should be the basis for the setting the targets for the end-line
evaluation.
iii. There was reluctance from some of the targeted respondents to participate in the
midline study. This not only meant that the study was unable to meet the expected
sample size but also resulted to incomplete information. To address this, the study
relied on secondary data mainly from KMT and TNS where information was not
available from primary respondents.
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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3 CHAPTER 3: RESULTS AND FINDINGS
3.1 Introduction
This chapter presents the key findings of the midline impact assessment study. The first section
describes the dairy farmers’ demographic and household characteristics, dairy hub
characteristics and dairy farming dynamics. This is then followed by the key findings on the
program components namely: supply chain; improving and promoting A.I service; and
commercial hay production. This is discussed along the program aspects of target group change,
market systems change and program impacts.
3.1 Dairy Hub’s Membership
The membership of the dairy hubs involved in the study is summarized in Table 3.1 below.
From the findings, it was evident that all the treatment dairy hubs, (except Tumaini which had
retained the same membership), exhibited a growth in membership ranging from 8% to 317%
between the years 2013-2015. The control dairy hubs also exhibited a 4% to 100% growth in
the number of members during the same period.
Table 3.1: Membership of Dairy Hubs
Treatment Dairy
Hubs
Year % growt
h 2013-2015
Control Dairy
Hubs
Year % growt
h 2013-2015
2013 2014 2015 2016 2013 2014 2015 2016
Nyala 10,000 10,000 11,963 12,671 27% Kabete 2,268 2,311 2,364 2,367 4%
Njabini 0 500 610 680 36% Olbutyo 0 0 400 1384 59%
Karati 500 700 750 720 44% Umoja 495 526 692 756 40%
Torongo 2,800 2,845 2,892 3,037 8% Nandaras
i
110 120 130 134 18%
Siongiroi 9,690 10,350 11,228 12,215 26% Kahuru 62 124 124 124 100%
Tumaini15
160 160 160 0%
Limuru 9,000 9,500 9,800 10,365 15%
Mkulima16 Bora
146 250 625 644 341%
Rugendo17 0 0 0 208
Gatamaiyu 200 300 350 400 100%
Olololung’a 130 80 120 140 8% Total 32,46
6 34,68
5 38,49
8 41,24
0 61%
2,935
3,081
3,710
4,765
Source: Dairy hubs’ managers’ interviews
15 Tumaini started operations in 2014
16 Was registered in 2012 but started operations in 2013 17 Rugendo started operations in 2008 (Rugendo dairy alliance as a community project) collected upto 2014 then
stopped. In 2015 it was transformed into a cooperative but only resumed milk collection operations in Feb 2016. Membership records between 2008 and 2014 are therefore missing.
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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Dairy hubs exhibited different numbers of membership based on the years they have been in
operation where older hubs had higher membership numbers. Based on membership, the hubs
were divided into 3 categories namely: small, medium and large as in Table 3.3 below
Table 3.2: Distribution of Membership Sampled by size
Size of the Hub Name of the Hub Membership Average membership Proportion
Large Hubs Nyala 12,671 9,572 36%
Singiroi 12,215
Limuru 10,365
Torongo 3,037
Medium Hubs Karati 720 675 27%
Njabini 680
Mkulima Bora 625
Small Hubs Gatamayu 300 202 36%
Rugendo 208
Tumaini 160
Ololulunga 140
Using the distribution of the hubs by size and percentage share, and extrapolating from the
KMT data indicating a total of 23 organizations18 that participated in the dairy sector
interventions, this translates to a total of 85,980 members as in Table 3.3.
Table 3.3: Dairy Program Outreach
Size of the Hub Proportion Number of
organizations
Average Membership Total
Membership
Large Hubs 36% 8 9,572 80,057
Medium Hubs 27% 6 675 4,234
Small Hubs 36% 8 202 1,689
Total
85,980
Using this approach, the impact outreach numbers are much higher than the KMT reported
numbers 56,927 beneficiaries by the end of March 201619.
Notes:
(i) *Meru Multipurpose beneficiaries could not be well captured since the cooperative is made up of member
hubs
(ii) *Feed component was implemented in Nyala and Meru Multipurpose dairy hubs (iii) Improvement and promotion of AI services was implemented in Nyala, Njabini, Karati and Siongiroi hubs (iv) Formal supply chain interventions were implemented in Limuru, Gatamaiyu, Mkulima bora, Tumaini, Rugendo,
Torongo and Ololulung’a dairy hubs (v) Targeted Informal supply chain dairy hubs were Kabete, Kahuru, Nandarasi, Olbutyo and Umoja dairy hubs (vi) Numbers include households served through the informal supply chain
18 Includes dairy hubs, commercial hay and forage producers, County governments and processors 19 Source: KMT Dairy sector tracker 2016.
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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3.2 Age of Respondents
The average age of the respondents was 46 years with a minimum of 18 and a maximum of 88
years. Out of the total number of respondents, 164 (24.4%) were aged between 18 and 35
years (youth), 342 (50.4%) were aged between 36 and 55 years while another 24.7% were aged
above 56 years.
3.3 Dairy Farmers’ Socio-economic and Demographic Characteristics
This sub-section illustrates the socio-demographic characteristics of the dairy farmers that
participated in the evaluation based on aspects such as sex, marital status, education, and employment, sources of income, household size and age. It is important to understand the
demographic and socio-economic characteristics of dairy farming households as these influence
farming decisions, choice and adoption of innovations. The percentage for male-headed
households was higher in the treatment group (66%) compared to the control group (52%) see
Table 3.4.
Table 3.4: Household Demographic Characteristics
Characteristic Treatment Control
N % N %
Sex of the Household Head
Male 311 66 107 52
Female 162 34 99 48
Sub-Total 473 100 206 100
Relationship of respondent with head of household
Head of household 318 67 127 62
Spouse 116 25 63 31
Son 20 4 4 2
Daughter 4 1 9 4
Parent 8 2 2 1
Sibling 4 1 0 0
Employee 3 1 1 1
Sub-Total 473 100 206 100
Marital Status of the respondent
Married 389 82 157 76
Single 52 11 26 13
Separated 4 1 1 1
Divorced 2 0 3 1
Widow/Widower 26 6 19 9
Sub-Total 473 100 206 100
Highest level of Education
None 20 4 14 7
Adult Literacy 30 7 7 3
Some Primary 36 8 34 17
Completed Primary 121 26 53 26
Some Secondary 51 11 20 10
Completed Secondary 132 28 52 25
University 48 10 20 9
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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Characteristic Treatment Control
N % N %
Vocational Training 35 7 6 3
Sub-Total 473 100 206 100
Employment of household head
Farmer 376 80 180 87
Own Business 46 10 11 5
Formal Employment 36 8 9 4
Informal Employment 15 3 6 3
Sub-Total 473 100 206 100
Highest source of income
Production and sales of cereals, pulses and tubers 24 5 15 7
Production and sales of vegetables 28 6 13 6
Production and sales of fruits 9 2 0 0
Sale of milk 300 66 143 71
Production and sales of livestock and other livestock products 23 5 1 1
On farm casual labor (On -Farm kibarua) 2 1 2 1
Off-farm labour (Non-farm kibarua) 3 1 3 2
Salaried labour 42 4 10 5
Business activities 22 5 14 7
Remittance (receiving money from others 1 1 0 0
Sub-Total 454 100 201 100
Source: Dairy farmers’ household survey
The farmers interviewed in the household survey were majorly heads of households (67% for
treatment and 62% for the control). These heads of the households were mostly male and were
the owners of the dairy enterprises. Majority of the respondents were also married (82% for
the treatment, 76% for the control), and had completed primary education levels and above
(81% for treatment, 73% for the control). The level of literacy is a crucial indicator to the
adoption of improved technologies as it enables target farmers to discern the importance of
such technologies. The main occupation for the household heads was farming. Nonetheless, it is
worth noting that the percentage was higher under the control group (87%), compared to the
treatment group (80%). Sale of milk was the highest source of income for majority of the
treatment (66%) and control group farmers (71%). This implies that dairy farming remained a
very important enterprise to the communities in the areas under review.
On average, there were 3 males and 3 females in the household; an average total of 6
household members under the treatment group and 6 members in the control group (Table
3.5).
Table 3.5: Mean Household Size and gender distribution
Treatment Control
N Mean N Mean
Number of male persons in the household 473 3 206 3
Number of female persons in the household 473 3 206 3
Total number of households 473 6 206 6
Source: Dairy farmers’ household survey
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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The number and age distribution of household members is often used as an indicator of labour
availability within a household, and therefore a determinant of whether the family would adopt
the technology or not. The most active age group in terms of labour provision would generally
fall between 18 and 64 years. The average number of household members aged between 18 to
64 years in each household was 2 persons for both the treatment and control groups, implying
that in each household, there were two members within the active labour force age group
(Table 3.6).
Table 3.6: Number of Members in a Household in Different Age Category by Gender
Males Females
N Mean N Mean
Treatment
Below 5 years 142 1 113 1
6-17 years 247 2 234 2
18-35 years 245 2 262 1
36-64 years 314 1 279 1
Over 64 years 45 1 42 1
Control
Below 5 years 51 1 49 1
6-17 years 86 1 87 1
18-35 years 107 1 113 1
36-64 years 94 1 99 1
Over 64 years 25 1 25 1
Source: Dairy farmers’ household survey
3.4 Dairy Farming Experience
On average, the farmers interviewed had 12 years of experience in dairy farming, for both the
treatment and control group (Table 3.7). Men had more years of experience in dairy farming
compared to their female counterparts averaging 13 years for male and 12 years for female for
both the treatment and control groups. The more experience of males in practicing dairy
farming is attributable to the fact that the dairy enterprise is generally male dominated mainly
because it is considered a capital intensive enterprise, which often women farmers do not have
equal access to.
Table 3.7: Years of experience in Dairy Farming Type of Group Male N Female N Both N
Treatment 13 311 12 162 12 473
Control 13 107 12 99 12 206
Source: Dairy farmers’ household survey
3.5 Dairy Farming Systems
The main production systems amongst the treatment group was zero grazing, 69% of the
households kept their animals using this system (Figure 3.1) as compared to 65.8% during the
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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baseline study. For the control group households, semi-zero system was the most popular (42%
percent). This is not unusual given the areas where sampling was done. Majority of dairy
farmers in Kenya practice zero or semi-zero grazing systems for efficient milk production (Bebe
et al., 2003)20.
Figure 3.1: Main grazing system
Source: Dairy farmers’ household survey
Free range grazing system was least popular amongst the three grazing systems for both
treatment and control groups. The higher number of farmers practicing zero grazing in the
treatment group could be attributed to adoption of new innovations especially those that were
introduced by KMAP especially on quality feeding. Additionally, the areas sampled are
predominantly high potential areas where dairy production adopts intensive systems. The key
informants confirmed that most farmers fed their dairy cows with hay, silage and Napier grass
either under zero grazing or semi zero grazing.
3.6 Herd characteristics and Dynamics
Table 3.7 gives a detailed description of the herd dynamics in the last one year. Herd sizes
varied from one hub to another with Ololung’a, Torongo and Siongiroi hubs having the highest
herd sizes of 16, 12 and 11 respectively. Amongst the control group, the largest herd size was
in Olbutyo with a total of 8 while Nandarasi and Karuhu hubs had 7 each. The average herd size
was 9 for the treatment group and 7 for the control group.
On average, the dairy farmers within the treatment group had an average of 5 milking cows,
including 3 that were being milked and 2 that were dry as at the time of the survey while those
within the control group had an average of 4 including 2 that were being milked and 2 that
were not being milked as at the time of the survey. In addition, farmers in the treatment group
had an average of 4 calves including 2 male and 2 female. The average number of female calves
20 Bebe, O.B., Udo, H.M.J., Rowlands, G.J., Thorpe, W., 2003 Smallholder dairying systems in the Kenya highlands:
cattle population dynamics under increasing intensification. Livest. Prod. Sci. doi:S0301-6226(03)00013-7
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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within the control hubs was 2 and 1 for the female calves making an average of 3 calves. The
lower number of calves in the control group can be associated with the lower number of
mature cows. It is also an indicator of lower herd growth rates.
The number of cows is an important factor in dairy production; however the breed
composition is even more important. Most farmers both in the treatment and control groups
kept improved breeds of cows, with very few keeping pedigree cows (Table 3.8). Nonetheless,
there were more farmers in the treatment group rearing pedigrees than in the control group.
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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Table 3.8: Herd Characteristics and Dynamics Categ
ory
Herd Characteristics Limu
ru
Gatama
iyu
Mkuli
ma bora
Tumai
ni
Rugen
do
Toron
go
Ololun
ga
Nya
la
Njabi
ni
Kara
ti
Siongi
roi
Meru
Multipurpose
Avera
ge
Treatment
Number of Cows Currently Milked
4 2 2 2 2 5 6 3 2 2 4 2 3
Number of Cows not Currently Milked
2 1 1 1 1 3 3 3 1 2 3 1 2
Number of Female Calves Currently Owned
2 1 1 1 1 3 4 2 2 1 3 1 2
Number of Male Calves Currently Owned
2 1 1 1 1 1 3 1 2 1 2 1 2
Total Average number
of cows
11 6 5 5 5 12 16 9 7 6 11 6 9
Name of dairy Hub Kabe
te
Olbutyo Umoj
a
Nandar
asi
Kahur
u
Avera
ge
Control Number of Cows
Currently Milked
2 2 2 2 3 2
Number of Cows not
Currently Milked
1 2 2 2 2 2
Number of Female Calves
Currently Owned
1 2 1 2 1 2
Number of Male Calves
Currently Owned
1 2 1 1 1 1
Average Herd size/hub 5 8 6 7 7 7
Source: Dairy farmers’ household survey
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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3.7 Results for Supply Chain Component
The expected outcome of KMAP’s supply chain intervention is to enhance effectiveness and
efficiency of milk value chain actors for eventual benefit of small holder farmers. This is to be
done through formal and informal supply chain interventions. Formal supply chain interventions
included: supporting dairy co-operatives/dairy hubs obtain professional management and ICT
services: improving retail and distribution of feed breed and vet services through dairy co-
operatives/dairy hubs; supporting investments in energy efficiency and optimization programs by
dairy enterprises; and supporting investments by processors in volume and quality based milk
payment systems.
Informal supply chain interventions include: supporting the development of structures to
support sale of safe, quality and affordable milk by informal milk traders; supporting traders to
improve milk collection and input supply systems and infrastructure: working with equipment
providers to introduce payment plans and credit options for the informal milk traders. For
purposes of discussing the findings of the midline evaluation, formal and informal supply chain
intervention findings will be discussed together for the levels of target group change and market
system change. The impacts for all the components will be discussed at the last section of the
findings.
3.7.1 Target Group Change Level for the Supply Chain Component
3.7.1.1 Milk Production
All the efforts of KMAP project should culminate to increased productivity and efficient
functioning of the milk market markets for the benefit of the smallholder farmers. Table 3.9
shows the milk production under the treatment and control groups in various seasons of the
year. Within the treatment groups, the average yield per cow per day was 9.7 litres during the
wet season and 8.0 litres during the dry season; averaging 8.9 litres for the two seasons. This
was 16.8% short of the targeted 10.7 litres. The average yields per cow per day for all seasons
were higher at the midline at 8.9 litres than at dip stick (early impact assessment) in the year
2014 which was 7.02 litres.
The average number of dairy cows for the treatment groups was 3. This therefore meant that
the daily milk production for a household within the treatment group was 29.1 litres during the
wet season, 24 litres during the dry season and an average of 26.7 litres for the two seasons.
The higher amount of milk produced in the treatment group was largely attributable to the
program interventions such as quality feeding and use of and better management of improved
breeds21.
The average number of dairy cows for a household within the control group was 2 with the
average daily yields being 9.3 litres per cow per day during the wet season and 7.5 litres during
the dry season; averaging 8.4 litres for both seasons. This meant that the total daily milk yields
21 This was reported by the dairy hub managers
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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per household per day was therefore 18.6 litres for the wet season, 15.0 litres for the dry
season and an average of 16.8 litres for both seasons (Table 3.9).
Table 3.9: Milk Yields per Cow per Day Dairy Hub Average Cows
Currently Milked/Farmer
Amt produced
(Wet season/farmer)
Average/
cow/day (wet season)
Amt of Milk
produced (Dry Season/farmer)
Average/
cow/day (dry season)
Average
lts/cow/day (All seasons)
# Treatment
1 Limuru 4 30 7.8 25 6.5 6.9
2 Gatamaiyu 2 18 8.8 16 7.7 8.1
3 Mkulima
bora
2 25 14.3 22 12.8 13.5
4 Tumaini 2 18 11 16 9.6 10.5
5 Rugendo 2 27 14.2 24 12.3 13.5
6 Torongo 5 28 5.7 20 4.1 5.4
7 Ololunga 6 31 5.4 22 3.9 5.3
8 Nyala 3 27 10.3 20 7.9 9.4
9 Njabini 3 27 8.8 24 6.1 7.8
10 Karati 2 23 11.3 16 7.7 8.8
11 Siongiroi 4 25 6.8 17 4.7 5.9
12 Meru Multipurpose
2 27 12.8 27 12.4 12.4
Overall
Averages
3 29.1 9.7 24.1 8.0 8.9
Control
1 Kabete 2 26 13 25 12.5 12.8
2 Olbutyo 2 13 6.5 11 5.5 6.0
3 Umoja 2 22.5 11.3 13 6.5 8.9
4 Nandarasi 2 17 8.5 14 7 7.8
5 Kahuru 3 22 7.3 18 6 6.7
# Overall Averages
2 18.6 9.3 15.0 7.5 8.4
Source: Dairy farmers’ household survey
* Outliers were removed from the data
On average, the achieved milk yield was higher than the national averages of approximately 7.1
liters per cow per day22. It should however, be noted that the KMT program intervened in
mostly high potential areas while the national average, includes production includes yields from
low production agro-ecological zones such as the coastal low lands and the Arid and Semi-Arid
areas.
3.7.1.2 Milk Marketing Channels
One of the dairy interventions’ objectives is strengthening farmers’ collective action for them to
be able to access formal markets and be influential actors in the dairy value chain.
22 Kenya dairy Board, 2014
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
20
Over 80% of milk from the treatment group went to the hubs. The increase in volumes
marketed was associated both with the increased yields and access to more reliable markets as
well as support services. From the midline assessment, 93% of the milk is sold through formal
channels. At baseline 65% of the milk went hubs, 36% to traders/venders and other consumers.
(Table 3.11).
Dairy Co-operative/hub was the most used milk marketing channel23. For the treatment group,
91% of the milk is sold to dairy co-operatives/hubs with venders/traders, direct consumers and
private processors account for 5%, 2% and 2% of the milk sold respectively (Table 3.10). This
implies that 93% of the milk is sold through formal channels (Dairy co-operative and private
processors). This is much higher compared to the baseline where approximately 70% of the
milk was sold through formal channels and 86% for the control group. These results may be
attributed to KMTs intervention of improvement of practices and skills of supply chain
management for the dairy hubs.
It is important to note that the high proportion of farmers selling their milk through formal
channels may be attributed to the fact that the respondents interviewed are affiliated to dairy
hubs/co-operative and they therefore sell most of their milk through those dairy hubs.
However, it is known in Kenya that most of the small scale dairy farmers (about 80%) sell their
milk through informal channels, and majority may not be affiliated to any dairy hub/co-
operative/enterprise. Staal, S., Pratt, A., & Jabbar, M. (2008)24 found that milk was being sold
through three major milk marketing channels including direct sales to individual consumers,
informal private traders and sale through cooperatives and private dairy processors.
Table 3.10: Percentage distribution of quantity of milk sold by type of outlet
Marketing outlet Treatment Control Baseline
Wet
Season
Dry
Season
Wet
Season
Dry
Season
Wet
Season
Dry
Season
Dairy co-operatives 91% 91% 84% 84% 66% 64%
Vendors/traders 5% 5% 6% 7% 15% 16%
Direct Consumers (e.g
neighbors, educational
institutions, hospitals hotels
etc)
2% 2% 7% 7% 21% 20%
Private processors 2% 2% 2% 2% 4% 4%
Others (e.g gifts, donations) 0% 0% 0% 0% 1% 1%
Source: Dairy farmers’ household survey
Despite the dairy cooperatives/hubs offering the lowest prices25 compared to the other
channels, it still remained the main channel for most of the respondents. This is because, apart
23 This was largely expected as KMT interventions were largely focused on dairy hubs 24 Staal, S., Pratt, A., & Jabbar, M. (2008). Dairy Development for the Resources Poor - Part 2: Kenya And Ethiopia Dairy Development Case Studies. Rome, Italy: Pro-Poor Livestock Policy
Initiative. 25 Tables 3.25 and 3.26 on revenues
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
21
from consistently buying all the milk that the farmers supplied, these cooperatives offered other
services to the farmers that made the channel more attractive than the others. Such services
included access to quality feeds and AI on credit and payment recovered by check off system. In
some cases, the cooperatives also offered extension services. This increased farmers loyalty and
trust in the co-operatives; hence delivering their milk even if cooperatives offered relatively
lower prices.
Given the importance of the dairy hubs/co-operatives in enabling farmers to sell most of the
milk that they produced coupled with the services offered, this channel remains the most
important in the milk value chain. In that view, it is important to continue empowering them to
be viable business entities which would be instrumental in propelling smallholder farmers from
poverty.
Discussions with dairy hub managers indicated that after aggregating milk from farmers, most of
the DHs sold the milk to different buyers mainly through the formal channels to major milk
processors including New KCC and Brookside. It was however, noted that some dairy hubs
(mainly those that pasteurized their milk at the dairy hubs), also sold through the informal
channels such as milk traders and satellite milk bars or dispensers. Ostensibly processors were
unpopular due to their low price and other unfavorable conditions. For example it was noted
that the informal channels usually offered higher milk prices compared to large milk processors
particularly during the dry seasons. In addition, milk processors required that the dairy hubs
guaranteed certain quantities of milk supplies on daily basis at a given price while any surplus
could only be offtaken at a lower price. In some instances (particularly during the wet season)
the milk processors were unable to offtake all the milk collected by the dairy hubs even where
a contract existed. Such cases led to DHs maintaining informal traders as their offtakers in
addition to the processors. Given this reality, it was noted that KMAP’s focus on developing the
informal milk channel through interventions that targeted informal milk traders and retailers
was well aligned and justified.
3.7.1.3 Volumes of Milk sold
The daily milk sales through hubs for the treatment group were higher compared to the
control group. This is illustrated in Table 3.11below.
For the treatment group, the average volume of milk sales per day per farmer/household was
21.3 litres during the wet season and 16.7 litres during the dry season. This translated to an
average of 19.1 litres for all seasons which was a 14% increase from the baseline value of 16.3
litres. Among the control group households, the daily quantities of milk sold to hubs averaged
15.1 liters and 13.4 litres during the wet and dry seasons respectively.
The increase in percent of milk sold may be mainly due to increased loyalty of the members in the treatment hubs as a result of improved services delivery, as well as KMAPs intervention of
enhancing linkages between small holder dairy farmers with marketing channels.
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
22
Table 3.11: Volume of Milk Sold per Day
Source: Dairy farmers’ household survey Name of
dairy hub
N Av Amt
Sold (Wet Season Oct_Dec)
N Av Amt
Sold (Wet April_June)
Average
Wet season
N Av Amt
Sold in Dry Season(Jan-March)
N Av Amt
Sold Cold season (July_Sept)
Average
Cold & Dry seasons
Average all
seasons
Treatment
1 Limuru 32 27.3 32 26.0 26.7 32 21.4 30 21.3 21.4 24.0
2 Gatamaiyu 39 15.7 39 14.6 15.1 37 13.5 36 13.6 13.5 14.3
3 Mkulima bora 39 21.7 40 21.6 21.7 40 19.5 40 19.5 19.5 20.6
4 Tumaini 38 15.7 38 15.7 15.7 38 13.7 38 14.8 14.3 15.0
5 Rugendo 39 23.3 39 23.9 23.6 39 20.1 39 20.3 20.2 21.9
6 Torongo 39 22.4 39 25.3 23.8 39 16.3 39 17.8 17.0 20.4
7 Ololunga 39 25.9 39 28.5 27.2 36 18.3 36 21.7 20.0 23.6
8 Nyala 36 22.9 36 22.8 22.9 36 17.4 35 17.8 17.6 20.2
9 Njabini 37 13.4 38 14.3 13.8 36 10.3 35 10.8 10.5 12.2
10 Karati 36 19.7 35 19.3 19.5 38 12.9 37 12.0 12.5 16.0
11 Siongiroi 42 21.4 42 22.5 21.9 42 14.4 41 15.3 14.8 18.4
12 Meru Multipurpose
33 23.1 34 23.5 23.3 33 22.6 34 21.5 22.1 22.7
Overall
averages
449 21.0 380 21.5 21.3 377 16.7 374 17.2 16.9 19.1
Control
1 Kabete 41 22.4 41 22.5 22.5 41 21.1 41 24.0 22.6 22.5
2 Olbutyo 38 8.9 40 10.6 9.7 22 7.8 21 7.1 7.5 8.6
3 Umoja 38 10.7 38 11.9 11.3 34 10.6 39 10.6 10.6 10.9
4 Nandarasi 35 13.5 37 11.6 12.6 36 11.5 36 10.9 11.2 11.9
5 Kahuru 39 18.9 39 19.6 19.3 37 14.6 37 15.5 15.0 17.1
Overall averages
191 14.9 195 15.2 15.1 170 13.1 174 13.6 13.4 14.2
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
23
3.7.2 Dairy Production Costs
The overall cost of production for a household within the treatment group was Kshs. 9,180 per
per cow per month or Kshs. 137.7 per cow per day. Given an average yield of 8.9 litres per
cow per day, this would translate to Kshs. 15.5 per litre. For the control group, the monthly
cost per cow was Kshs. 8,836 or Kshs 141.6 per cow per day. Given a daily yield of 8.4 litres
per cow per day, this would translate to Kshs. 16.9 per litre.
Costs of labour, hay and fodder as well as feed supplements comprised the largest share of
monthly production costs among the treatment group households while feed (hay and forage)
comprised the highest cost component for the control group households (Table 3.12).
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
24
Table 3.12: Average costs of production (variable costs) Name of
dairy hub
Av
Cost hired labour
Av Cost
Feed - hay and fodder
Av Cost
Feed - supplements
Av
Cost Water
Av cost
treatment &pest control
Av Cost
Transport (inputs &milk)
Av
Cost Electricity
Total
Costs
Averag
e No.of cows
Average
cost per cow/month
Average
cost per cow/day
Averag
e cost per litre
Limuru 10,099 7,739 12,370 1,122 1,036 2,613 1,346 36,326 4 9,463 82.2 11.9
Gatamaiyu 6,150 3,689 5,635 197 625 330 193 16,818 2 8,105 130.2 16.1
Mkulima
bora
8,513 12,933 8,958 348 396 1,737 322 33,208 2 18,976 361.4 26.8
Tumaini 7,153 3,360 3,173 203 403 442 208 14,943 2 8,966 179.3 17.1
Rugendo 7,833 8,667 5,122 233 398 512 265 23,030 2 11,976 207.6 15.4
Torongo 8,460 11,039 5,912 1,183 1,568 1,823 - 29,985 5 6,096 41.3 7.6
Ololunga 4,474 5,601 2,546 4,000 1,310 2,441 1,400 21,772 6 3,848 22.7 4.3
Nyala 6,102 2,768 3,544 333 1,266 556 552 15,120 3 5,863 75.8 8.1
Njabini 7,436 6,812 7,995 1,106 283 2,136 1,150 26,918 2 12,146 182.7 23.4
Karati 7,705 2,694 7,137 - 4,250 437 - 22,224 2 10,827 175.8 20.0
Siongiroi 3,648 2,247 2,892 750 664 1,261 1,533 12,996 4 3,483 31.1 5.3
Meru Multipurpose
7,366 6,835 4,455 1,150 338 1,483 564 22,190 2 10,410 162.8 13.1
Average 7,078 6,199 5,812 885 1,045 1,314 628 22,961 3 9,180 137.7 14.1
Kabete 5,927 6,042 6,838 311 717 1,200 389 21,424 2 8,612 115.4 9.0
Olbutyo 3,473 3,760 2,575 311 304 771 390 11,585 2 4,866 68.1 11.4
Umoja 4,746 7,807 3,498 356 300 505 387 17,599 2 9,599 174.5 19.6
Nandarasi 4,898 14,867 4,204 533 792 783 581 26,658 2 14,505 263.1 33.7
Kahuru 6,215 4,878 4,213 400 628 422 - 16,755 3 6,600 86.7 12.9
Average 5,052 7,471 4,266 382 548 736 349 18,804 2 8,836 141.56 17.33
Source: Dairy farmers’ household survey
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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3.7.3 Revenues and Gross Margins from Milk production
Gross margins were determined as the net of milk revenues less the total variable costs (direct
costs of milk production and sales (ie GM = TR- TVC)
Where,
TR = Volume of milk * Price of milk
TVC = Summation of all variable costs
Milk sales revenues were higher for the treatment group farmers than for the control group
farmers. One of the expected impacts of the KMAP program is to increase the incomes of the
dairy farmers. The average revenue from milk sales per cow per day averaged Ksh. 334.2 during
the wet season and Ksh 286.1 during the dry season (Table 3.13). On the other hand, the
average revenues for the control group averaged Kshs. 265.4 during the wet season and Kshs.
240.2 during the dry season (Table 3.14).
As a result of higher milk yields and better prices, the gross margins per cow per day for both
the treatment and control groups increased with the treatment group receiving higher gross
margins of Kshs. 196.5 during the wet season and Kshs.148.4 during the dry season (Table
3.13).. In comparison, gross margins for control group members averaged Kshs. 123.9 during the wet season and Kshs. 98.7 during the dry season (Table 3.14).
Table 3.13: Average Milk Revenue for Treatment Group
Outlet Treatment
Wet Season Dry Season
Average Quantity Sold (L)
Average price (Ksh)
Revenue (Ksh)
Average Quantity Sold (L)
Average price (Ksh)
Revenue (Ksh)
Dairy co-operatives 9.5 31.5 300.2 7.4 31.5 234.6
Private processors 11.2 34.0 381.2 9.2 36.0 330.5
Vendors/traders 4.5 37.5 168.2 4.2 38.5 162.6
Consumers 3.9 39.5 153.0 3.1 41.5 130.7 29.1 35.6 1,002.6 24.0 36.9 858.4
Average No. of dairy cows
3.0
3.0
Average revenue per cow per day
334.2
286.1
Average variable costs per cow per day
137.7
137.7
Gross Margin per cow
per day
196.5
148.4
Source: Dairy farmers’ household survey
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
26
Table 3.14: Average Milk Revenue for Control Group
Outlet Control
Wet Season Dry Season
Average
Quantity Sold (L)
Average
price (Ksh)
Revenue
(Ksh)
Average
Quantity Sold (L)
Average
price (Ksh)
Revenue
(Ksh)
Dairy co-operatives 5.4 30.6 166.4 4.6 31.8 146.6
Private processors 4.1 29.8 122.0 3.9 30.0 115.9
Vendors/ traders 3.7 33.8 124.2 3.6 33.9 122.7
Consumers 3.6 32.9 118.2 2.9 32.9 95.2
Total 16.8 31.8 530.8 15.0
480.4
Average No. of cows
2.0
2.0
Average revenue per cow per day
265.4
240.2
Average variable costs per cow per day
141.6
141.6
Gross Margin per head per
day
123.9
98.7
Source: Dairy farmers’ household survey
3.7.3.1 Farmers Access to Information and Inputs
Market information is a key factor in smallholder dairy farming enterprises. Smallholder farmers
suffer from insufficient information on the available yield enhancing technologies as well as
lucrative markets. This midline evaluation sought to understand the level of information
availability to dairy farmers on production and marketing. KMAP program endeavoured to build
capacity of DHs and also encourage them to create avenues for sharing different kinds of useful
information with their members.
Figure 3.2: Market Information and Participation in Marketing Activities
Source: Dairy farmers’ household survey
Data from the household survey illustrates that 76% of the treatment group and 65% control
group of farmers had heard or seen marketing activities, promotions or advertising related to
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
27
dairy farming production or marketing that were used during the intervention period (Figure
3.2). This is an indication that 76% (28,12026 farmers) of the beneficiary farmers that benefitted
from supply chain interventions had access to information and inputs.
This is an indication that there are endeavours to disseminate information publicly regarding
dairy production and marketing. In terms of participation in these marketing activities, 30% of
the treatment farmers and 47% of the control group farmers had participated in these kinds of
activities. The results revealed that the farmers were able to gather a wide range of information
including quality feeds, hay, concentrates, silage, milk quality, veterinary services and herd
management.
Table 3.15 presents the different sources of information related to the three main yield
enhancing inputs: hay, concentrates and AI. The results indicate that the DHs were the main
sources of information to the dairy farmers. Our results shows that 44% and 39% of the
treatment and control group; 42% treatment farmers and 36% control group and 40% of the
treatment farmers and 33% of the control received information on AI, Concentrates and Hay
respectively from the DHs. This was corroborated by the information from key informant who
acknowledged that DHs organised for education days at least once per year for their farmers.
Other DHs had a structured extension department that offered extension services to their
members systematically.
One of the interventions of the KMAP program is improving the informal supply chain services
by working with agents and traders. From the study, only 6% (1,92727 farmers) accessed
information and inputs from traders and agents.
Table 3.15: Sources of Information Source of Information AI (%) Concentrates (%) Hay (%)
Treatment Control Treatment Control Treatment Control
Cooperative/ dairy hub 44 39 42 36 40 33
Milk trade association 3 1 4 2 3 1
Processors 1 1 2 4 4 5
Agro vets/Animal feeds outlets 18 17 20 24 16 14
Village agents/traders 6 3 6 5 7 6
Other farmers 15 20 14 17 19 24
Community events 2 4 3 4 4 6
Demonstration plots/farms 3 1 5 2 6 2
Private vets 10 14 4 6 2 10
Source: Dairy farmers’ household survey
26 76% of total number of beneficiaries (37,000) 27 6% of beneficiaries of feed component (32,067)
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
28
3.7.3.2 Frequency and Consistency of Information Access
This evaluation also sought to understand the progress made on the consistency of receiving
this information. This is because for these pieces of information to be useful, they ought to be
disseminated consciously and consistently.
Figure 3.3: Consistency and Frequency of information
Source: Dairy farmers’ household survey
The evaluation results reveal that information regarding AI, feed concentrates and supplement
was received by majority of the farmers most recently. At least 37% of the treatment group
farmers and 25% percent of the control group farmers had received information on
concentrates within the last week. Similarly, 30% of farmers participating in KMAP and 21% of
the control group farmers received information on AI in the same period of time. However, the
information on hay had been received slightly over a year ago as noted by 31% of the treatment
group farmers, and 10% of the control group. Figure 3.4 gives more details on how the
information on the different feed products had been accessed.
3.7.3.3 Level of Satisfaction with Sources of Information
Availability of information alone does not suffice, the information accessed should be easy to
comprehend and be useful to the consumers. Figure 3.4 gives details on the level of satisfaction
the farmers expressed on the information they received. This was measured using a likert scale
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
29
of between 1 and 5, where 1 is very dissatisfied and 5 is very satisfied. The results indicate
majority of the farmers were satisfied with the information they received. However, there was
a slightly higher proportion the treatment farmers reporting high level of satisfaction compared
to the control group farmers. For treatment farmers, the satisfaction index ranged from 4.1
(82%) for information on AI services, and 4.2 (84%)each for concentrates and supplements and
hay, while for the control group farmers the satisfaction indices were 3.7, 3.9, 4.0 for
information on hay, AI services and concentrates and supplements respectively.
4.2 4.2
4.1
3.7
4.0
3.9
3.4
3.5
3.6
3.7
3.8
3.9
4
4.1
4.2
4.3
Hay Concentrates and supplements
A.I Services
Satisfaction Index with Source of Information
Treatment
Control
Figure 3.4: Level of satisfaction on information received
Source: Dairy farmers’ household survey
3.7.3.4 Level of Satisfaction with Supply Chain Services
The level of satisfaction with supply chain services was measured using four main attributes:
price, timeliness of milk collection, timeliness of milk payment and information received from
processors/dairy hubs. This was measured using a scale of between 1 and 5, where 1 is very
dissatisfied and 5 is very satisfied. The overall satisfaction index with supply chain services for
the treatment group was 3.5 (70%), higher than that of the control group at 3.1 (62%) as shown
in Table 3.16. This implies that 70% of the beneficiaries are accessing improved supply chain
services, which are 25,900 farmers28 .
Farmers in the treatment group had benefitted from KMAP interventions of improving the
operations of the dairy hubs, thus making the hubs more responsive to the farmer needs, hence
higher proportions accessing improved supply chain services than control group farmers. High
satisfaction levels were exhibited more in the information farmers received from dairy hubs
(3.9) as well as with the timeliness of milk collection (3.8) and milk payment (3.6). The lowest
levels of satisfaction were experienced with the pricing of milk. This is an indication that
28 70% of total number of beneficiaries (91,865)
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
30
although farmers sold their milk to the cooperatives, the attraction to deliver milk to
cooperatives was not necessarily due to price, but due to other benefits as noted earlier in this
report. However, it is important for supply chain players to discuss ways of making the price of
milk better for the farmers.
Table 3.16: Level of Satisfaction with Supply Chain Services
Attributes Level of satisfaction
Treatment (N=473) Control (N=206)
Price offered for milk 2.6 (52%) 1.9 (38%)
Timeliness of milk collection 3.8 (76%) 3.7 (74%)
Timeliness of milk payment 3.6 (72%) 3.3 (66%)
Information I get from the milk processors/dairy hubs 3.9 (78%) 3.5 (70%)
Average 3.5 (70%) 3.1(62%)
Source: Dairy farmers’ household survey
3.7.3.5 Level of Satisfaction with Inputs Provision
The evaluation also sought to establish the satisfaction of the farmers with inputs provision: hay,
feeds and concentrates and AI services on a number of attributes. These attributes include:
price, quality, availability, and trust of the vendors. The level of satisfaction was measured using
the same methodology used for measuring the level of satisfaction with supply chain services.
The level of satisfaction with inputs provision to farmers was between 3 and 4 for both the
treatment and control groups, with the highest levels of satisfaction being observed for AI
services and the lowest for hay provision (Table 3.17). The biggest challenge the farmers had
was with the high price of inputs. It is therefore important for the service providers to offer
competitive prices for the inputs. It is noted that the farmers both in the treatment and control
groups exhibited a high trust in the vendors of inputs. This may be attributed to the fact that
most of the farmers purchased their inputs from either the dairy hubs or vendors
recommended by the dairy hubs, hence assured of quality inputs.
Table 3.17: Level of Satisfaction with Inputs Provision
Attributes
Level of Satisfaction
Hay Feeds and Concentrates A.I. Services
Treatment Control Treatment Control Treatment Control
Price 2.5 2.5 2.6 2.6 3.0 2.6
Quality 3.7 3.6 3.9 3.9 3.8 3.8
Availability 3.7 3.4 4.0 4.0 3.9 3.8
I trust the vendors 3.8 3.5 4.0 4.0 4.1 4.0
Average 3.4 3.3 3.6 3.6 3.7 3.6
Source: Dairy farmers’ household survey
3.7.4 Market Systems Change Level for the Supply Chain Component
Qualitative analysis of the sampled treatment and control dairy hubs revealed that the dairy
hubs offered a myriad of services to their farmers including:
• Veterinary and AI services;
• Concentrates and supplements on credit;
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
31
• Extension services/training and advisory services;
• Seeds and fertilizers;
• Loans and linkages to credit;
• Mobile money – advances through mobile phones;
• Transport services;
• Quality checks for milk;
• Provision of marketing information;
• Provision of hay29 or linking farmers with commercial hay providers; and
• Farm machinery and equipment.
Following the KMAP interventions on supply chain, the performance in most of the intervention
dairy hubs improved (Table 3.18)30. Overall nine (9) of the intervention dairy hubs had
membership numbers growing by between 8% and 317%. Quantity of milk handled also
increased in seven (7) of the dairy hubs by between 11% and 94%. Turnover increased by
between 2% to 100% in eight (8) of the dairy hubs.
Table 3.18: Performance of the Intervention Dairy Hubs Growth
(2013-2015)
Nyala
Nja
bin
i
Kara
ti
To
ron
go
Sio
ngir
oi
Tu
main
i
Lim
uru
Mku
lim
a
Bo
ra
Ru
gen
do
Olo
lolu
nga
Gata
maiy
u
Membership 27% 36% 44% 8% 26% No data 15% 317% No data 8% No data
Quantity (Litres)
11% 82% 75% 0% 11% No data -1% 94% 50% 46% No data
Turnover (KES)
7% 83% 11% -16% 16% No data 14% 2% 100% 31% No data
Source: Dairy Hubs Managers
Other benefits reported by the dairy hubs included:
• Increased customers and sales;
• Improved stocks display and management;
• Improved access to financial resources;
• The dairy is now more focused on the growth path due to having strategic plan;
• Market research plan has enabled them to venture into new markets;
• Training on customer service helped reduce complaints from farmers and other clients
The market systems change for the supply chain intervention is discussed further based on the
Adopt Adapt Expand and Respond (AAER) model as illustrated in Annex 10.
29 This applies only to Nyala Farmers Dairy Co-operative 30 More details in appendix 4.
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
32
3.8 Results for Improving and Promoting AI Service Component
Animal genetics is a critical input in dairy production for the purposes of improving production
given different environments. Better/dual breeds that feed less and still produce more –milk and
meat and able to adapt to various ecological zone/climate change and tolerant to many livestock
disease etc are crucial. This is another key intervention area of the KMAP project with the aim
of stimulating greater demand for AI and veterinary services and ensuring access to and
adoption of quality AI and animal health services by small holder dairy farmers.
KMAP enhanced partnerships between dairy hubs and processors and the private sector
providers, County Governments and LGSA to improve AI service providers customer service
skills in 11 dairy hubs so as to build customer confidence in AI services. As a result AI service
providers affiliated to 8 dairy hubs and 2 processors invested in promotional and marketing
activities with relevant market actors. These efforts bore fruit because accredited AI service
providers reported increased AI services provision by 61% between 2013 and 2016, implying an
increase in number of farmers adopting A.I services.
3.8.1 Target Group Change Level for Improving and Promoting AI Service
Component
3.8.1.1 Awareness of Accredited AI Services
From the midline evaluation, there was a high awareness of accredited A.I services, with
awareness levels of 75.9% and 67% for the treatment group and for the control group
respectively. The source of awareness was mainly through the co-operative/dairy hub as
indicated by 45.4% of the farmers in the treatment group and 43.2% of the farmers in the
control group (Figure 3.6). Other major sources of awareness include agrovets, other farmers
and village agents.
Figure 3.6: Source of awareness of Accredited AI Services
Source: Dairy farmers’ household survey
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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3.8.1.2 Usage of Accredited AI Services
There was considerably high usage of the accredited AI services, 72.7% of the treatment
farmers and 57.8% of the control group farmers used accredited AI services. It is important to
note that the level of usage for the accredited AI services is higher for the treatment group
than the control group (Figure 3.7). Similarly, the usage of accredited AI services has more than
doubled from 35.3% in the baseline to 72.7% at the midline. This may be attributed to KMAP’s
strategy of leveraging the interconnectedness of various market systems that are important to
dairy, specifically breed improvement (through provision of accredited AI services), feed, and
vet services. The midline evaluation found out that most of the DHs provided accredited AI
services to their members on check-off system in one way or another. Two arrangements were
common; first where the dairy hub accredits a number of AI service providers (SPs) who the
members use on credit. The second one is where the dairy hubs have a vet and AI services
departments in their structure, they employ experts who serve their members on credit. These
arrangements are instrumental in availing quality AI services to members and thus scaling up the
use.
Figure 3.7: Usage of Accredited AI Services
Source: Dairy farmers’ household survey
3.8.1.3 Cost of Accredited AI Services
Accredited AI service providers charge the following per insemination: Local semen- Ksh. 1000;
Exotic-Ksh. 1000-3000; Sexed- Ksh 6000-700031. The average price of A.I services is Ksh 1,578
(Maximum Ksh 8,000). These costs are quite high for most of the farmers. There is therefore
need to subsidize these costs so as to further increase the adoption of accredited A.I services.
It is also important to open up more space to more actors to provide accredited AI services.
When compared with the baseline, the average prices was Ksh 1,277 (Maximum Ksh 3,600)
when provided by agrovets and Ksh 1,768 (Maximum Ksh 3,000) when provided by private
vets.
31 Source: Key informant interviews with Independent and Dairy Hub based AI providers
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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3.8.1.4 Level of Satisfaction with Accredited AI Services
The evaluation also sought to understand the level of satisfaction of farmers on a number of
indicators related to AI service delivery and utilisation (affordability, quality, availability, and
trustworthiness). Tables 3.19 and 3.20 reflect the levels of satisfaction relating different aspects
on AI services for the treatment and control groups respectively. On average, there was an
increase from 16.8% at the baseline to 35.8% of the farmers in the treatment group that “strong
agreed” that they were satisfied with the affordability, quality, availability, and trustworthiness of
the A1 services (Table 3.19). The control group also had a lower satisfaction level at 20.1% as
compared to the treatment group (Table 3.20). However, it is noteworthy that both the
treatment and control groups had a problem with the pricing of the AI services because it is the
aspect that exhibited the lowest satisfaction levels. AI services should therefore be made more
affordable.
Table 3.19: Agreement Scale on Satisfaction with AI Services (Treatment)
Attributes
Level of Satisfaction (Treatment)-Midline (%)
Baseline
(Strongly
agree) Strongly
disagree Disagree
Neither
agree
or
disagree
Agree Strongly
Agree
I am satisfied with the price
of artificial insemination
services
19.4 23.2 13.6 19.2 24.6 15
I am satisfied with the quality
of artificial insemination
services
9.5 5.5 10.5 36.7 37.8 15
I am satisfied with the
availability of artificial
insemination services
6.7 6.7 7.7 40.6 38.3 19
I trust the providers who sell
me artificial insemination
services
3.3 6.3 14.5 33.3 42.6 19
Average 9.7 10.4 11.6 32.5 35.8 17
Table 3.20: Agreement Scale on Satisfaction with AI Services (Control)
Attributes Level of Satisfaction (Control) - (%) Baseline
(Strongly
agree) Strongly
disagree
Disag
ree
Neither
agree or
disagree
Agre
e
Strongly
Agree
I am satisfied with the price of
artificial insemination services
24.3 31.6 4.6 34.2 5.3
I am satisfied with the quality of
artificial insemination services
6.6 12.5 13.9 47.4 19.7
I am satisfied with the availability
of artificial insemination services
3.9 11.2 8.6 51.3 25.0
I trust the providers who sell me
artificial insemination services
1.3 13.2 9.2 46.1 30.3
Average 9.0 17.1 9.1 44.7 20.1 15.5
Source: Dairy farmers’ household survey
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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3.8.1.5 Perceived Benefits of using Accredited AI Services
Both treatment and control group farmers appreciated the benefits of the use of AI to their
dairy enterprises. The main benefits mentioned by farmers in the treatment group include:
increased milk production (77.5%); healthier calves (75.7%); high conception rates (68.6%);
increased incomes (63.2%). For the control group increased milk production (57.1%) and
healthier calves (50.4%) were the main benefits accruing to use of AI services (Table 3.21).
Table 3.21: Benefits of using Accredited AI Services
Benefits Treatment Control
N % N %
Increased milk production from
offspring 259 77.5 68 57.1
Increased incomes from milk sales
(offspring’s) 211 63.2 45 37.8
High success rate (Conception) 229 68.6 59 49.6
Higher birth rate 167 50.0 34 28.6
Easier birth process 182 54.5 27 22.7
Healthier calves 253 75.7 60 50.4
Less variation in milk production 117 35.0 4 3.4
None 1 .3 1 .8
Note: The percentages are for a multi response variable and therefore they do not add up to 100%
Source: Dairy farmers’ household survey
3.8.2 Market System Change Level for Improving and Promoting AI Service
Component
3.8.2.1 Success Rate of AI Services
The success rate of the AI services was calculated by getting the proportion of cows with live
births for the cows artificially inseminated. This is illustrated in Table 3.22 below. The success
rate for AI services for the treatment farmers marginally increased by 3.8%, from 75.4% at the
baseline to 79.2% at the midline. It is also observable that the success rate is higher for the
treatment group than the control group. This may be attributed to the fact that there are more
farmers in the dairy hubs under MAP intervention using accredited AI services than both in the
control group and at the baseline (Figure 3.8).
Table 3.22: Success Rate of AI Services
Statistics Treatment Control
Mean N Total Mean N Total
Number of cows artificially inseminated 2 318 636 2 125 250
Number of cows with live births 2 252 504 2 85 170
Success Rate (Midline)
79.2%
68.0%
Success Rate (Baseline)
75.4%
% change 3.8%
Source: Dairy farmers’ household survey
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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3.8.2.2 AI Service Providers with Improved Customer Service and Business Skills and
Investing in Promotional and Marketing Activities with Relevant Market Actors
Accredited AI providers also reported that the KMAP program had increased the number of
clients due to referrals as well as customer loyalty. This is illustrated by the increase in the
number of AI servings (Table 3.23). Overall, the number of AI servings grew by 61% between
2013 and 2016.32 The increase in growth was observed for all the AI providers sampled in the
evaluation except for KCC Runyenjes experiencing growth in the number of AI services
provided, thus implying that they served an increased number of customers.
Table 3.23: Trends in Provision of AI Services33 (No. of customers)
AI Provider 2012 2013 2014 2015 2016 % Growth
(2013-2016)
Limuru 600 780 900 1,440 1,800 131%
Farmlink-Embu 600 600 650 720 700 17%
Meru Central 4,800 5,400 6,000 6,600 7,200 33%
Caritas Embu 6,600 2,700 2,700 5,400
100%
KCC Runyenjes 1,200 1,200 600 540
-55%
Nyala 3,120 3,600 4,200 4,200 4,200 17%
Karati 480 720 840 1,080 1,200 67%
Nandarasi 3,161 3,661 4,112 5,000 5,050 38%
Torongo 50 50 60 80 120 140%
Siongoroi 240 456 636 720 1,020 124%
Overall 61%
Source: Dairy hubs managers’ interviews
The market system change for improving and promoting AI services are further on the Adopt
Adapt Expand and Respond (AAER) model is illustrated in Annex 10.
3.9 Results for Commercial Hay Production
3.9.1 Background of Commercial Hay Production Intervention
The KMAP project intended to develop dairy value chain by assisting farmers’ access and use
quality inputs for their dairy farming, a crucial aspect in promoting productivity and helping
farmers cope during times of drought. One of the most important inputs of dairy farming in the
KMAP program is hay. KMAP’s intervention included: support commercial hay producers to
improve production, expand their business and adopt faster growing fodders (hay); support
feed manufacturers to develop formulation strategies based on quality fodder, concentrates and
supplements and build the capacity of labs to market and co-brand quality feed.
32 Note: AI success rates are 79.2% 33 Estimated by number of AI straws used
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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3.9.2 Target Group Change Level for Commercial Hay Production Component
3.9.2.1 Awareness of Quality Assured Hay
Hay is a very useful fodder for dairy farmers because it can be dried and preserved for use in
the dry season. It is also has very high levels of nutrition and thus very ideal. Thus, the KMAP
project has been working with commercial hay producers to increase its supply and availability.
The results show that on-farm production of hay was still low, at only 28% for the treatment
group and 27% for the control group (Table 3.20). In view, farmers supplemented this through
purchase in which 50% treatment and 27% control group farmers said that they purchased hay.
KMAPs’ efforts are not only focused on the supply of hay but also the quality of the hay
produced. From the midline survey 41% of the treatment and 63% of the control group were
aware of quality assured hay.
Table 3.24: Hay Production
Treatment Control
N Midline% Baseline
%
N Midline
%
Baseline
%
Do you grow grass for Hay (Yes) 132 28 56 27
Do you purchase hay (Yes) 236 50 56 27
Aware of quality assured hay (Yes) 192 41 9.3 31 63 10.7
Source: Dairy farmers’ household survey
3.9.2.2 Utilization of Quality Assured Hay
KMAP intended to increase the availability, access, and use of hay, the reason was to bridge
scarcity of fodder during dry season to prevent reduction in milk production. A key
intervention of the program was to not only ensure access to hay, but also emphasis on the
quality. The evaluation results indicate a huge proportion of the farmers that purchase hay, go
for quality assured hay, 93.2% and 61.5% for the treatment group during the dry and wet
season respectively (Table 3.25)34. On average 77% (24,083) 35 of the beneficiary farmers access
quality assured hay during both the wet and dry seasons. For the control group, the
proportions are slightly lower than for the treatment group; however, the difference is not much.
Findings from interviews with dairy hub managers revealed that all the dairy hubs in Kiambu and
Embu counties did not stock hay for their farmers and thus only sourced it from the traders
and agro-vets. In the central region it is only in Nyala dairy hub in Nyandarua where the KMAP
initiative on production and selling of hay was being practiced. However, in the Rift Valley,
Torongo and Siongiroi had arrangements of stocking hay and availing it to their members.
However, it was noted that KMT had made efforts to work with the commercial hay producers
34 The differentials between the use of quality assured hay during the dry season and wet season is
because more famers buy hay during the dry season than the wet season 35 Proportion of farmers selling*Total beneficiaries feeds component (32,067)
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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such as the Technology Farm in the Rift valley both to train farmers on hay production, and
also to ensure that there was enough quality hay for the market.
Table 3.25: Proportion of Farmers that Purchase Quality Assured Hay
Season Treatment (%) Control (%)
N Purchase Quality
Assured Hay
(Yes)
N Purchase Quality
Assured Hay
(Yes)
Wet season (Oct-Dec) 120 60.0 41 56.1
Wet Season (April-June) 108 63.0 44 56.8
Average for wet season
61.5
56.5
Dry Season (Jan-Mar) 120 96.7 46 87.0
Cold and dry season (July-Sept) 106 89.6 35 88.6
Average for dry season
93.2
87.8
Source: Dairy farmers’ household survey
3.9.2.3 Perception on the Quality of the Hay Purchased
One of the main indicators of the KMAP program for the commercial hay production
component is to establish the proportion of farmers claiming to purchase ‘very good’ quality
hay during the wet and dry season. This is illustrated in Table 3.26 below. The proportion of
the farmers in the treatment hubs claiming to be using “very good quality hay” during the wet
season was 45.6%, higher than the baseline value (35.4%) and the control group (26.3%). The
trend is similar for the dry season with the proportion of farmers claiming the hay they used is
‘very good quality’ being 40.3% as compared to 23.5% and 29.5% for the midline control group
and for the baseline respectively. These results show that there is a great improvement in
accessing quality hay for the farmers under the dairy hubs benefiting from the KMAP
interventions.
Table 3.26: Quality of Hay Purchased by Season Season Treatment group (Midline) Baselin
e (Very
good quality
(%)
Control group
(Very good quality)
(%)
Very poor
quality (%)
Poor quality
(%)
Okay quality
(%)
Mostly good
quality (%)
Very good
quality (%)
Wet season (Oct-Dec) 0.0 8.5 25.8 20.5 45.2
31.8
Wet Season (April-June) 3.4 6.9 21.6 22.1 46.0
20.8
Average for wet season
45.6 35.4 26.3
Dry Season (Jan-Mar) 0.9 4.7 27.7 24.5 42.1
26.3
Cold and dry season (July-Sept) 12.2 2.2 27.8 19.4 38.4
20.7
Average for dry season
40.3 29.5 23.5
Average all seasons 42.5 32.5 24.7
Source: Dairy farmers’ household survey
3.9.2.4 Types of Hay Purchased
The main types of hay purchased by the farmers were the grass and leguminous hay. The grass
hay included Rhodes, ryegrass, brome and orchard while the leguminous hay was mainly
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
39
Lucerne, berseem, cowpea and soybean. Of the sampled treatment farmers who used hay, 58%
utilized grass hay, while 39% used the leguminous hay (Figure 3.8).
Figure 3.8: Types of Hay Purchased
Source: Dairy farmers’ household survey
3.9.2.5 Sources of Hay
The midline results show that majority of the treatment farmers sourced their hay from their
DHs as indicated by 54% and 56% of the treatment group farmers in the wet and dry seasons
respectively (Table 3.27). On the other hand, most of the control group farmers and farmers
during the baseline procured hay from mostly from traders during the wet and dry seasons.
This implies that the KMAP interventions through working with dairy hubs is an effective
mechanism for availing quality assured hay to farmers. It is therefore important to enhance the
capacity of dairy hubs to ensure that farmers have access to quality assured hay to its members.
It was further noted that most of the dairy hubs in Kiambu, Embu and Nyandarua County
except did not stock hay to supply to their farmers. Only Nyala cooperative supplied their
members with hay. In the Rift Valley region, Torongo and Siongiroi DHs stocked hay and
supplied it to their farmers. Siongiroi DH had contracted farmers to supply hay to their stores.
This should be encouraged for the other Dairy hubs.
Table 3.27: Sources of Quality Assured Hay Source of Hay Wet season Dry season Baseline
Treatmen
t Control Treatment Control
Wet
season
Dry
season
Dairy hub/co-operative 54.0% 20.5% 56.0% 22.4% 18.2% 14.7%
Agrovet 32.8% 18.1% 29.6% 23.7% 24.2% 24.7%
Traders/agents/Trader association 45.2% 49.7% 34.9.3% 48.0% 55.6% 54.2%
Other farmers/neighbours 5.9% 21.6% 8.5% 13.4% 9.1% 11%
Source: Dairy farmers’ household survey
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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3.9.2.6 Level of Satisfaction with Quality Assured Hay
The midline results revealed that, overall the farmers in the treatment group had a higher
proportion (28.5%) of those who ‘strongly agree’ with the statements measuring satisfaction
(affordability, quality, availability, trustworthiness, willingness to continue purchasing hay) than
the control group farmers (20.9%) and the baseline (15.7%). This is illustrated in Table 3.28. It is
however important to note that the level of satisfaction related to price was low for farmers
both in the treatment and control group. Interventions that can lead to affordable quality
assured hay would go a long way in improving the efficiency for milk production.
Farmers showed willingness to continue using hay but emphasized on availability of good quality
hay. For treatment farmers, 45.8% indicated they strongly agreed that they will buy hay if the
quality is assured. A huge proportion of the farmers strongly agreed that they will continue and
also increase purchase of hay in the future. There was almost a similar trend on the control
side, 50% of the farmers strongly agree that they will buy hay if the quality is assured. A
considerable proportion agreed that they were willing to increase the purchase of hay in the
future.
Table 3.28: Agreement Scale on Satisfaction with Hay
Attributes
Level of Satisfaction (Treatment)-% Midline Control
(Strongly agree)-%
Baseline (Strongl
y agree)-%
Strongly disagree
Disagree Neither agree or disagree
Agree Strongly Agree
I am satisfied with the price of hay
33.5 18.8 15.7 23.0 8.9 1.8 9.7
I am satisfied with the
quality of hay
2.6 16.9 17.5 37.6 25.4 13.8 12.3
I am satisfied with the availability of hay
11.6 9.0 9.0 43.4 27.0 15.8 14.5
I trust the providers who sell me hay
3.2 11.1 18.9 39.5 27.4 9.3 15.2
I will continue to
purchase hay in the future
10.2 7.5 11.2 40.6 30.5 26.4 16.1
I plan to Increase my
purchases of hay in the future
10.0 8.4 10.0 36.8 34.2 29.1 18.1
If quality assured hay is made available in the market, i will purchase it
6.8 5.8 7.4 34.2 45.8 50.0 24.2
Average 11.1 11.1 12.8 36.4 28.5 20.9 15.7
Source: Dairy farmers’ household survey
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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3.9.2.7 Perceived Benefits of Quality Assured Hay
Farmers in both the treatment and control groups rated increased milk production, increased
incomes, healthier cows and higher quality milk production as the perceived benefits of using
quality assured hay. This is presented in Table 3.25 below.
Table 3.29: Benefits of using Quality Assured Hay from farmers’ perception
Benefits Treatment Control
N % N %
Increased milk production 148 85.1 64 90.1
Increased income 117 67.2 41 57.7
Less variation in milk production 74 42.5 6 8.5
Higher quality milk produced36 96 55.2 23 32.4
Healthier cows 116 66.7 40 56.3
None 4 2.3 1 1.4
Source: Dairy farmers’ household survey
3.9.3 Market Systems Change Level for Commercial Hay Production Component
The market systems changes for commercial hay production based on the Adopt Adapt Expand
and Respond (AAER) model are discussed in Annex 10.
3.10 Results on Program’s Impact on the Farmers/Target Beneficiaries
The expected impact of the KMAP program is job creation and increasing farmers’ incomes.
This section will therefore discuss the increase in farmers’ revenues from sale of milk, as a
measure of incomes as well as review the number of new jobs created. This section will
further discuss the social and economic benefits accruing from dairy farming that have and
impact of building the resilience of the dairy farmers’ households to cope with social, economic
and climate change shocks.
3.10.1 Most Significant Changes to Dairy Farming
The evaluation sought to establish from both treatment and control group farmers the most
significant changes that have occurred to their dairy farming in the last 12 months. This is
illustrated in Figure 3.10 below. Increased milk production, increased incomes, healthier cows,
consistency in milk production and reduced A. I failures/increased conceptions were identified
as the most significant changes in dairy farming experienced by farmers both in the treatment
and control groups.
36 The quality of feeds affects the butter fat content in milk, taste of the milk and the level of aflatoxins in milk. It
should however, be noted that milk quality is also affected by other factors including milk handling (post-harvest), udder management, presence of antibiotics residue etc.
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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Figure 3.10: Most Significant Changes in Dairy Farming
Source: Dairy farmers’ household survey
3.10.2 Contribution of Dairy Hubs/Co-operatives to Most Significant Changes to
Dairy Farming
Dairy cooperative/dairy hubs were the most important KMAP’s intervention entry point. It is
therefore imperative to understand just how this contributed to the changes that were
experienced at the farm level. Majority (43% in treatment and 42% in the control) rated
provision of quality trainings / seminars on dairy practises as the main contribution which led to
the significant changes in dairy production (Figure 3.11).
Figure 3.11: Role of Dairy Hubs in Most Significant Changes
Source: Dairy farmers’ household survey
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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Farmers attributed the information and training they received from the dairy hubs as an
important factor contributing to increased milk production, reduced AI failures and healthier
cows. Information has been identified as a major factors supporting of inhibiting adoption and
use of improved innovations. So if farmers are able to received quality information from a
trusted source, then they are able to make rational decisions. This is supported by the second
listed factor, that dairy cooperatives/hubs offered good extension services (12% treatment). At
least 18% of the control group also mentioned that the dairy cooperatives provided credit
services/loans. Again, lack of access to affordable credit can inhibit technology adoption,
especially for capital intensive enterprises such as dairy.
3.10.3 Resilience Analysis
The resilience data was collected and analyzed based on 6 livelihood assets/ capitals as defined
by the DFID’s Livelihood sustainability framework (see annexed). The six (6) capitals include:
human capital; increased knowledge and skills; social capital; physical capital; financial capital; and
natural capital. The farmers’ perception of benefits accruing from dairy farming was measured
for each of the capitals using a likert scale of 1 to 5, where 1 represents least benefited and 5
represents most benefited. The overall index for each of the aspect (human capital; increased
knowledge and skills; social capital; physical capital; financial capital; and natural capital was
derived by getting the average indices for each of the benefits describing each capital. This is illustrated in Table 3.30.
Overall, both the treatment and control group had an above average level of benefit on all
aspects measured, with the treatment group experiencing more benefits than the control group
on all aspects (Figure 3.12), albeit with not very big differentials. This may be attributed to the
KMAP interventions that led to farmers in the treatment groups having more incomes from the
sale of milk as well as having more knowledge on dairy production.
Figure 3.12: Role of Dairy Hubs in Most Significant Changes
Source: Dairy farmers’ household survey
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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Table 3.30: Social and Economic Benefits
Socio-economic Benefits Treatment Control
Human Capital
Improving health 3.85 3.96
Improving nutrition 3.99 3.98
Improving education 3.97 3.85
Average 3.94 3.93
Increased Knowledge and Skills
Improving capacity to work at the farm/enterprise 3.45 3.05
Improving capacity to adapt and diversify sources of livelihoods 3.46 2.98
Average 3.45 3.01
Social Capital
Increasing networks and connections 3.36 2.90
Improved relations of trust and mutual support 3.53 3.03
Joined formal and informal groups-chamas 3.48 3.15
Improved mechanisms for participation in decision-making and agency 3.21 3.01
Average 3.39 3.02
Physical Capital
Was able to acquire tools and equipment for production , e.g. jembes,
seed, fertilizer, pesticides
3.35 3.38
Was able to acquire means of transport –motor cycle, bicycle,
wheelbarrow, donkey carts, vehicles, etc
3.10 2.69
Secured/improved shelter and buildings 3.18 3.01
Improved Energy-solar, wind, biogas etc 2.90 2.57
Average 3.13 2.91
Financial Capital
Improved Savings, Chamas, Mobile Banking Etc 3.22 3.00
Acquired insurance 2.48 1.96
Expanded/deepened business 2.88 2.53
Able to access credit and reduce debt 3.20 3.06
Reduced reliance on remittances 3.16 3.01
Increased wages 3.10 2.89
Average 3.08 2.87
Natural Capital
Bought or leased more land 2.42 2.13
Developed/acquired improved water resources 2.69 2.72
Planted trees and forest products 2.78 2.52
Average 2.63 2.46
Source: Dairy farmers’ household survey
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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4 CHAPTER 4 ACHIEVEMENTS OF PROGRAM INDICATORS
Based on the findings from the impact assessment, a summary of the program achievements
based on the set targets and comparing with the baseline survey values are discussed in this
section.
In terms of the impacts of the program, the average yield per cow per day for the two seasons
stood at 8.9 litres against a target of 10.7 litres, thus missing the set target by 1.8 litres. This is
when compared to the control group whose average was 7.8 litres per cow per day. Since the
average milked cows for the treatment groups were 3, the total daily milk yields were 26.7
litres per household, with an average price of Kshs. 36, this earned the household a total
revenue of Kshs.1, 002 per day on average. After deducting the daily variable costs per cow
which averaged Kshs, 137.7, this further resulted to gross margins of Kshs 196.5 per cow per
day during the wet season and Kshs. 148.4 per cow per day during the dry season.
The number of farmers that accessed information and inputs reached 28,120 by midpoint of the
program against a set target of 44,26437 (63.5% achievement). The trend is similar with the
number of farmers who active members and accessing improved supply chain services reaching
25,900 farmers against a target of 42,203 farmers (61.4% achievement). The number of dairy
hubs with increased access to retail markets was 14 against a set target of 8DHs and 3
processors. However, only 5 dairy hubs and 2 processors improved customer-centric
distribution and retail strategies and new product innovations and marketing strategies out of
the 16 dairy hubs and 5 processors envisaged (31% achievement). New ICT solutions were to
be purchased by 8DHs and 3 processors but only 5 DHs and 3 processors purchased (73%
achievement).Investments in improved supply chain management practices were carried out by
5 dairy hubs against the 20 (25% achievement) envisaged. Energy efficiency technologies were
adopted by 5 DHs and 1 processor as envisaged.
The average price of insemination was also slightly higher at Ksh 1,578 against a target of Ksh
1,316. The higher prices were as a result of increased preference for exotic semen which was
more costly to local semen. The proportion of farmers who used accredited AI services
exceeded by 18% to reach 72.7% against a target of 55% (118% achievement). A total of 218 AI
service providers from 7 Counties invested in customer service training against a set target of
200 (105% achievement). The number of internal and independent providers investing with
relevant market actors in promotional and marketing activities was 12 against a set target of 15
(90% achievement).
The number of farmers accessing quality assured fodder was 24.083 against a target of 14, 850
(171% achievement) while 28.5% of the farmers strongly agreed they were satisfied with the hay
they received against a target of 25%. The proportion of farmers purchasing hay that was
37 This is because the number of farmers benefitting from supply chain services was only 37,000, much less than
the set target.
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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termed as of “very good quality” was reported by 42.5% of the farmers against an envisaged
52.5%. Only two CHPs38 invested in soil testing and with labs in co-branding against a set target
of 5 for soil testing and 2 for co-branding. The two CHPs were also expected to access
working capital/assess financing and/or equity, and this was achieved. More details on the
achievement of targets are illustrated in Table 4.1 below.
38 Hay N Forage and Sochon
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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Table 4.1: Summary of Program Achievements per Indicators Issue/
Level
Key Result Indicators Baseline Mid line 2016
Targets 39
Achievement
Increasing incomes to
farmers from milk
sales
% increase in income from sale of milk
Dry season- 258 per day
Wet season- 278 per day
• Dry season-286.1
• Wet season- 334.2
Not set 17.8% increment during the dry season
80.2% increase during the wet season
Total revenue generated from the sale of milk in Ksh.
Wet season – Kshs.1,002.6 per day per hhd Dry season – Kshs. 858.4 per day per
household40
Not set
Additional revenue generated from the sale of
milk in Ksh.
Wet season – Kshs. 223 per head per day
Dry season –Kshs. 46.1per head per day41
Not set
Dairy- Formal Supply Chain
Target Group Change
Farmers Increase milk sales at farm level42
Total Volume of milk sold in litres
Wet season – 21.3 litres per household Dry season -16.8 litres per household
Not set
Additional volumes of milk sold in litres
Dry season- 14 per day Wet
season- 15.2 per day
Dry season- Additional 2.8 litres per day Wet season- Additional 6.1 litres per
day
% increase in volumes of
milk sold
Dry season-20%
Wet season- 40.1%
No targets
set
Farmers increase milk
yields at farm level43
Aggregate yield per day Dry season- 24
Wet season- 29.1 Average -26.6
No targets
set
Average yield per cow per
day
Dip stick
values(2014)
Dry season- 8.0
Wet season- 9.7
10.7 Target missed by 1.8
litres
39 Sourced from the 2016 projections in the KMT intervention plans 40 Reported per household 41 Per household and per cow 42 Cover all beneficiaries 43 Covers all beneficiaries
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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Issue/ Level
Key Result Indicators Baseline Mid line 2016 Targets 39
Achievement
at 7.02 liters Average- 8.9
Other farmers increase milk yields at
farm level
Average yield per cow per day for non-target farmers
Dry season- 8.7
Wet season- 11.7 Average-
10.2
Dry season- 7.5 Wet season- 9.3
Average-8.4
No targets set
Achievements were lower than the baseline
values
Farmers access better information and inputs
through improved distribution and retail channels
No. of farmers accessing information and inputs
76% (28,12044) 44,264 Targets not met. (63.5% achievement)
This is because the number of farmers benefitting from supply
chain services was only 37,000, much less than the set target
Level of satisfaction of services being offered and relationship with service
providers
84%
Farmers access better market for their milk
% of milk sold through DHs and formal channels
70% 93% 80% Exceeded by 13% (113% achievement)
Farmers have increased access to better supply chain
services
No of farmers who are active members and accessing improved supply
chain services
70% = 25,90045 42,203
Targets not met. (61.4% achievement) This is because the
number of farmers benefitting from supply chain services was only
37,000, much less than the set target
Level of satisfaction of
farmers on supply chain services and relationship
Price offered for milk-52%
Timeliness of milk collection-76% Timeliness of milk payment-72%
Qualitative
(Targets not set)
44 76% of total number of beneficiaries (37,000) 45 70% of total number of beneficiaries in the supply chain component (37,000)
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Issue/ Level
Key Result Indicators Baseline Mid line 2016 Targets 39
Achievement
with DH or processor Information-78% Average-70%
Market System Change
Other DHs and processors improve their supply chain services to their
farmers (transport, timely payments, information, pricing,
etc.)
Perception of utility by non-target DHs/processors on providing quality services
to customers/farmers
Price offered for milk-38% Timeliness of milk collection-74% Timeliness of milk payment-66% Information-70%
Average-62%
Targets not set
DHs and processors have increased access
to retail markets of their products
No of DHs with increased access to retail markets
14 dairy hubs with 22,82846 registered farmers
8 DH and 3 processors
Targets exceeded (127% achievement)
Other DHs and processors crowd in and invest in improved customer-
centric distribution and retail strategies
No of non-target DHs and processors investing in improved customer-centric distribution and
retail strategies
3-Sogoo dairy Co-operative, Donyo Lesos Dairy Co-operative, Nabaya Cooperative and Nalepo Olepolos Dairy Cooperative)
Targets not set
DH and processors invest in improved customer-centric distribution and retail
strategies
No. of DHs and processors investing in improved customer-centric distribution and
retail strategies
5 dairy hubs - Limuru, Karate, Njabini, Gatamaiyu and Nyala. 2 processors, KCC and Lattana
16 DH, 5 processors
Targets not met (30% achievement)
No of target DHs and
processors renewing or continuing their investments in improved customer-centric
distribution and retail strategies after initial engagement
5 dairy hubs - Limuru, Karate, Njabini,
Gatamaiyu and Nyala. 2 processors, KCC and Lattana
16 DH, 5
processors
Targets not met
(30% achievement)
DH and processors No. of DHs/processors 5 dairy hubs - Limuru, Karate, Njabini, 16 DH, 5 Targets not met
46 Beneficiaries of KMT MAP
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Issue/ Level
Key Result Indicators Baseline Mid line 2016 Targets 39
Achievement
invest in innovative products and/or new marketing strategies
targeting different customer segments
with new product innovations and/or marketing strategies
Gatamaiyu and Nyala. 2 processors, KCC and Lattana
processors (30% achievement)
DH and processors
invest in energy efficiency upgrades through technology
firms
No. of DHs/processors
that have purchased new or additional energy efficiency solutions
5DHs and 1 processor 6 Targets met
(50% achievement)
DHs and processors negotiate agreements
with finance providers for debt, equity, and/or private
investment
No. of contract agreements signed
between DHs/processors and finance providers
3- Lattana Dairy Ltd, Lari and Limuru processors
6 DH, 1 processor
Targets not met (50% achievement)
DHs and processors invest in ICT
solutions for improved operational efficiency
No. of DHs/processors that purchased new or
additional ICT solutions
5 DHs and 2 processors 8 DH, 3 processors
Targets not met (63.6% achievement)
DHs and processors invest in improved supply chain
No. of DHs and processors investing in improved supply chain
management practices
5 dairy hubs - Limuru, Karate, Njabini, Gatamaiyu and Nyala. 2 processors, KCC and Lattana
20 Targets not met (40% achievement)
No. of target DHs and
processors renewing or continuing their investment in improved supply chain management
practices after initial engagement/contract
5 dairy hubs - Limuru, Karate, Njabini,
Gatamaiyu and Nyala. 2 processors, KCC and Lattana
20 Targets not met
(40% achievement)
Dairy- Informal Supply Chain
Target Group
change
Other farmers increasing the use of
inputs and services through milk
No. of non-target farmers accessing inputs through
arrangements facilitated by the trader/village agents
AI-3% Hay-6%
Supplements and concentrates-5%
Targets not set
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Issue/ Level
Key Result Indicators Baseline Mid line 2016 Targets 39
Achievement
traders/village agents
Farmers increase use of quality inputs and services through
traders/village agents
No. of farmers using quality inputs through arrangements facilitated by
the trader/village agents?
AI-6% Hay-7% Supplements and concentrates-6%
Average-6% Total=2,22047
38,640 Targets not met ( Need to revise this target)
(6% achievement)
Market
system change
Other traders increase
demand for quality milk from farmers and sale of milk to
processors
No. of non-target farmers
accessing inputs through arrangements facilitated by non-target traders (SCI)
Targets not
set
Other traders invest in branding, new
products and new retail models
No. of non-target traders adopting branding, new
products and new retail models (SCI)
2- All Seasons Milk Bar worked with a
brand and design firm (Renovazone) to redesign the milk outlets to meet the KDB and public health retail
certification requirements Prime Cut Ltd, a milk trader in Kisumu County has been able to
independently invest in product differentiation and a brand ‘moo’ targeting low income earners
Targets not set
Traders increase sales of milk due to improved supply chain
management
Litres of milk sold per day Prime Cut Ltd, a milk trader in Kisumu County increased daily milk intake from 50 litres per day to 2,000
litres per day
Targets not set
Dairy- Improving and Promoting AI Service
Target
group change
Farmers receive
higher price from the sales of the improved bulls and heifers
• Revenue generated in
Ksh annually from sale of improved bulls and
heifers
Heifers-
156,847,104 Bulls-
441,443,520
Other farmers % of non-target farmers 49.8% 57.8%
47 6% of beneficiaries of supply chain component (37,000)
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Issue/ Level
Key Result Indicators Baseline Mid line 2016 Targets 39
Achievement
increase use of AI from well-rated AI providers
who used accredited AI for last AI service
Farmers increase use of AI from well-rated accredited AI
providers
Average price per insemination from internal/independent
service providers (Ksh)
1,523 • Local semen – Ksh. 1000;
• Exotic – Ksh. 1000-3000;
• Sexed- Ksh 6000-700048 Average- 1,578
1,316 Not achieved. – (84% achievement)
Proportion of farmers who used accredited AI for last AI service
35.3% 72.7% 55% Target exceeded by 18% (118% achievement)
Proportion of farmers purchasing breed services from an accredited AI
service provider
35.3% 72.7% 30% Target exceeded by 43% (143% achievement)
Proportion of farmers who "strongly agree" that
they are receiving affordable, quality, available, trustworthy
services from AI providers (average)
17% 35.8% 50% Target not achieved but there is an increase as
compared to the baseline (72% achievement)
Market
systems change
A.I providers offer
improved quality services
% change in insemination
success rate
75.4 79.2 85.4 Target not achieved
(93% achievement)
% change in awareness of existence of "accredited"
AI services by farmers.
75.9 75.4 Target exceeded by 0.5 (109% achievement)
Other AI providers
offer improved quality services
% change in insemination
success rate
68 Target not
set
% change in awareness of existence of "accredited"
AI services by farmers.
67 Target not set
AI providers have improved customer
service and business
No. of internal/ independent AI providers
investing in customer
• 7-Njabini, New Ngorika, Siongiroi, Nyala, Muki, Tulaga and Karate
200 Target exceeded
(109% achievement)
48 Source: Key informant interviews with Independent and Dairy Hub based AI providers
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Issue/ Level
Key Result Indicators Baseline Mid line 2016 Targets 39
Achievement
skills to build farmer confidence in the service
service training from relevant market actors
• 218 AI service providers from 7 counties invested in customer
service training through the Continuous Professional Development (CPD) training
facilitated by LGS.
Other non-target AI providers have
improved customer service and business skills to build farmer
confidence in the service
No. of non-target internal/independent AI
providers investing in customer service training from relevant market
actors
By benchmarking with Siongiroi, 5 DHs in the Rift Valley (Chebusot,
Torongo, Naitiri, Lessos and Cherobu) have adopted several accreditation components.
Target not set
Internal/independent
providers invest in promotional and marketing activities
with relevant market actors
No. of internal and
independent providers investing with relevant market actors in
promotional and marketing activities
12 (Muki, Nyala, Karate, Kitiri, Tulaga,
New Ngorika, Njabini and Siongiroi, Caritas Embu, Githongo, Katheri and Buuri)
15 Target not achieved
(90% achievement)
Dairy-Commercial Hay Production
Target Group Change
Other farmers increase use of quality assured
fodder, both during the dry and rainy seasons
No. of non-target farmers accessing quality assured fodder, both during the dry and
rainy seasons
Rainy Season-56.5% Dry Season-87.8%
Targets not set
Farmers increase use of quality assured fodder,
both during the dry and rainy seasons
No. of farmers accessing quality assured fodder, both during the dry and rainy seasons
Rainy Season-61.5% Dry Season-93.2% Average-77.3%
Total = (24,083) 49
14,850 Targets exceeded by 71% (171% achievement)
Proportion of farmers claiming to purchase and use "very
good" quality hay
35.4 42.5 52.5 Targets not achieved by 10%
(90% achievement)
% of farmers who "strongly 15.7 28.5 25 Targets exceeded by
49 Proportion of farmers selling*Total beneficiaries feeds component (32,067)
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Issue/ Level
Key Result Indicators Baseline Mid line 2016 Targets 39
Achievement
agree" on the satisfaction of price, quality and availability of hay; including future
investments in hay (Average)
3.5% (104% achievement)
Other CHPs sell more affordable
and high quality fodder
No. of non-target farmers selling more affordable and high
quality fodder
No data Targets not set
Other CHPs invest in soil testing
No. of Other CHPs investing in soil testing
0 Targets not set
CHPs investing in soil testing
What is the No. of CHPs investing in soil testing
2-Sochon, hay and forage 5 Targets not met (40% achievement)
CHPs invest in
co-branding of fodder
No. of CHPs investing with labs
in co-branding?
2
• Hay N Forage linked to Crop Nutrition Laboratory Services (Crop Nuts)
• Sochon worked with Agri-quest laboratories
2 Target achieved
(100% achievement)
CHPs access to working capital, asset-financing
and/or equity
No. of CHPs accessing working capital/assess financing and/or equity
Three financial institutions (Root Capital, Kenya Commercial Bank and Chase Bank) are providing debt
financing to commercial hay producers. A total of KES 26 Million has been extended to Hay N Forage
and Sochon towards business expansion, New KCC has secured an
undertaking of KES 800 million from Kenya Commercial Bank to pay for quality hay supplies.
2 Targets achieved (100% achievement)
Amount accessed by CHPs in working capital/asset financing and/or equity
Ksh 26 million Targets not set
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5 CHAPTER 5: CONCLUSIONS AND RECOMMENDATIONS
5.1 Summary of Findings and Conclusions
The MAP program was designed to work in partnership with the private sector and
government to transform how dairy sector markets work so that they could become more
inclusive and more competitive. This is to be done by facilitating the realignment of the
incentives, capacities, relationships and rules which govern how markets work using the
"Making Markets Work for the Poor (M4P)" approach. This was to be done by interventions in
improving management and structures, improving AI services and promoting availability of
commercial hay to farmers.
Generally, the KMAP program has achieved a lot in terms of enhancing the supply chain
management and structures, improving AI services and promoting availability of commercial hay
to farmers so as to improve dairy sector markets so they become more inclusive and more
competitive and hence improve the production and incomes of small holder dairy farmers. This
is important bearing in mind that majority of the beneficiary farmers (66%) interviewed in the
relied on sale of milk as their main source of income.
The three years of implementation of the KMAP program 56,927farmers benefitted from the
program with a wide range of impacts. These impacts include, increase in incomes and
consequently building of farmers’ resilience to deal with social, economic and climate change
shocks. Overall, the average yield per cow per day for the two seasons stood at 8.9 litres
against a target of 10.7 litres, thus missing the set target by 1.8 litres. This is when compared to
the control group whose average was 7.8 litres per head. Since the average milked cows for the
treatment groups were 3, the average daily milk yields were 26.7 litres per household, with an
average price of Kshs. 36, this earned the household a total of Kshs.961 per day on average.
These further resulted to gross margins of Kshs 207 per cow per day during the wet season
and Kshs. 125 per cow per day during the dry season. This is lower than the recommended
gross margin of Ksh 267.1550. This implies that there is an opportunity of improving efficiency in
the dairy value chain to ensure that it is more profitable. KMAP has also enabled the famers to
gain from human capital benefits; increased knowledge and skills; social capital benefits; physical capital benefits; financial capital benefits; and natural capital as a result of engaging in dairy
farming.
Supply Chain
The farmers are also adopting new innovations promoted by KMAP thorough its implementers
in the private and public sector, as it was noted that the farmers practicing zero grazing grew
from 65.8% during the baseline to 69%. It was also notable that KMAP beneficiaries had
adopted pedigree and improved cows than the non-beneficiary farmers. This could be
50 Undated report: Findings of Moi University Agshare Pilot Project on Dairy Value Chain.
http://www.oerafrica.org/FTPFolder/Agshare/Marketing%20and%20Price%20Analysis/DairyFarmersResearchReport.pdf
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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attributable to capacity building under the project implementation as well as the ability of such
farmers to provide proper management through quality feeding and AI services.
Milk yields were also noted to be higher in the program beneficiary dairy hubs both during the
wet and dry seasons with averages of 9.7 litres and 8.0 litres during the wet and ry seasons
respectively. Further, the volumes of milk sold increased by 20% during the wet season and
40.2% during the dry season with the daily total volume of milk sold per household being 21.3
litres during the wet season and 16.8 litres during the dry season. This constituted 80% of the
total milk yields. Increase in volumes marketed was associated both with the increased yields
and access to more reliable markets.
The farmers selling milk through formal channels (Dairy co-operative/hubs and private
processors) increased from 70% in the baseline to 93%, implying that Dairy co-operatives/hub
were found to be the most preferred marketing channels mainly used to market milk by the
smallholder farmers. This is because the dairy hubs offer other integrated services from farmers
apart from buying milk including advance payments, feeds and AI on check off system and
extension services in some cases. In view, it is important to continue empowering the dairy
hubs to be viable business entities which would be instrumental in propelling smallholder
farmers from poverty.
Beneficiary farmers that had access to information and inputs were 76% (28,120 farmers).
Farmers’ accessing improved supply chain services was 70%, (25,900 famers). Bearing in mind
that the dairy hubs are the main provider of these services is a strong indication that farmers
are accessing better supply chain through improved distribution and retail channels. It was
however noted that the farmers were not satisfied with the prices they get for the milk the sell
and the prices they get from inputs such as AI, hay, feeds among others.
One of the interventions of the KMAP program is improving the informal supply chain services
by working with agents and traders. From the study, only 6% (1,927 farmers) accessed
information and inputs from traders and agents. It is therefore important to work with these traders and agents to ensure that the milk is handled in a safe manner and encourage them to
offer integrated services to attract more clients.
Increased professionalism in dairy enterprise management through improved supplier and retail
management is one of the key objectives of the KMAP program through efforts such as
investing in ICT solutions, investing in energy efficiency upgrades, adopting customer focused
marketing and distribution strategies, development of strategic plans and ensuring access to
finance. This is being implemented in partnership with the private sectors.
Adoption of ICT is important in improving the efficiency and effectiveness of the supply chain by
reduction of transaction and coordination costs. It was noted that very only five of the dairy
hubs had adopted ICT based systems to improve their operations. However, KMAP is making
efforts to develop user friendly ICT solutions to dairy hubs using partners such as iProcure that
develops systems that improve distribution of inputs and information. These systems are easily
adaptable to other dairy hubs even outside the KMAP intervention areas. A positive trend
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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noted is that three ICT firms have developed hotlines, authentication and rating platforms, and
12 agrovets are already using those platforms.
It was noted that 5 dairy hubs (Limuru, Karate, Njabini, Gatamaiyu and Nyala) and 2 processors,
(KCC and Lattana) were active in investing in improved customer-centric distribution and retail
strategies and in improved supply chain management practices. Some non-beneficiary dairy hubs
such as Sogoo dairy Co-operative, Donyo Lesos Dairy Co-operative, Nabaya Cooperative and
Nalepo Olepolos Dairy Cooperative also crowded in and invested in improved customer-
centric distribution and retail strategies.
It was notable that there is a lot of potential for the dairy hubs exposed to the interventions of
professional management companies continued to improve their business operations and thus
improving the performance of the dairy enterprises. Overall nine (9) of the intervention dairy
hubs had membership numbers growing by between 8% and 317%. Quantity of milk handled
also increased in seven (7) of the dairy hubs by between 11% and 94%. Turnover increased by
between 2% to 100% in eight (8) of the dairy hubs.
Other benefits reported by the dairy hubs included:
• Increased customers and sales;
• Improved stocks display and management;
• Improved access to financial resources;
• The dairy is now more focused on the growth path due to having strategic plan;
• Market research plan has enabled them to venture into new markets;
• Training on customer service helped reduce complaints from farmers and other clients
Five dairy enterprises were also linked with energy technology companies to work towards
creating energy efficiency solutions.
Improving and Promoting AI Service
Usage of accredited AI services has more than doubled from 35.3% in the baseline to 72.7% at
the midline. This may be attributed to KMAP’s strategy of leveraging the interconnectedness of
various market systems that are important to dairy, specifically breed improvement (through
provision of accredited AI services), feed, and veterinary services. The satisfaction levels with
the aspects of quality, availability and trustworthiness of the AI services were quite high. Those
farmers that were strongly satisfied with quality, availability and trustworthiness were 27.8%,
31.2% and 32.6% respectively as compared to 15%, 19% and 19% respectively in the baseline.
However, it is noteworthy that the farmers had a problem with the pricing of the AI services
because it is the aspect that exhibited the lowest satisfaction levels (14.6%). There is therefore
need to subsidize these costs so as to further increase the adoption of accredited AI services
and open up more space to more actors to provide accredited AI services.
Farmers complained that milk prices were lower yet Inputs costed higher. Milk prices ranged
from Kshs. 31.5 to Kshs 39.5 depending on the outlet. Prices for inputs such as A.I ranged from
Kshs 1,000 to Kshs 7,000 depending on the type (local, exotic, sexed etc) and source, while
prices of hay ranged from Kshs.250 to Kshs 450 depending on source, type of grass and season.
Different animal feeds had varying prices.
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The main benefits the farmers got from the AI services include: increased milk production from
offsprings (77.5%); healthier calves (75.7%); high conception rates (68.6%); increased incomes
(63.2%). As a result of improved breeds, farmers earned a total of Ksh 163,732,957 from the
sale of improved heifers and bulls.
Efforts were made to ensure that AI service providers have improved customer service skills to
build farmer confidence in the AI service. This was done through various dairy hubs partnering
with private sector service providers, County Governments and LGSA to improve their
customer service skills. These include: Njabini, Nyala, Muki, Tulaga, Karate, Siongiroi,
(Chebusot, Torongo, Naitiri, Lessos and Cherobu)51. Accredited AI service providers reported
increased AI services provision by 61% between 2013 and 2016, implying an increase in number
of customers served.
AI service providers invested in promotional and marketing activities with relevant market
actors. Joint planning and financing was adopted as an efficient and effective model of delivering
quality services to small holder farmers. For instance, 8 DHs (Muki, Nyala, Karate, Kitiri, Tulaga,
New Ngorika, Njabini and Siongiroi) invested in joint promotional and marketing activities in
partnership with Twiga, Bimeda, Pokea, Indicus and Coopers. Five (5) dairy hubs (Nyala, Muki,
Karate, Njabini and Siongiroi partnered with two (2) processors (Brookside and Kinangop
Dairy) and five (5) genetics supply companies (Bimeda, Pokea, ABS, Twiga and Semex) for joint
AI promotional events.
Commercial Hay Production
Awareness of farmers on quality assured hay has increased from 9.1% at baseline to 41%. On
average 77% of the beneficiary farmers access quality assured hay during both the wet and dry
seasons. This implies that there is a high potential for purchase of additional hay products.
Eighty percent (80%) of the farmers indicated that they would be willing to purchase hay as long
as the quality is assured. This creates an opportunity for the private sector players can explore
business opportunities in hay preservation and marketing to make it available to small holder
farmers all year round.
The main benefits the farmers got from the use of quality assured hay include: increased milk
production (85.1%); increased incomes (67.2%); healthier cows (66.7%); higher quality milk
(55.2%); less variation in milk production (42.5%). The increased incomes enhance the dairy
farmers’ resilience to cope with social, economic and environmental shocks.
Through the project intervention, farmers were now able to access quality feeds such us quality
assured hay, which could be used during the dry season. This was made possible by linking
farmers with commercial hay producers, which meant that even without their own production;
farmers were able to source the feeds from the commercial producers. It was noted from the key informants that farmers used fodders from their farms and the surrounding during the wet
season. However, hay was good for dry seasons.
51 Benchmarked with Siongiroi
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In addition to there been overall milk production per cow, it was noted that the difference
between milk produced across the seasons was still big at 1.7 litres. This would mean that
although KMAP interventions, and especially by availing hay for dry season feeding is being
undertaken, there is still work to be done to ensure that the seasonal fluctuations in milk
production are reduced. Proper feed budgeting throughout the year is therefore paramount to
ensure that farmers preserve fodder or have access to preserved fodder for them to purchase.
The availability of hay becomes handy to solve this challenge. Information gathered indicates
that only a handful of dairy hubs stocked hay in their feed stores, more so in the Central Kenya
region.
Efforts have been made to ensure that there is access to quality and affordable hay to
smallholder farmers through piloting with Hay N forage and Sochon to show the viability of
commercial hay farming. However, this is gaining acceptance because by in the last quarter of
2015 crossing over to the first quarter of 2016, the number of commercial hay producers has
increased to 28, with an equivalent rise in outreach numbers. KCC is also creating linkages
with Commercial Hay Producers to supply its customers with hay. County Governments are
also crowding in with Laikipia and Narok intending to fund hay production ventures. It was also
notable that about 55% of the intervention farmers procured their hay from their dairy hubs,
thus the need to enhance linkages between dairy hubs and hay produces to ensure that quality
assured hay is accessible to farmers in a timely and affordable manner.
Achievement of Targets
Overall, the program the achievement rate of the set targets was over 50% for most of the
program indicators including:
• Additional revenue from sale of milk -156% achievement;
• Additional volumes of milk sold in litres-105% achievement;
• Average yield per cow-110.3% achievement;
• No. of farmers accessing information and inputs-63.5% achievement;
• % of milk sold through DHs and formal channels-113% achievement;
• No of farmers who are active members and accessing improved supply chain services-
61.4% achievement;
• No of DHs with increased access to retail markets-127% achievement;
• No. of DHs/processors that have purchased new or additional energy efficiency
solutions -100% achievement;
• No. of contract agreements signed between DHs/processors and finance providers-50%
achievement;
• No. of DHs/processors that purchased new or additional ICT solutions-63.6%
achievement;
• Revenue generated in Ksh annually from sale of improved bulls and heifers- Heifers
(101% achievement); Bulls (57% achievement);
• Average price per insemination from internal/independent service providers - 84%
achievement;
• Proportion of farmers who used accredited AI- 118% achievement;
• Proportion of farmers purchasing breed services from an accredited AI service
provider-143% achievement;
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• Proportion of farmers who "strongly agree" that they are receiving affordable, quality,
available, trustworthy services from AI providers-72% achievement;
• % change in insemination success rate-93% achievement;
• % change in awareness of existence of "accredited" AI services by farmers-109%
achievement;
• No. of internal/ independent AI providers investing in customer service training from
relevant market actors-109% achievement;
• No. of internal and independent providers investing with relevant market actors in
promotional and marketing activities-90% achievement;
• No. of farmers accessing quality assured fodder, both during the dry and rainy seasons-
171% achievement;
• Proportion of farmers claiming to purchase and use "very good" quality hay-90%
achievement;
• % of farmers who "strongly agree" on the satisfaction of price, quality and availability of
hay; including future investments in hay-104% achievement;
• No. of CHPs investing with labs in co-branding-100% achievement;
• No. of CHPs accessing working capital/assess financing and/or equity-100% achievement;
However, the following indicator targets had an achievement rate of less than 50%:
• No. of DHs and processors investing in improved customer-centric distribution and
retail strategies-30% achievement;
• No of target DHs and processors renewing or continuing their investments in improved
customer-centric distribution and retail strategies after initial engagement-30%
achievement;
• No. of DHs/processors with new product innovations and/or marketing strategies-30%;
• No. of DHs and processors investing in improved supply chain management practices-
40% achievement;
• No. of target DHs and processors renewing or continuing their investment in improved
supply chain management practices after initial engagement/contract-40% achievement;
• No. of CHPs investing in soil testing- 40% achievement;
5.2 Recommendations
The following recommendations are made based on the main findings and lessons learnt fro the
midline study.
a) The dairy hubs are the most important source of inputs and marketing channels for the
farmers. In view of tis, it is important for KMAP to continue empowering the dairy hubs
to be viable business entities which would be instrumental in propelling smallholder
farmers from poverty;
b) The use of key service providers for continuous professional development of dairy
hubs, milk traders, agrovets and other actors was noted as a good approach through
which challenges in supply chain management as well as delivery of A.I and animal health
services can be addressed. KMAP should therefore promote this approach to the wider
stakeholders in the dairy industry as a best practice and for wider impacts;
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
61
c) Benchmarking should be enhanced for dairy hubs and market actors that have adopted
and are implementing the program interventions well so that other actors may learn
from them. This may be done by developing case studies on the successful dairy
enterprises and organizing other dairy enterprises to learn from them.
d) The main challenges experienced by the AI providers are inadequate supplies, lack of
specialized semen handling facilities and equipment’s adnd facilities as well as perception
by farmers that AI services are expensive; and therefore slow uptake of A.I in some
areas. There is therefore need to provide assistance to the AI service providers to
aquire semen handling facilities and equipment as well as offering more training and
information on modern A.I services to dairy farmers focusing on the value proposition
for use of A.I services;
e) The study revealed that there were low numbers of DHs and processors investing in
improved customer-centric distribution and retail strategies. KMAP therefore need to
introduce new/innovative products and/or marketing strategies and improved supply
chain management practices so as to make greater impacts in the dairy sector;
f) KMAP in association with its partnerss should make efforts in enhancing appropriate
partnerships between the DHs, processors and private sector players as well as the
County Governments so as to improve on supply chain management, marketing and
retail strategies, as well as scaling up use of ICT to improve on the services provided to
farmers;
g) To ensure sustainability of the program interventions there should be concerted efforts
to involve the County Governments more intensely in the implementation of the KMAP
program. This is because implementation of livestock programs is a devolved function;
h) In order to effectively inform the program log frame, t is recommended that for future
evaluations, the same methodology applied in the midline assessment should be applied
in the end-line assessment to enhance comparability while the findings from the midline
assessment should be the basis for the setting the targets for the end-line evaluation.
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
62
6 APPENDICES
6.1 Appendix 1: Program Indicators
6.2 Appendix 2: Data Collection Tools
Double Click to Open
6.3 Appendix 3: DFID’s Livelihood sustainability framework
Dairy 2016 Indicators.zip
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
63
6.4 Appendix 3: List of Key Informants Interviewed
COUNTY DAIRY HUB TYPE KII NAME POSITION
Nyandarua Karati Treatment DH Official David Issy Njoroge Chairman
A.I Kiarie Mwangi Private
Agro vet Karati Agro Vet Manager
Njabini Treatment DH Official Peter Muhia Nduruhu Manager
A.I AI/Vet
Agro vet Peter Muhia Nduruhu Manager
Nyala Treatment DH Official Kelvin Ndegwa Dairy Manager
A.I DR. Richard Muraya A.I Provider
Agro vet Nyala Agro Vet Manager
CHP Nyala Hay & Forage Manager
Umoja Control DH Official David Macharia Manager
A.I Simon Maina Kanyua A.I
Agro vet Store Manager Store Manager
Nandarasi Control DH Official Julius Wahinya Kang'ethe Chairman
A.I Josphat K. Waithuki A.I
Agro vet Simon Maina Farmers Guide
Milk Trader Geoffrey Kinyua Milk Trader
Kahuru Control DH Official John M. Macharia Secretary
Kiambu Limuru Diaries Treatment DH Official Bidan Manager
A.I
Agro vet StoreStore supervisor
Gatamaiyu Treatment DH Official David Irungu Manager
A.I
Agro vet
Milk Trader Mary Njoroge (Mugunda)
Milk Trader
Kabete Control DH Official Morris Nzioka Manager
A.I Karanja Private
Agro vet Kabete DH Agro Vet Accountant
Embu Mkulima Bora Treatment DH Official Ms Florence Njeru Manager
A.I Dr. Opiyo-Farmlink Manager
Agro vet Dr. Opiyo-Farmlink Manager
Tumaini Treatment DH Official Leonard Nyaga Chairman
A.I Albert Gitonga Gichamu A.I Provider
Agro vet
Rugendo Treatment DH Official Henry Dickson Jomo Kagwithi
Chairman
A.I Augastine Mukundi Kariuki
A.I
Agro vet Dr. Opiyo-Farmlink Manager
Meru Processor Official Mr.Gitonga Production Manager
Feed manufacturer
Official Mr.Gitonga Production Manager
Bomet Singiroi Treatment DH Official Ann Bett Hub Manager
A.I Dr.Weldon Kirui A.I
Agro vet Singiroi Agro Vet Agro-vet Assistant
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
64
COUNTY DAIRY HUB TYPE KII NAME POSITION
Olbutto Control DH Official Vincent Langat Manager
A.I
Agro vet
Baringo Torongo Treatment DH Official Wilson Cheromei Assistant Manager
A.I John Kiprop A.I
Agro vet Robert/Lydia Clerks
Narok Ololulunga Treatment DH Official Winfred M Keiwa Chairman
A.I
Agro vet
Nakuru Technology Farm
CHP David Soisoi Director
Sochon CHP Director/Farm
Manager
Nairobi Dot Matrix BDS Willie Njoroge Director
Mac5 BDS Waweru Gichimu Managing
Consultant
PKF BDS Martin Muriithi Head of Agribusiness
Consulting
ConsumerPro BDS Jessica Kimathi Managing Director
Processors Processor Managing Director
6.5 Appendix 3: List of Documents Reviewed
i. Baseline assessment report on dairy hubs and their status in Kenya: November 2014
ii. Bebe, O.B., Udo, H.M.J., Rowlands, G.J., Thorpe, W., 2003 Smallholder dairying systems
in the Kenya highlands: cattle population dynamics under increasing intensification.
Livest. Prod. Sci. doi:S0301-6226(03)00013-7
iii. Dairy performance review rapid assessment report, March 2014
iv. Kenya Market Assistance Programme project closure report: Jan 2012 - Mar 2016
v. KMT Dairy intervention plans
vi. KMT Dairy sector evaluation baseline primary research report, Feb 2014
vii. KMT Dairy sector output reports: 2014-2015
viii. Review of MAP’s Dairy Sector Strategy, 2015-16: November 2014
ix. Undated report: Findings of Moi University Agshare Pilot Project on Dairy Value Chain.
http://www.oerafrica.org/FTPFolder/Agshare/Marketing%20and%20Price%20Analysis/Dai
ryFarmersResearchReport.pdf x. Staal, S., Pratt, A., & Jabbar, M. (2008). Dairy Development for the Resources Poor - Part 2:
Kenya and Ethiopia Dairy Development Case Studies. Rome, Italy: Pro-Poor Livestock Policy
Initiative. xi. Tegemeo Institute of Agricultural policy and development report on Productivity trends and
performance of dairy farming in Kenya, 2011
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
65
6.6 Appendix 4: Characteristics of the Treatment Dairy Hubs
N
o
Result Characteristics
Nyala
Nja
bin
i
Kara
ti
To
ron
go
Sio
ngir
oi
Tu
main
i
Lim
uru
Mku
lim
a
Bo
ra i
Ru
ge
nd
o
Olo
lolu
ng
a
Gata
maiy
u
1. Total Membership
2. 2012 10,000 _ 350 2957 8972 8,900 150 130
3. 2013 10,000 _ 500 2800 9690 9000 140
4. 2014 10,000 500 700 2845 10350 160 9500 80
5. 2015 11,963 610 750 2892 11228 160 9800 120
6. 2016 12,671 680 720 3037 12215 160 10365 625 208 140
7. Quantity of Milk in litres
8. 2012 624,301 1,545,270 Av150,000 4,353,227.99 7,594,815 1,080,000 759481
5
9. 2013 661,274 2,361,198 Av150,000 4,614,212.80 72,000 7,138,629 887,703 1,080,000 760,520 713862
9
10. 2014 659,032 378,637.5 3,964,275 Av150,000 4,641,531.80 360,000 6,666,655 1,588,480 1,080,000 980,340 666665
5
11. 2015 735,852 689,480 4,139,980 Av150,000 5,136,758.30 468,000 7,040,725 1,719,095 1,109,532 704072
5
12. 2016 577,917 618,192 4,049,572 Av150,000 5,136,758.30 7,155,656 1,007,776 720,000 1,111,820 715565
6
13. Turnover in Kshs
14. 2012 6,000,00 56,169,272 53,814,850 217,261,473 249,830,580 1,200,000
15. 2013 7,500,000 12,275,995.1 68,564,241 62,431,942 165,282,402 348,225,000 67,305,003 1,200,000 19,773,520
16. 2014 6,000,000 25,164,012.5 74,926,396 55,681,740.48 186,585,081 358,507,358 66,481,419 1,200,000 25,488,840
17. 2015 8,000,000 22,510,766.5 75,898,461 52,523,003.20 202,503,399 398,059,256 60,696,916 25,907,320
18. 2016 5,700,000 71,461,762 53,814,850 217,261,473 430,861,177 2,400,000
19. Where is the
milk sold?
Various
processors
direct sales to
residents
Brookside New KCC
Sun power
products
Brookside
dairies Ltd
KCC
Brookside
New KCC Sunflower
Products
Latanna
Pascha
Gwango
Yoghurt
Brookside
New KCC
Runyenjes
Superior
highlands
dairy
Brookside
30 milk
traders
20. Do you use
ICT
platforms?
Inuka Software
to manage
milk
recording,prep
rocess of
payments,
financial
reports
To manage milk
supplies and
payments
No
Uses Coop
works ICT
paltform
“da power’’
linking Milk
supply,Agrovet
and SACCO
Updating
records
Sending
messages to
farmers
Accounting
Financial
reporting
Not yet
embraced
technology
use.
21. Do you Quality AI About quality AI milk supply Information Milk quality Extension(Produ Information On milk Yes.
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
66
provide any
kind of
information
to farmers?
Source quality
feeds
concentrates
and
supplements
routine
training
payment
notification
service
sources of quality
feeds
right
concentrates and
supplements
statement,
rate of
payment
and inputs
deductions
AI
Information
Information
on feeds
on milk
quality.
Pasture/f
odder
management
Record
keeping
Financial
management
Disease &
pests control
Fodder
Establishment
Disease
Control
Insurance
information
Financial
information
ction & Milk
handling
Meeting
notification
Seminars
on quality
AI
Information
on sources
of quality
feeds
concentrat
es and
supplement
s
supply by
farmers
through milk
supply cards
Product
ion and
milk
quality
manage
ment.
22. Services
provided by
the HuB
Collecting milk
marketing
AI services.
Feeds and
concentrates
from our store.
Veterinary, drugs
and
agrochemicals.
Collecting
milk
Milk
marketing
AI services
Feeds and
concentrat
es supply
Supply of
inputs to
farmers on
credit
AI services
Milk advances
Training and
advisory
services
Loans through
Skyline
SACCO
Hardware
credit to
establish zero
grazing units
Hay supply to
farmers
Transport
services
AI services
Hay Provision
Feeds &
Supplements
Financial
services
NHIF,NSSF
Agro vet
services
Credit
facilities to
our active
members
only
Bulking of
milk
marketing
and
transport
services
Clinical & AI
services
Feeds &
Supplements on
credit
Food stuff on
credit
Extension
services
Linkages to
financial access
Mobile Money
Collecting
milk from
farmers
marketing
mainly to
New KCC
Collecting
milk
Marketing
Training of
farmers
Advise on
veterinary
drugs type
and use
Financial
literacy(Acce
ss to loans)
Check
of
payment
for
inputs
and
essential
food
stuffs
from
the farm
shop
23. Activities
undertaken
to improve
on Milk
Productivity
& Milk supply
chain
Hire transport
services
Train farmers
on how to
manage their
herd
Farm and herd
management
skills.
Hire transport
services on
behalf of farmers
Give feed and
supplements on
credit
Train farmers on
how to manage
their herd
Provide ICT
systems
Demonstration
to farmers
Offer
transport
services
Give feed
and
supplement
s on credit
Train
farmers on
how to
manage
their herd
Provide
Promoting of
zero grazing
Value addition
activities
(yoghurt
making)
Investing in a
cooling plant
(chilling Plant).
Educating
farmers during
field days on
quality and
increasing
quantity
Advocating AI
services
use(use of
motorbike for
Training on
importance &
use of AI
Training
farmers on use
and
management of
fodder
Training
farmers on use
and making of
silage
Price
information
Extension
Inputs on credit
Transport
Provision
of AI
services in
collaboratio
n with New
KCC
Extension
services
staff
Milk
transport
services
Farmer
trainings
Milk is
tested at
farm level
for quality
Training of
farmers on
milk hygiene,
handling and
storage/pres
ervation
Training of
farmers on
the types of
feeds that
can help
boost milk
productivity
Collecti
onqualit
y
control
Chilling
Transpo
rt
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
67
outreach)-
Subsidized AI
service
24. Activities
undertaken
to improve
on Milk
quality by
farmers
Hygienic Milk
handling
Train farmers
Using lactometer
to check milk
density.
Use graders who
ensure quality
before collecting
milk
Use of
Lactometer
(density
test and
Alcohol
gun test)
Graders
who
ensure
quality
before
collecting
milk
Practically
training
farmers on
how to ensure
and test milk
quality
Checking of
the quality of
milk by field
clerks at the
collection
centers
By strictly
ensuring that
milk is
collected and
handled in
aluminum cans
Training
farmers on milk
hygiene &
Handling
Providing
farmers with
Mazi milk
handling cans
Encouraging
farmers to
deliver milk on
time
Training of
our staff on
milk
handling and
hygiene
Ensure
quality
before
collecting
milk from
farmers
Milk stored
in cooler
after
receiving
from
farmers
Quality checks
for milk
Use
graders
who ensure
quality
before
collecting
milk
Delivering
of milk to
New KCC
chilling
plant
Test the
milk at
collectio
n
Chilling
milk to
maintain
quality
25. Activities
undertaken
to improve
on Skills of
farmers
Training of our
staff on milk
handling and
hygiene
Extension
trainings
Practically
training
farmers on
how to ensure
and test milk
quality
Educating
farmers during
field days on
quality and
increasing
quantity
Planning &
organizing
farmer field
days
Organizing
seminars for
farmers to
enhance their
skills
Exchange visits
Investing in
extension
service staff to
support
farmers
Training of
farmers on
milk
handling and
hygiene
26. Services/activ
ities
implemented
as a result of
participating
in the MAP
program
Training of staff
on milk handling
and hygiene
Mobilizing
farmers
Management of
Milk bar
preparation of
financial reports
Linking the Hub
with financiers
Internet program
Introduced A.I
providers such as
Training on
milk
handling
and hygiene
Operating
Milk bar
Preparation
of financial
reports
linking the
Hub with
financiers
Record
keeping for
Outreach
and
Collection of
Milk from
more
farmers
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
68
ABS and Pokes. financial
accounting
and feeds
stock
manageme
nt
27. Which
partners have
you worked
with?
Techno serve
Leowa
Associates
Inuka Software
-Brookside
-I procure-
-Kenya
Veterinary
Association
Techno
serve
Sunflower
products,
Twiga
Agricultural
Jubilee
Feeds
Limuru
Feeds Ltd
Mwanza
Feeds
Green
World
Feeds.
Bamscos
Kdff
Kcbf
PKF
Skyline
SACCO
KDFF-ICT
Coopers,
BIMEDA,
County
government
Boda boda
transporters
NEW KCC
AI providers
TNS (KPMG)
Co-op
consultancy
Land O’ Lakes
SNV PKF –
manage
ment
consulta
ncy
Farm
shop –
setting
it up
28. Which
partners did
you work
with to
improve
management
and efficiency
& roles
Leowa
Associates
Inuka Software
-Techno serve
-KAPAP
-I procure-
-KENAFF
USAIDs
Techno
serve
IFCD.
KDFF-ICT
KCBF-Kenya
commercial
bank
foundation-
Inputs
Ministry of
Agriculture
PKF-capacity
building
Bamscos
(Baringo
Farmers
Marketing
Cooperative
Society)-AI
service
provision
Coopers
Norbrook
KDFF
PKF MAK 5
Banks and
Microfinancial
institutions
AI-ABS, Twiga
chemicals,
Coopers,
BIMEDA,Count
y Government
Essential tracks
Ltd,
Pharma Inputs,
Vernah
Machineries,
LEWA
consultancy
on
ICT(SMS)
services
TNS (KPMG)
Land O’ Lakes
Co-op
consultancy
Kenya dairy
board
Techno
serve
County
Sacco
Feed
producers
Hay
farmers
Livestock
officers from
government
Priate AI
service
providers
ASDSP
TNS
(PKF) –
For
restruct
uring of
the
business
29. Impact have
these
activities had
in the dairy
hub
They have led
to increase in
milk
production
There is
increased
supply of milk
we receive
Increase in milk
production
Helped revive
the Cooperative.
Efficiency in
payment to
farmers
Increased supply
Increase in
milk
production
Improved
service
delivery to
farmers
The
cooperative has
established the
use of AI
champions paid
on commission
basis
Training of
The
Cooperative is
now more
focused on the
growth path
The cooperative
has measurable
goals to pursue
They have
led to
increase in
milk
production
Increased
supply of
milk to new
Improved
milk supply
by farmers
Efficient
transpo
rt
system
Quality
feed and
supplem
ents to
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
69
from our
farmers have
also increased
of milk to new
KCC and from
farmers
farmers on the
use and
importance of
AI services
Stocking
varieties of
semens to cater
for farmer
needs
The
Cooperative has
put in place in
market research
plan
Training
programs on
customer
service
KCC and
from
farmers
farmers
on
credit
30. What
changes have
you
experienced
as a result of
these
activities?
There is
increased
supply of milk
we receive
from our
farmers have
also increased
Improvement
on society
management
Adoption of
ICT
Increased
production
Increase of
active
membership
Improved
productivity
Improved
breeds
Improved
incomes(sales)
Improved
Membership
Employment
opportunities(A
gro vet staff, AI
champions)
Increase
d
member
ship
Increase
d milk
collectio
n
Reduce
d costs
of
operati
ons
from
efficient
milk
transpo
rt
system
33.
What
challenges
did you face
while
working with
MAP?
Poor feasibility
study before
implementing
the project
leading to
flopping of
most MAP
projects.
Involvement of
all
stakeholders
before
implementing
any project.
None
None Unsustainabilit
y-The project
is short lived
No challenge,
Feels the
project was
good as it
delivered on its
goals
The
program is
very new
to the Hub
so we
haven’t
experience
d any
challenges
thus far
Lack of
financials to
have an
greater
outreach to
farmers
Poor
transport
network to
transport
milk
The
manager
hasn’t
interact
ed with
TNS
since
march
2015
34. How would
these
challenges be
addressed?
Involvement of
all
stakeholders
before
implementing
any project
Reviving the
engagement
Engaging
More
partners
who are
reliable in
offering AI
None
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
70
More
extension
trainings
services and
sensitizing
farmers on
the
importance
of AI
services
35. Having learnt
from MAP
and its
partners,
have you
worked with
other new
partners
based on this
experience?
Training of
our staff on
milk handling
and hygiene
Mobilizing
farmers
preparation of
financial
reports
linking the
Hub with
financiers
Hay and
forage
department-
project failed.
Herd
management
program for
farmers
Not Yet Not yet Not yet
36. Are you
aware of
other hubs
around that
have
adopted/copi
ed some
activities or
engaged
partners
after learning
from MAP
Muki
Cooperative.
Not aware Had worked
with other
partners before
MAP and also
after MAP
Land O’ Lakes
Tumaini,
Mutugi,
Kirimiri
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
71
6.7 Appendix 5: Characteristics of the Control Group Dairy Hubs
No Result Characteristics
Kabete Olbutyo Umoja Nandarasi Kahuru
1. Total Membership
2012 2,189 441 90 -
2013 2,268 495 110 62
2014 2,311 526 120 124
2015 2,364 692 130 124
2016 2,367 984 756 134 124
2. Total Quantities handled in litres
2012 2,298,248 210,000 108,456
2013 2,510,604 300,000 126,356 48,000
2014 2,766,562 780,000 162,500 72,000
2015 3,685,909 950,000 197,390 78,000
2016 4,001,169 1,050,000 230,300 45,000
3. Total Turnover
2012 2298248 5,460,000 2,711,400
2013 2510604 8,100,000 3,411,612 1,302,000
2014 2766562 22,000,000 4,550,000 2,304,000
2015 3685909 27,550,000 5,921,700 2,496,000
2016 4001169 31,500,000 5,630,000 1,440,000
4. Where is the milk
sold?
Hubs owned by the
Kabete dairy hub
Milk traders
Selling chilled raw milk
processors (KCC)
Brookside
New KCC
Brookside Countryside
and New KCC
processors.
-Milk retail outlets
-Schools
-Hotels
Supply to SAMEER
Agriculture
Brookside chilling plant
Private buyers
5. Do you use ICT
platforms?
Captures data on milk
collected Processing
payments
Accounting, sales, stores
not yet embraced
technology use
Not yet embraced ICT The cooperative still uses
Manual system
No yet embraced technology(ICT)
6. Do you provide any
kind of information to
farmers?
Performance of the dairy
hub, farmer production
and milk quality issues,
prices, new development
in the dairy sector.
Price information
Quality requirements for
Milk
Information on AI
services, Information on
sources of quality feeds,
and the right
concentrates and
supplements for their
dairy cattle, fertilizer,
fodders planting, price
fluctuations, meetings
notification and milk
quality.
About quality AI, sources of
quality feeds, and the right
concentrates and
supplements for their dairy
cattle
Information on AI, Information on
sources of quality feeds, and right
concentrates and supplements for their
dairy cattle
7. Channels of Communication
route meetings, AGMs, Education meetings
Through farmer field days
AGM meetings
Through transporters
Extension officers, field days and radio
announcement
Extension, SMSs and telephone calls
Extension, field days, contact farmers and shows
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
72
No Result Characteristics
Kabete Olbutyo Umoja Nandarasi Kahuru
SMS to farmers
8. How often is the
communication
AGM Once a year
Route meetings –
quarterly
Education meetings –
half yearly
Annually
Quarterly
When need arises
On need basis at least
twice in a month
On need basis When need for communicating to
farmers arises
9. Services provided by
the HuB
AI and clinical services on
check off
Feeds, livestock
supplements, equipment
on check off system
Extension services
Use of milk supplied to
guarantee bank advances
Collecting of milk from
farmers
Marketing of milk for
farmers
AI services
-Supply of feeds and
concentrates
AI services
Feeds and concentrates
AI services
Feeds and concentrates
Financial support through aberdares
Sacco
10. Activities undertaken
to improve on Milk
Productivity & Milk
supply chain
Collection, quality control
– chilling
Transport services
Training of farmers
Ensuring Quality of milk
and chilled storage
Transport services on
behalf of farmers
Supply feeds and
supplements on credit
Train farmers on good
farming practices
Supplying farmers with
quality feeds and
supplements
Trainings
Transport services
Supply feed and supplements on credit
Train farmers on how to manage their
herd, clean milk and animals health.
11. Activities undertaken
to improve on Milk
quality by farmers
Test the milk at collection
chill it to maintain quality
Conducting basic tests
on milk Density test,
Alcohol test during milk
collection
Training (Milk handling)
Use graders to test milk
quality at collection
points (Check is made
for Resasolin, Density
and butter fat contents.)
Graders test quality of milk
before collecting using
lactometer for density
checks and later at
processors plant.
Use of graders who ensure quality before
collecting milk from farmers using
lactometer, Alcohol test and smell.
12. Activities undertaken
to improve on Skills
of farmers
Farmer trainings in
collaboration with
stakeholders(Brookside,
KCC)
Extension trainings to
farmers
Trainings Offering training to farmers by extension
staff
13. Services/activities
implemented as a
result of participating
in the MAP program
Never participated in the
program
Not yet worked with
MAP program
Not yet worked with
MAP program
Not yet worked with MAP
program
Not yet worked with MAP program
14. Which partners have
you worked with?
KCC, Milk traders Brookside, KCC Milk processors,
transporters, Dairy
board, County
Government
Aberdares Sacco Brookside processor
County government
15. Which partners did
you work with to
improve management
and efficiency & roles
None None Milk processors,
transporters, Dairy
board, County
Government
Muki cooperative A.I
service provider and
County's government
Brookside processor
County government
16. Impact have these
activities had in the
dairy hub
17. What changes have
you experienced as a
result of these
None None None None
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
73
No Result Characteristics
Kabete Olbutyo Umoja Nandarasi Kahuru
activities?
18.
What challenges did
you face while
working with MAP?
None None Not yet participated in
MAP program
None None
19. How would these
challenges be
addressed?
Not applicable Not applicable Not applicable Not applicable Not applicable
20. Having learnt from
MAP and its partners,
have you worked with
other new partners
based on this
experience?
Never participated in the
program
Not yet worked with
MAP program
Never participated in
the program
Not yet worked with MAP
program
Never participated in the program
21. Are you aware of
other hubs around
that have
adopted/copied some
activities or engaged
partners after
learning from MAP
Never participated in the
program
Not yet worked with
MAP program
Never participated in
the program
Not yet worked with MAP
program
Never participated in the program
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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6.8 Appendix 6: Characteristics of the Treatment Agro Vet Service Providers
No. Result Characteristics
Limuru Farm Link Siongiroi
1. What type of inputs do you sell in
your agrovet? Services provided by
the agrovet
• Animal feeds &
concentrates
• Supplements
• Chaff cutter
• milk cans
• Seeds
• Food stuffs
Fertilizers
-Seeds
-Animal feeds
-Animal concentrates and
supplements
-Agro chemicals
-Veterinary pharmaceuticals
AI services
-Laboratory
-Animal health
Advisory services on administering of drugs(de wormers) and supplements
Advisory services on Animal nutrition/feeding
Advisory services on importance and use of AI service
Advice on the general animal health(frequency of cow treatment and drug
use)
The Agrovet is newly established and has 2 employees (1 Male employee
and 1 female employee)
The Agro vet is connected to an ICT platform (da power) but has not yet
embraced its use.
2. Total Employees
3. 2012 6(M),7(F)
4. 2013 7(M),8(F)
5. 2014 7(M),8(F)
6. 2015 3 (2Male, 1 Female) 8(M),8(F)
7. 2016 3 (2Male, 1 Female) 8(M),8(F) 2 (1M) (1F)
8. Do you have an ICT platform for sales,
payments and information
management?
Only at the main office
Not yet, but planning to
install soon
Yes, Issuing receipts and
managing stock
9. What impact has the ICT platform
has in your business operation
Efficiency and speed
10. Challenges with the system Network failure
-maintenance cost is high
11. Do you provide any kind of
information to customers?
New products
Production and milk quality
Information about new
products and price changes
The Agro vet provides information to farmers on drug
application/use/dosage
General animal health
12. How/ what channels do you use?
AGM
Extension
Mobile phones and SMS Field days
Printing the message on the receipt of the proceed during delivery
Notice board on the cooperatives compound
The frequency of communication is on demand or when need arises
13. As part of the TNS/KMT initiative,
whom did you partner with (or are
working with) and what were (or are)
their roles?
TNS AGRI-Experience
MAK 5
Twiga Chemicals
BIMEDA
Norbrook
14. Do you use agents’ networks to reach
your customers and market your
products?
you provide
Yes, Has improved the sale and
services over the years
No
15. How did agents’ networks affect your
business performance?
Has improved customer
handling, satisfaction and
increased sales
Increase the flow of business
-Increases overall sales
No
16. Do you integrate customer service Helping customers load Provide information on The agrovets attendants always greets and warmly welcomes customers to
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
75
No. Result Characteristics
Limuru Farm Link Siongiroi
practice in your business operations? If
yes which kind of customer services
practice do you offer to your customers
products bought into their
cars, giving them extra
information, and general
customer courtesy
products and educate them on
the same
the agrovet
They too help customers load items on the motorbike/car
Enganging the customers and explaining to them on the various products
and their usage
17. What impact has the customer service
practice had in your business?
Customer satisfaction has
increased
Increased sales from even
non-members
Increase the flow of business
-Increases overall sales
This practice has made the Agro vet known-publicity
Improved sales
18. What services/activities have you
implemented (or you are currently
implementing) as a result of participating
in the initiative
VAN selling
Selling to smaller Agrovets
through the above method
Established and operating a model Agro vets
Stocking and selling of Hay
Selling of concentrates/supplements in bulk
Introduced and made use of ICT platform
19. In this TNS/KMT program, which
partners did you work (or are working
with) and what were (or are) their roles?
AGRI-Experience-branding and
marketing
EQUITY-loan facility
KDFF-ICT
MAK 5-Branding
Coopers-Input supply
Twiga Chemicals
Norbrook
BIMEDA
ALLURE
20. What changes have you experienced in
your agro vet as a result of these
activities/services
More sales/stocks Improved contacts with the farmers
Improved sales
Variety of stocks
Increased demand of agro vet inputs
21. What impacts have these activities had in
your agro vet?
Increase in number of
customers
Improved sales
More stock varieties
Improved customer service
Increased demand for agro vet products
22. What challenges have you encountered while in
this engagement
Interest rates on loan are high As a result of increased demand for agro vet products, farmers are
demanding inputs/products that are not stocked and when stocked they
never buy them.
The cooperative incurred high cost of establishing the agro vet which was
not in their budget
Delays in the construction work
Unavailability of construction of materials locally
23. Having learnt from the TNS/KMT engagement
and apart from partners introduced/ facilitated
by KMT/TNS, have you gone ahead and sought
to work with partners on your own initiative?
Please explain?
Other Agrovet dealer
-Farmer groups
24. If so, which activities have you implemented
though your own initiative?
Field days
-Association of Agro Dealer
25. Are you aware of other agro vets around
your area that have adopted or
duplicated some activities or engaged
partners/service providers after learning
from what you have implemented
YES-most Agrovets have learnt
from Farmlink
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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6.9 Appendix 7: Characteristics of the Treatment AI Service Providers
No. Result Characteristics
Limuru FarmLink CARITAS Embu Torongo FCS Siongiroi
26. Type of semen do you
mostly supply
AGRICS
WWS
AI total
Friesian
Arshire
Conventional semen (normal)
Sexed semen (genetic semen)
Friesian
Arshire
Semex
ABS
CRU
Viking geneticsics
27. Number of doses sold per
month on average
80-120 60 80 22 75-80
28. Average price per
insemination?
Local Shs. 1000
Exotic Kshs 1500-3000
Sexed Kshs. 7000
Min 1,000
Max 6,000
Kshs 1,000 Local-800
Imported-1500
1000
29. Challenges, faced with
regard to cost and
provision of A.I services
Farmers perceive the prices
to be high
Liquid nitrogen is
expensive
Validity of
semen(breakages,
expired
Competition
Cost variations
Debts from farmers
Some farmers still prefer the
bull due to lack of awareness
Loss of liquid nitrogen through
evaporation
Farmers complain of
high prices
Repeats
Inadequate supply of
liquid Nitrogen
Handling of liquid
Nitrogen
Lack of proper timing
information by farmers
High costs of repeat
cases
30. Changes in insemination
success rate over the last
one year?
Yes. Because if high viability
because of good storage
Yes as a result of farmers
are more aware of the
importance of AI services
60% in 2012 to 70-80% in 2016
mainly due to proper storage
and handling of semen
Dry spell uptake of AI
services has increased
Increased
31. Membership of Livestock
Genetics. Benefits for
membership
No
Not a member Yes. Joined in 2013 No Yes,2014
Exposure and
information about semen
distributors
32. Attendance of mandatory
annual Continuous
Professional Development
(CPD) training by LGSEA
and other industry
associations?
No Gets to know of the new
research findings
Acts as a refresher course
fresher course.
provide free services
around where the meeting
is taking place
Update news of Kenya
veterinary Board
-Continuous professional
development(CPD)
-Organizing Forum to meet and
network with other experts
Yes, on hoof health and
nutrition
Training on linking
farmers with AI
providers
Management of AI
Information by farmers
33. Do you use farmer groups
(Agent Network, AI
Champions, Farmer
Group Leaders) to
promote AI services?
Yes. To pass information to
other farmers
YES-
Mainly to reach the
farmers small Agrovets-eg
jamken, Murimi Mwega
YES-Through training of trainers
(TOT) where a group of about
10 farmers are invited in
CARITAS offices in Embu,
trained on AI technicalities and
trusted to go back to their
villages to train others
No Yes, AI champions,
34. Have the (Agent
Network, AI Champions,
Farmer Group Leaders)
helped improve number
of A.I services you provide
Yes. They recommend and
result to more clients
YES-This has improved AI
provision
YES-CARITAS as an
organization arrange for the
training which a requirement for
the Kenya veterinary Board in
order to renew the practicing
certificate
No Uptake of AI services
has increased
Members using AI
services have increased
Little cases of repeats
are reported
35. What has been the trend
of A.I services that you
2012=960
2013=1800
2012=600
2013=600
2012=500-600
2013=200-250
2012=50
2013=50
2012=240
2013=456
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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No. Result Characteristics
Limuru FarmLink CARITAS Embu Torongo FCS Siongiroi
have been providing to
farmers
2014=1800
2015=1440
2016=1440
2014=650
2015=720
2016=700
2014=200-250
2015=400-500
2016=
2014=60
2015=80
2016=120
2014=636
2015=720
2016=1020
36. Impact of customer
service practice in your
business?
Increased number of clients
due to referrals
Honesty in payment on
service of credits
Customer loyalty
Improved success rates (AI
services)
Enhanced service provision
Increased use of AI service
products
Increased number of
farmers reached
Increased turnovers
Increase in incomes
Increased milk supply
Increased number of
customers
Increase in volumes and
profits
37. When did you start
working with KMT/TNS
or their partners in the
MAP programme?
2015 2013 2012 2014
38. What major challenges
have you had while
working in the MAP
program
None The consistency of the
whole program is lacking
Distance-Trainers have to come
all the way to Embu
Communication costs(printing,
photocopies)
Additional costs which
were not budgeted for
Tight schedule in staff
training
39. Are you aware of A.I
service providers in your
area who have adopted or
duplicated some activities
or engaged partners after
learning from what you
have done in the MAP
program
Not aware There are there especially
those who have learnt
from us as the pioneers of
AI services and Agro vets
YES-about 4 AI providers No
40. Having learnt from the
MAP program and
working with partners
introduced/ facilitated by
KMT/TNS, have you gone
ahead and sought to work
with other market players
on your own initiative
AGRI-Experience
Other service providers eg
Agro vets Farmer groups
YES-We have worked with
other colleagues, farmers and
community at large
FICF-Finance innovation
for climate change fund
Climate smart
agriculture program
Heifer Pacific Project
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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6.10 Appendix 8: Characteristics of the Commercial Hay Providers
Result Characteristics
Hay N Forage Sochon Hay farm Technology farm
1. How many acres of land have you dedicated
to commercial hay production?
1,000 700 400
2. What is the number of times do you harvest
hay per year?
3 2 2
3. What was the production per acre in the
last season? (No. of bales produced?)
70 150 230
4. Who are your major customers for hay?
NYALA Dairy Cooperative Society Individual farmers spread across (Nakuru,
Baringo, Lessos, Kiambu,Machakos,
Kajiado,Kericho and Sotik
Cooperative societies through New KCC-In
Nyeri, Nyahururu & Embu
Farmers spread across areas of
(Kisumu,Kisii, Bomet,Mombasa
Kiambu/Nairobi,Eldoret,Nakuru and
Kericho)
Cooperative societies through New
KCC-In Nyeri, Nyahururu & Embu
5. What is the average weigh of the Hay bales?
(in kgs)
16 kgs 15 Kgs 15 Kgs
6. For how much do you sell hay? (KES)
Ksh.160 per bale Kshs 140 Kshs 195
7. What strategies do you use to ensure hay
produced is quality hay
Adequate fertilizer application
Proper weeding
Timely harvesting.
Early harvesting of hay (Flowering stage)
Ensure no weeds in the hay farm
Fencing the farm to keep away encroaching
livestock (grazing animals) to make sure
hay is free of ticks
Early harvesting of hay (Flowering
stage)30% flowering stage for cows and
40% flowering for seed multiplication
Ensure no weeds in the hay
farm(Weed Control)
Good land preparation-use of fertilizer
during planting and top dressing
8. What types of trainings have you received as
result of MAP in regard to hay production
and how useful were the trainings
Fire fighting
IT System
Techniques on Commercial Hay
production and value addition
Branding of Hay products
Fertilizer application
Record keeping
Data management
Importance of soil analysis and
interpretation
None as the farm was used to train
other Hay producers
9. How have your marketing activities about
hay changed since the engagement with
MAP?
Have increased Customers. Before engaging with the MAP project 80
percent of Hay was marketed through
brokers and only 20 percent by farmers.
Currently the trend has reversed and 80
percent of hay is marked through farmers
and 20 percent brokers
The director has also adopted value
addition of Hay by investing in the machine
to fine process hay and package before
marketing
No change noted in marketing of hay,
Manager argues that maybe it is
because the farm is well established
and the interventions helped only to
create networks with interested hay
farmers and not buyers
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
79
Result Characteristics
Hay N Forage Sochon Hay farm Technology farm
10. We are aware that the demand for quality
hay outweighs the supply, what are your
plans towards satisfying this demand?
Planting more Hay Establish stores at every station near
farmers to address seasonality of hay
supply(Embu, Narok, Kajiado and Nakuru)
Investing in more machinery to ensure
grass harvesting is timely
Addressing the storage of hay
11. As part of the MAP program, which input
providers have you been able to partner
with
John Deere Kenya seeds-Supply of grass seeds
YARA-Supply of fertilizer to the farm
Agri-quest-Soil analysis
None
12. As part of the MAP program, which financial
and equipment service providers have you
been able to partner with
Root Capital- Financial provider
John Deere-Equipment supplier
John Deer
Roots Capital
One source consultants-Business plan
development, financial management
The farm is well established with its
own Machinery and a good network of
input suppliers
13. What changes have you experienced in your
hay farming as a result of participating in the
MAP program?
Increased customers harvesting in time, that is at flowering stage
14. As part of the MAP program, which private
labs for co-branding and quality assurance
have you been able to partner with
Eco-media-for website development and
branding
15. Achieved changes
Increased Hay production
Establishment of out grower program under
the name Rift Valley Hay growers
Increased sales
Hay production has become popular in many
parts of the country unlike before when the
farm was starting
More awareness on the quality and standard by
farmers and consumers of hay as a result of
trainings
16. What challenges towards sustainable
production and commercialization of hay,
fodder do you face?
Drought,
Frost and
Theft
Storage challenges
Poor road networks
Financing of machinery not matching
productivity
Inability to make advance payments to
farmers for the hay supplied
Lack of enough storage facilities
17. What can the program do to reduce these
challenges?
Irrigation of grass, storage of Hay and fencing
of hay farms.
Capacity building in establishing the
association
Linkages of Hay producers with
transporters
Establish storage hubs in different areas
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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6.11 Appendix 9: Characteristics of the BDS Providers
No.
Result Characteristics
Dot Matrix MAC 5 PKF Consumer pro
1. Training modules
offered to dairy
sector
Brand creation
Customer service
Marketing
Advertising
PR
Shop remodeling
Agent network
Merchandising
Customer service
Team building
Financial and procurement
Governance
Investment
Business and strategic plans
HR
Customer service
Stock management
Customer service
Growth and expansion
Village agency
2. Feedback and
Response
mechanism on
customer
satisfaction
Exit mystery
shopper – To
monitor if
implementation is
being done
Random interviews
with shop customers
Post training follow ups
– To monitor if
implementation is being
done
Feedback from
beneficiaries
Track business performance of the client
Constant communication
Through donors e.g. KMT through their evaluations
Through evaluations
Exit interviews – revisiting what wasn’t
well understood
3. Methods of
training preferred
for the future
A combination of
the approaches
Simulation training –
puts participants into
their environments
Participatory approach
Simulation training – puts participants into their environments
Simulation training
4. Targeted changes
expected
Complete overhaul
of the feed shop
Improved sales
Improved customer
service
Shop remodeling
Rural sales strategies
developed
Improved customer
service
Increased membership/activation of dormant members
Better prices for farmers
Improved and efficient business performance
Quality feeds and other inputs
Improved customer service
Functioning feed shop
Increased membership and growing
business
5. Changes that the
BDS thinks
happened
The objective has
been achieved. Shop
sales increased
Better shop display
Good customer
service
Increased sales
Functioning rural
agents network
(cheque book system)
Shop remodeled
Increased member
loyalty
Increased membership and milk collection
Established farm shop
Efficient transport system
Lean organization – efficiently ran organization
Because of delays in starting the project
and internal management problems none
of the changes happened
6. Do you think it is
sustainable?
Yes.
Puts management of
change in the hands of
users/employees
Yes.
An efficiently ran business, offering better prices to members is a
viable business
She was pessimistic
7. Challenges faced
in implementation
of MAP
Delays from the
project
implementers.
Project took over a
year while could
have taken 3 months
Delays from the
project implementers.
Project took
unnecessarily long
period, some gains
were thus eroded or
not reached
The collapse of the partnership between TNS and KMT –
resulted to suspicion which slowed down project implementation
Mistrust at initial stages. Farmers and Hub management viewed
PKF as an audit firm pursuing issues related to taxes. This took
time to fade away
The skills of project implementers at the farm level were a
challenge for both PKF and KMT/TNS. Staff didn’t have proper
skills for lowest level implementation
Some BoD members were resistant to change and preferred
status quo because they benefited form the inefficient system. E.g
some members could not easily agree to reduce meetings as they
Internal management wrangles
The hub was perceived to have very low
capacity to be incorporated in the pilot
The project planning side was not well
organized. There were delays in
implementation of the project
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
81
No.
Result Characteristics
Dot Matrix MAC 5 PKF Consumer pro
were losing the sitting allowances
Some selected hubs had very low capacity thus a lot of effort was
needed to see results
8. Recommendations
for improvement
of the program
Reduce delay in
implementation
proper planning
TNS should have had a
budget for shop
remodeling
TNS should have
increased the budget
for the consultant –
they did more than the
resources could
support
TNS/KMT/PKF should have staff with proper skills and
experience for rural development
TNS KMT should have done a more thorough due diligence so as
to select hubs with considerable good capacity for the pilot
TNS KMT should have done a more
thorough due diligence so as to select hubs
with considerable good capacity for the
pilot
9. From Experience
with MAP has the
BDS sought to
work with other
partners
Had worked with
Agro-dealers before
Shop remodeling
was done in Limuru
for the first time and
turned out to be a
success. The BDS is
pursuing
opportunities to try
and do shop
remodeling with
other clients
Agency model is a new
model that is efficient
and effective.
Working with Agro-
vets in Makueni, Kitui
and Taita
Planning to do shop
remodeling for milk
traders
Yes.
Now working with Hubs in narok and a private dairy firm
Yes.
In talks with Sygenta to implement a
similar idea. But it not yet implemented
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
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6.12 Appendix 10: AAER Model for Supply Chain Intervention
Nature of Intervention
Adopt Adapt Expand Respond
Increase professionalism
in dairy enterprise
management through
improved supplier and
retail management
• 5 dairy cooperatives (Mkulima Bora, Burungu, Tumaini, Rugendo and Gakundu dairies) in Embu County signed a
standard fee and performance based management contract with Sewa.
• 3 management firms (PKF, KPMG and Sewa) continued to develop innovations around management contracting in
order to improve their service offers to businesses. PKF introduced an agribusiness division fully dedicated to
agribusiness while Sewa developed more attractive fees offers (performance/ fixed) for business support. PKF also
works with New KCC, Kenya’s second largest milk processor, to provide services to over one hundred dairy
hubs supplying milk to the processor To date, 14 dairy hubs with 22,82852 registered farmer suppliers have benefitted from these turnaround services that include setting up and
restructuring the businesses to improve performance and growth.
• Three leading marketing firms – Dot Matrix, Consumer Pro and Mac 5 developed and promoted customer focused
marketing and distribution strategies for agrovets, piloted with three DHs (Limuru, Gatundu and Siongiroi).
• United States International University (USIU) has introduced an internship program for student consultants to support
roll out of village agent’s networks, for low cost up-to-date accessible extension services to farmers. USIU has
collaborated with Kenya’s Dairy Board to market its services countrywide. To date, 138 village agents have been recruited
by Agrovet input stores and input suppliers.
• 19 Agrovet input stores have adopted 17 improved retail and distribution practices for feed, breed and vet services
• 4 dairy equipment suppliers (ASHUT, Richie Technologies, ASL and Desley holdings) have developed a six-month
payment plan for acquisition of milk cans by milk traders registered under DTA.
• Upon exit of professional management firms, two (2)
DHs (Gatamaiyu, Limuru), have continued to improve
business operations. For instance, Gatamaiyu dairy has
continued the franchise arrangement with Farm Shop
for provision of inputs to farmers, installed a new
cooler and increased milk intake to 2000 litres per day
and undertaken restructuring to improve service delivery to
members. Limuru dairy on other hand has set up a
members SACCO.
• Limuru, Karate, Njabini and Nyala have continued to
implement the strategic plans they developed with the
assistance of KMAP.
• Limuru also went ahead to
engage Land O Lakes (LOL) to develop a marketing plan
based on the ideas gotten from the strategic plan.
• Prime Cut Ltd, a milk trader in Kisumu County has been
able to independently invest in product differentiation and a brand ‘moo’ targeting low
income earners. This trader has been able to realize
• 1 business, Mbiri Mwivoini Farm, a
private agribusiness
enterprise in Kirinyaga County
specializing in dairy and
horticulture, saw potential in
management services and
independently approached Sewa
and entered into a management
contracting service.
• MAC 5, a marketing firm is planning to do
shop remodeling for milk traders
• PKF has also expanded and is
also offering management
services to other dairy hubs that
are not in the KMAP in Narok
County (Sogoo dairy Co-
operative, Donyo
• 1 enterprise, Centum group of
companies independently
contracted PKF to undertake due
diligence and diagnostic study of
the poultry industry in Kenya to provide
insights into the business and
develop entry strategy
recommendation.
• Lattana Dairy, an SME processor in
Kiambu County currently processing
15,000 litres of fresh milk per day is
in the process of engaging PKF to
support setting up of new aggregation
centers and introduce
innovations leading to sustainable and
improved farmer loyalty and milk
quality. This is one of Lattana’s Dairy’s
expansion strategy
52 Beneficiaries of KMT MAP
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
83
• 1 ICT firm (virtual city developed a platform to host DTAs equipment payment plan through a structured bank
guarantee.
• 1 milk outlet (All Seasons Milk Bar) worked with a brand and
design firm (Renovazone) to redesign the milk outlets to meet the KDB and public health retail certification
requirements.
• I ICT firm, iProcure developed a new ICT based distribution
system for inputs and information. By aggregating demand through village agents who connect farmers to agrovets,
iProcure has been able to lower the cost of inputs and the distance farmers travel to access inputs and information,
thus making the offer attractive and relevant to them. Due to the benefits of the innovation there has been a significant increase in input procurement through the iProcure
platform, which is currently serving 21,893 customers.
• Some of the Treatment DHs had adopted ICT systems to
improve their operations.
• Five dairy enterprises with energy technology companies to
work towards creating energy efficiency solutions.
• KMAP has supported investments in dairy production and processing through debt and equity financing. These include
one dairy processor, Lattana Dairy Ltd., which raised expansion capital by ceding a minority stake to UK based
investors. KMAP also facilitated negotiations between potential equity investors and two dairy enterprises (Lari
and Limuru Processors) looking for equity investments. TechnoServe has also worked with businesses to prepare
them for equity investment.
improved business leading to:
II) increased daily milk intake from 50 litres per day to
2,000 litres per day and ii) business expansion by
opening up new dispensers in different locations in Mosoriot and Eldoret towns
in Uasin Gishu County and iii) setting up a collection center
aggregating milk from 40 small holder dairy farmers.
Lesos Dairy Co-
operative, Nabaya
Cooperative and Nalepo Olepolos
Dairy Cooperative)
and increased
appetite for quality milk.
• Sygenta, an agro-chemical manufacturer is in
talks with ConsumerPro to
provide marketing services to agro-
dealers
Source: Kenya Market Assistance Programme Project Closure Report: Jan 2012 - Mar 2016 and Midline Key Informant
Interviews
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
84
6.13 Appendix 11: AAER Model for Artificial Insemination Services Intervention
Nature of Intervention
Adopt Adapt Expand Respond
Service providers
have improved customer service
skills to build farmer confidence in the AI
service.
• Siongiroi engaged a marketing firm (Mak 5) to
train 6 inseminators in customer service skills. As a
result, the number of inseminations increased by
67% (from 250 to 375 compared to a similar period
last year.
• Njabini, New Ngorika,
Siongiroi and Karate are partnering with suppliers of
genetics to train their AI service providers in
customer.
• Njabini, Nyala, Muki, Tulaga and Karate continued partnering with
genetics suppliers7 to train their AI service providers in customer
service skills.
• One (1) dairy enterprise (Nyala)
has integrated customer service training for AI and animal health
service providers into its business operations.
• Olkalou and Miharati partnered with the county government of
Nyandarua to train 6 AI service providers in customer service
skills.
• By benchmarking with
Siongiroi, 5 DHs in the Rift Valley (Chebusot, Torongo,
Naitiri, Lessos and Cherobu) have adopted several
accreditation components.
• 218 AI service providers from
7 counties invested in customer service training through the
Continuous Professional Development (CPD) training facilitated by LGSEA.
• One genetics supplier (Indicus) is providing
customer service training as technical
assistance to its loyal customers. The
company is also developing a marketing
strategy to drive sales by building customer
service skills in all their accredited service
providers countrywide.
Service providers
invest in promotional and
marketing activities with relevant
market actors
• Siongiroi recruited 28 AI Champions to promote AI
services to farmers
• 8 DHs (Muki, Nyala, Karate,
Kitiri, Tulaga, New Ngorika, Njabini and Siongiroi)
invested in joint promotional and marketing activities in
partnership with Twiga, Bimeda, Pokea, Indicus and
Coopers.
• -Five (5) dairy hubs (Nyala, Muki, Karate, Njabini and Siongiroi
partnered with two (2) processors (Brookside and Kinangop Dairy)
and five (5) genetics supply companies (Bimeda, Pokea, ABS,
Twiga and Semex) for joint AI promotional events
• 4 DHs (Nyala, New Ngorika, Njabini and Siongiroi) have
established long term working relationships with 3 suppliers
(Bimeda, Pokea and Indicus) for promotional and marketing
activities.
• Caritas Embu was facilitated by the county government of
Embu to promote uptake of AI in the major dairy producing
zones of the county.
• Three (3) dairy hubs (Githongo,
Katheri and Buuri) partnered with Meru Central processor
for joint promotional activities to increase adoption of AI.
• The county government of Embu is facilitating
joint marketing events with coffee and Tea
cooperatives.
• New KCC Naivasha
partnering with four (4) DHs (Turasha,
Kinangop, Kirima and Umoja) for promotional
and marketing activities to increase milk
delivery.
Source: Kenya Market Assistance Programme Project Closure Report: Jan 2012 - Mar 2016 and Midline Key Informant Interviews
Mid-Term Evaluation of the Kenya Market Trust Programme –Dairy Sector
85
6.14 Appendix 12: AAER Model for Commercial Hay Production Intervention
Nature of Intervention
Adopt Adapt Expand Respond
Increase smallholder farmer
access to quality and affordable feeds
• Hay N Forage adopted commercial production of
quality hay in 1200 acres of land
• SOCHON Ltd. as an early adopter was able to expand
his acreage from 150 acres to 700acre.
• Afya millers have adopted a new feed formulation strategy which has seen their
sales increase by 25% in the month of June.
• Hay N Forage invested in equipment
for efficiency in the farm, employed staff
and set up a n office
• SOCHON invested in
a business plan, new equipment’s and
developed his brand
• Afya millers have invested in
Agricultural modeling and Training System
(ATMS) software to assist them in feed
formulations
• Due to drought Hay N Forage have
decided to identify another farm where
they can continue with hay farming.
• Through SOCHON initiative Rift valley hay
growers association has been formed with
a membership of 121 members producing
hay on 3300 acres of land.
• Afya millers have expanded its sales from 2 dairies to 13
dairies in three counties.
• Root Capital structured it’s financial packages and was able to loan Hay N forage Ksh 17
million for hay business
• Three financial institutions (Root Capital,
Kenya Commercial Bank and Chase Bank) are providing debt financing to commercial hay
producers. A total of KES 26 Million has been extended to Hay N Forage and Sochon
towards business expansion,
• New KCC has secured an undertaking of KES 800 million (GBP 575,539) from Kenya
Commercial Bank to pay for quality hay supplies.
• New KCC has established a feed platform for all commercial hay growers to supply hay to it’s
over 60,000 farmers.
• Kenya commercial Bank has taken an
undertaking with new KCC to fund dairies to facilitate purchase of hay.
• County governments such as Laikipia and Narok committed funds to support commercial hay production.
Source: Kenya Market Assistance Programme Project Closure Report: Jan 2012 - Mar 2016 and Midline Key Informant Interviews