Update on dairy value chain development
in Tanzania
Amos Omore (ILRI)
CGIAR Research Program on Livestock and Fish
Planning Meeting
ILRI Nairobi
28 September 2011

Outline
• Value chain overview - highlights updated from
proposal;
• Previous engagements;
• Status of existing engagement and key strategic
partners;
• Overview of outcome pathways;
• Synthesis of existing and planned activities/
resources from sub-components (iterative);
• Analysis of gaps;
• Priorities for resource mobilization

Good growth and market opportunity
• Many people (43m; 37% poor) and cattle (19m): 3rd largest
cattle pop in Africa after Eth and Sudan
• Improved cattle only 0.6m (3%) but growing fast (6%)
• Milk supply about 1.6b litres/yr (56% consumed on farm)
• Milk consumption rising sharply: from 28 to 39 litres per
capita over the last decade (Country-stats)
• Nascent formal milk sector (approx 80,000l/d; <5% of
marketed milk from local production)
• Growth patterns could follow Kenya’s (longer history of
investment but similar prod – consumption systems)
• Private sector growth/collective action has been unable to
fill gap after withdrawal of public support

Projections in milk supply & demand to 2020
3,000
2,500
2,000
Million Lts
Milk/ Yr
1,500
1,000
2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Year
3% GDP Growth 2% GDP Growth Milk Production
Dairying in EA is the most important ag sector commodity for GDP gains
(ASARECA/IFPRI report)

Where are the cattle?
Cattle pop. Density/km2
Lindi 0.1
M twara 1.37
Ruvuma 1.48
M orogoro 1.61
Kigoma 3.5
P wani 3.99 <5
Rukwa 6 >5-10
Tanga 11.54
M beya 14.01
Dar es
Salaam 14.72
Dodoma 19.55
Iringa 21.13
Kagera 23.52
Tabora 23.86 >10-25
Singida 36.69
Arusha 41.75
Kilimanjaro 45.34 >25-50
M ara 65.72
Shinyanga 75.19 >50-100
M wanza 111.62 >100

Where are the improved dairy cattle?
Improved dairy cattle /100km 2
Lindi 2
Rukwa 2
Kigoma 2
Singida 2
Tabora 2
Mtwara 5
Morogoro 7
Dodoma 11
Shinyanga 22
Ruvuma 24
Manyara 30
Iringa 31
Pwani 33
Mwanza 40
Mara 45
Kagera 60
Mbeya 68
Tanga 103
Arusha 158
Zanzibar 203
Dar es Salaam 591
Kilimanjaro 1036

Where are the milk processing units?
32 29 28 27 26 25 15 14 13
UGANDA
11
30
31 RWANDA KENYA 12
32 MARA 10 6
KAGERA
9 24
33
16 19
34 35 36
BURUNDI
MWANZA ARUSHA
17 20
37 38 SHINYANGA
KILIMANJARO 8
39 MANYARA
18
40 7 23 21
KIGOMA
MANYARA Pemba
41 22
L a
46 TANGA 5
I NDIAN
I NDIAN
I NDIAN
TABORA
k e
SINGIDA
25 Musoma Dairy 40,000
4
T a n
26 Utegi Plant (Ex TDL ) (Hakifanyikazi) 45,000 DODOMA
27 Makilagi SSDU 1,500 Unguja Processor name Installed
28 Baraki Sisters 3,000 capacity
29 Mara Milk 15,000
49
g
g
g
a (litres/day)
OCEAN
OCEAN
OCEAN
30 Mwanza Mini Dairy 3,000
D.R.C n
31 Kagera Milk (KADEFA) 3,000 1 Azam Dairy 3,000
32 Kyaka Milk Plant 1,000 DAR ES SALAAM 2 Tommy Dairy (Hakifanyikazi) 15,000
y iii
33 Del Food 1,000 3 Tan Dairies
34 Bukoba Market Milk Bar RUKWA 15,000
500
k
MOROGORO PWANI 4 Tanga Fresh Ltd 40,000
35 Bukoba Milk Bar - Soko Kuu 500
5 Ammy Brothers Ltd 2,000
1
a
36 Mutungi Milk Bar 800
37 Salari Milk Bar
38 Kashai Milk Bar
800
800 45 6 Brookside (T) Ltd (Hakifanyikazi)
7 International Dairy Products
45,000
5,000
39 Kikulula Milk Processing Plant
40 Kayanga Milk Processing Plant
1,000
1,000
MBEYA
2 8 Mountain Green Dairy
9 Arusha Dairy Company
1,500
5,000
41 MUVIWANYA 1,000 IRINGA 10 Kijimo Dairy Cooperative 1,000
42 SUA
43 Shambani Graduates
44 New Tabora Dairies
3,000
4000
16,000
47 46 3
11 Longido (Engiteng)
12 LITI Tengeru
500
500
45 ASAS Dairy 12,000 13 Terrat (Engiteng) 500
46 CEFA Njombe Milk Factory 10,000 14 Orkesumet (Engiteng) 500
47 Mbeya Maziwa 1,000
48 Vwawa Dairy Cooperative Society
49 Gondi Foods
900
600
ZAMBIA 48 LINDI 42 15 Naberera (Engiteng)
16 Nronga Women
17 West Kilimamnjaro
1,000
3,500
1,000
La
43 18 Mboreni Women 1,000
k
k
k
k
ke
19 Marukeni 1,000
Key 20 Ng'uni Women
N y as a
1,000
y as
y as
y as
y as
21 Kalali Women 1,000
22 Same (Engiteng) 500
Less than 5000 litres/day RUVUMA MTWARA 23 Fukeni Mini Dairies 3,000
24 Kondiki Small Scale Dairy 1,200
5000-30,000 litres/day
More than 40,000 litres/day
MOZAMBIQUE
Milk processing installation 1995-2000. (Total approx. 315,000 l/day)

Farmer groups are struggling!
Performance of milk collection at Nnronga w omen dairy co-operative Society, Hai
Kilimanjaro and CHAWAMU-Muheza Tanga (1994-2007)
750000
700000
650000
600000
Volume of Milk (Litres)
550000
500000
450000
400000 Nnronga
350000 CHAWAMU-Muheza
300000
250000
200000
150000
100000
50000
0
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Year 2007

Low milk processing capacity utilization
Region Average Average
No. of Total Installed plant capacity per capacity
S/N Plants capacity* plant Milk processed/day
utilisation
1 Dar es Salaam 3 33,000 11,000 8000 24.2
2 Tanga 2 42,000 21,000 30500 72.6
3 Arusha 6 58,000 9,667 6500 11.2
4 Manyara 3 2,000 667 1100 55.0
5 Kilimanjaro 9 13,200 1,467 4580 34.7
6 Mara 5 104,500 20,900 39100 37.4
7 Mwanza 1 3,000 3,000 1000 33.3
8 Kagera 11 11,400 1,036 3450 30.3
9 Morogoro 2 7,000 3,500 950 13.6
10 Tabora 1 16,000 16,000 200 1.3
11 Iringa 2 22,000 11,000 8700 39.5
12 Mbeya 2 1,900 950 1100 57.9
13 Dodoma 1 600 600 200 33.3
Total 48 314,600 6,554 105380 33.5
Note Plant capacity defined on single 8 hr shift.
Source: Tanzania Dairy Board/ MLDF Records

Researchable supply constraints
• Large productivity gaps by genotype (Mwacharo et al.,)
• Breed choices/breeding services delivery:
European, Mpwapwa, Sahiwal, Gir?
• Feed: seasonality & quality
• Health: e.g., important but unclear epid picture: benefits
from ITM use /other AH techns
• Interventions to grow formal milk market sector given
low processing capacity utilisation (<25%) and reduce
imports of processed milk
• The role of farmer groups in facilitating access to input
supply and milk marketing is very small
• Main challenge for R&D: Value chain upgrading
/expansion options that can be taken up by dev partners

Value Chain Outcomes (proposal list)
Components Value chain outcomes
Inputs & Increased private sector /farmer group participation in inputs and services
Services provision.
Improved feed quality and increased quantity of feed (forage and concentrates)
Increased access to affordable animal health care
Production Reduced seasonality in milk supply
Increased milk off-take from existing herds in extensive areas
Increased feed options available
New more adaptable breeds introduced and accessible (e.g .,Gir cattle)
Reduced yield gap for cows with under-exploited genetic potential
Reduced disease risk and mortality, especially ECF
Transport & Increased volume and proportion of processed milk
Processing Increased number of small-scale milk traders selling more milk
Reduced transport and transaction costs
Marketing Increased number of farmer groups engaged in milk marketing
Reduced transactions costs
Participating milk businesses enjoying price premiums from improved milk quality
Higher milk volumes sold to more and profitable outlets
More women participating in larger milk businesses and farmer organisations

Activities & partnerships
• Past
– 1998: SDC funded dairy sector appraisal (with SUA & Min of Livestock)
– 2000: DFID funded research to improve informal milk markets while
addressing milk-borne health risks (with SUA, ILRI RR# 19)
• Ongoing/approved
– ASARECA-PAAP funded pilot to scale out BDS schemes in Mwanza and
Arusha /integrate informal into formal VC (with TDB)
– ASARECA-LFP – Milk Marketing and value addition (quality and safety)
– BMGF funded livestock data collection methods project
– MiLKIT (recent scoping visit; stakeholder meeting with CRP3.7 soon)
– CIAT recently initiated steps to build expertise on tropical forage research
• Proposed (with probable ILRI involvement)
– EADD 2, Irish Aid (with SUA), EPINAV(Norway, SUA), EAAPP (WB/IDA loan
with ASARECA convening role)
• Other key players/potential partners
– TAMPA/TAMPRODA, ACT, LoL, HPI, MLDF Res Centres (e.g., Mpwapwa),
FAO/UNDP ag value chains projects, AGRA’s “breadbaskets” partnerships

Objectives of new proposals
MiLKIT (IFAD): Enhancing livelihoods through feed innovation and
value chain development approaches (1.0m 3yrs)
• Institutional strengthening: To strengthen use of VC and innovation
approaches among dairy stakeholders to improve feeding strategies.
• Productivity enhancement: To dev options for improved feeding
• Knowledge sharing: To strengthen knowledge sharing mechanisms on
feed development strategies at local, regional and international levels
IrishAid: Getting milk to market: res. on dairy hubs in Tanzania (0.5m/yr)
• Generate and communicate evidence on business and organisational
options for milk marketing in marginalised Tanzanian dairy
households, and for associated service providers
• Identify mechanisms for establishing micro and small enterprises, or
appropriate links to the commercial sector for provision of inputs and
services
• Develop scalable dairy value chain interventions from pilots (TM bubs)

Impact pathways and outcomes
Sub- Pathway Outcome
component
2.1 Sectoral CRP3.7 works with partners to Consensus achieved among
& Policy conduct analyses and generate national and regional policymakers
Analysis evidence and engage with regarding pro-poor policies and
policymakers and stakeholders to investment strategies to support
understand the whether and how the development of the 9 target value
target value chain should be ‘enabled chains
2.2 Value CRP3.7 works with R&D partners to Improved and increased public &
Chain conduct field studies to identify private sector interventions being
Assessment opportunities, test best-bet strategies applied by development actors to
and generate evidence to inform and support women and resource-
stimulate development interventions poor value chain actors and
for pro-poor upgrading of the target consumers, with lower ecological
value chains footprint per unit produce
2.3 Value CRP3.7 works with partners to identify Enhanced pro-poor value chain
Chain and test the principles and methods performance and more equitable
Innovation that permit research to promote and distribution of benefits.
replicate effective and sustained pro-
poor change in value chains

2.2 Value Chain Assessment
Proposed Priority Outcomes & Outputs
2012 2013 2014
Outcomes R&D alliance 1. capacity to use tools Evidence base
2. Stakeholders aware influencing decisions
Research 1. Scoping study to characterize 1. Inventory and evidence base 1. Best-bet intervention
Outputs target VC and identify (literature review) for key strategy formulated and
stakeholders and potential constraints and proposed tested, ready for piloting
partners solutions compiled
2. Basic toolkit for VC assessment 2. Quantitative assessment of
compiled for testing VC performance
3. Analytical framework for 3. Technical and economic
assessing VC performance assessments of key VC
established components to target for
4. Rapid assessment of target VC upgrading (e.g. farm-level:
to inform design of in-depth husbandry, feeds, breeds,
assessment, and to identify health, environmental issues;
preliminary priority constraints market-level: institutional
and best-bet upgrading strategies environment, food safety,
to test (including specific demand characteristics;
components on environmental overall: policies, organizational
impacts, food safety risk strategies
assessment and gender analysis)

2.2 Value Chain Assessment
Implications for Tanzania in 2012 (Focus on 2.2)
Outcome: CRP3.7, local and international partners have established
an R&D alliance to transform Dairy VC in Tanzania
Priority Research outputs for 2012 Implications for Tanzania
/potential delivery mechanisms
1. Scoping study to characterize dairy VC and identify •Build of rich knowledge available
stakeholders and potential partners •Initial scoping in early 2012 –
2. Basic toolkit for VC assessment compiled for testing linked to MiLKIT start-up
3. Analytical framework for assessing VC performance •EADD CE
established •Irish Aid?
4. Rapid assessment of VC to inform design of in- •ASARECA-PAAP BDS networks
depth assessment, and to identify preliminary priority study
constraints and best-bet upgrading strategies to test •ASARECA milk marketing and
(incl. specific components on environmental impacts, value addition study (with
food safety risk assessment and gender analysis) demand data)
5. Candidate intervention strategies for piloting •Livestock Data Innovation
Linkages with sub-components (AH, Feed, Genetics Joint assessments of constraints /
etc) Candidate technologies: ITM, ????

2.2 Value Chain Assessment
Implications for Tanzania in 2012
Priority Organisational, Capacity Development and
Communication Activities
Activity Implications for
Tanzania/comments
1. Restructure team to match CRP needs, with 1. Irish Aid would be happier to
shared vision and assignments for subject/VC focus fund a country based office
2. Identify gaps for priority recruitment or 2.Lesson from EADD is that in-
partnership country presence is critical
3. Identify strategy and mechanisms for working
links internally with other CRP3.7 components, and
externally with CRP2, CRP4
4. Develop a communication strategy targeted to
stakeholders and partners in each target VC

2.2 Value Chain Assessment
Implications for Tanzania in 2012
Priority Resource Mobilisation Activities
Activity Implications for
Tanzania/comments
1. Individual or multiple-country projects to 1. VC assessment beyond
identify and test best-bet upgrading strategies for MiLKIT? Gap could be filled
each target VC (perhaps more manageable if done through EADD CE/EADD 2
separately at farm and market levels) 2. Targeted trialling of ITM?
2. Project to design and test analytical framework 3. Research to adapt
for assessing and monitoring VC performance Traditional milk hubs
(both as basis for M&E and as analytical tool) (without chilling plants)
(under CRP2??)
3. Field studies to develop assessment methods for
prioritizing animal health and public health (with
CRP4.3) priorities for pro-poor VC development
Create linkages with sub-components (AH, Feed, Joint assessments of constraints
Genetics, CRP2, 4 etc)

2.2 Value Chain Assessment
Implications for Tanzania in 2013
Outcome 1. Partners have capacity /tools for VC assessment
Outcome 2. Stakeholders are increasingly aware of potential,
constraints and initial options for pro-poor development of target VC
Priority Research outputs for 2013 Implications for Tanzania
/potential delivery mechanisms
1. Inventory and evidence base (literature review) MiLKIT - mainly feed/farm-level in
for key constraints and proposed solutions target locations
compiled
2. Quantitative assessment of VC performance EADD2
3. Technical and economic assessments of key VC
components to target for upgrading (e.g. farm- Irish Aid?
level: husbandry, feeds, breeds, health,
environmental issues; market-level: institutional EAAPP has adopted ILRI developed
environment, food safety, demand characteristics; tools for baseline surveys; may
overall: policies, organizational strategies seek ILRI’s collaboration in
targeted studies
Linkages with sub-components (AH, Feed, Joint assessments of constraints /
Genetics) Candidate techns: ITM, others??

2.2 Value Chain Assessment
Implications for Tanzania in 2014 (optional for now)
Outcome 1. Evidence base in each target VC for best-bet pro-poor
VC dev interventions is influencing dev investment decisions
Priority Research outputs for 2014 Implications for Tanzania
/potential delivery mechanisms
1. Best-bet intervention strategy (better refined) MiLKIT
formulated and tested, ready for piloting
EADD2
Irish Aid?
New project development?
Linkages with sub-components (AH, Feed, Joint assessments of constraints /
Genetics) Candidate techns??

2.2 Value Chain Assessment
2012 Priorities for
Organisational, Capacity Development and
Communication Activities
 Create a country VC team to match CRP needs (CIAT already has
an office (Selian Agric Res Inst in Arusha); ILRI office?
 Initiate engagements under MiLKIT,
 Pursue new proposals under EADD SUA led
projects, EAAPP, Others
 Identify gaps for priority recruitment or partnerships across sub-
component and other CRP’s
 Develop a communication strategy targeted to stakeholders and
partners (with 2.3)