Presented by A. Omore, L. Kurwijila and S. Nandonde at the Tanzania Society of Animal Production (TSAP) Conference, Arusha, 23-26 October 2012

1. More Milk in Tanzania
Entry points for extending the frontiers of dairy value
chains in Tanzania through hubs
Presentation at TSAP Conference
A. Omore, L. Kurwijila and S. Nandonde
35th Tanzania Society of Animal Production (TSAP) Conference,
Arusha, 23-26 October 2012

2. BACKGROUND:
Projections indicate demand to 2020 outstrips supply
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 in the medium
term (ASARECA/IFPRI report)

3. Milk yield per Lactation (Kg)
BACKGROUND: Large Yield Gaps
6000
5000
x3
4000
x3
3000
x3
2000
y2
1000
0
y1
x3
x2
x2
x1
x1
Indigenous Crossbred
Exotic Indigenous
Mixed rain fed
temperate/highlan
d
Crossbreds
Mixed rain fed
humid/sub-humid
Synthetics
Exotics
Large-scale
commercial ranches
Xi = Yield gaps due to “animal husbandry practices” : 33 - 76 %
Yi = Gap in productivity due to “genotype”: 18 - 74%
Source: Mwacharo et al., 2009

4. CONTEXT
CGIAR Research Program on:
More milk, meat and fish by and for the poor (LaF)
is one of 15 CRPs in a re-organized CGIAR system
Goal:
To sustainably increase the productivity of
small-scale livestock and fish systems to increase
the availability and affordability of animal-source
foods for poor consumers and,
in doing so, reduce poverty through greater
participation by the poor along the whole value
chains for animal-source foods.

5. Approach: Solution-driven R4D to achieve impact
Addressing the whole value chain to transform the sector over a decade
R4D integrated to transform selected value chains
In targeted commodities and countries.
Inputs & Services
Production
Processing
Marketing
Consumers
Major intervention with development partners
Value chain development team + research partners
Strategic LaF Cross-cutting Platforms
• Technology Generation
• Market Innovation
• Targeting & Impact
INTERVENTIONS TO
SCALE OUT REGIONALLY
GLOBAL RESEARCH
PUBLIC GOODS

6. LaF: Prepare intervention
Working toward interventions
for impact at scale
Time
Performance Target:
double production in
x poor households
Scaling out
Development Partners
$90m
Knowledge Partners $10m
LaF: Strategic Research $10m
10 years

7. Delivering Livestock + Fish Programme
Structure: Three integrated Components
3 Targeting: Foresight, prioritization, gender, impact
2 Value chain development
1 Technology
development:
− Genetics
− Feeds
− Health
Consumers
Commodity X in Country Y
Cross-cutting: M&E, communications, capacity building

8. 9 Target Value Chains
SHEEP & GOATS
AQUACULTURE
PIGS
DAIRY
Website for news updates on subscription: http://livestockfish.cgiar.org/

9. LaF Catalyst Role
NARS
ARIs
Investors
Research
Private
Sector
NGOs
LaF
CG partners
Ministry
Investors
Development
Website for news updates on subscription: http://livestockfish.cgiar.org/

10. Links to other CGIAR Programs (CRPs)

11. Current and anticipated CGIAR linked
dairy VC projects in Tanzania in 2012
1.
2.
3.
4.
5.
6.
MilkIT: Promoting feed innovations ILRI/CIAT/TALIRI/SUA; IFAD
MoreMilkIT: Adapting dairy market hubs: ILRI/SUA/TDB; Irish Aid
Safe Food Fair Food (SFFF2); - ILRI/SUA; BMZ
Livestock Data Innovation (LDIP) – MLDF/FAO/ILRI; BMGF/WB funded
Integrated Crops and Goat project (CGP) – SUA/UA/ILRI; IDRC
EADD – HPI/TNS/ILRI/ICRAF/ABS; BMGF
7.
Equitable access to animal source foods - ILRI/WFC/SUA - AUSAid

12. Main challenge for solution driven research
for development :
• How can research be more responsive?
• How can research deliver value beyond
knowledge?
• How can research serve development in
real time?

13. Entry points for More Milk in
Tanzania Project: Key considerations
• Strong focus on pro-poor marginalised precommercial men and women and ‘growing’ inputs
and outputs markets that serve them
• Explore new organizational models to achieve
economies of scale
• Aim is to provide proof-of-concept on how
marginalised groups can also be targeted
successfully
• Generate evidence for influencing policy
Following are highlights of dairy VC R4D engagement
and findings on entry points since Jan 2012

14. More Milk in Tanzania Project
Objectives
(derived from ASDS and Irish Aid Country Strategy Paper for Tanzania)
Goal: Inclusive growth and reduced poverty and
vulnerability among dairy-dependent livelihoods in
relevant rural areas in Tanzania
Outcome: Rural poor are more income secure through
enhanced access to demand-led dairy market business
services and viable organisational options
Contributing objectives:
– Develop scalable value chains approaches
– Generate and communicate evidence on business and
organizational options
– Inform policy on appropriate role for pro-poor smallholderbased value chains

15. More Milk in Tanzania Project
Addressing 5 inter-related problems
that face resource-poor milk producers
1. Dominant direct milk sales of
small volumes. This precludes
economies of scale  ↑costs
2. Credit facilities are lacking.
This contributes to low access
to basic inputs and services or
working capital to purchase
them
3. Lack of appropriate
organizational models for
pre-commercial producers.
These are required to
facilitate collective action
4. Seasonality of rainfall and
related effects are strong
Milk marketing outlets
Milk Buyer
(NBS, 2003)
%
Neighbours
86.1
Local market
5.5
Secondary market
0.5
Processors
1.4
Large scale farms
0.2
Trader at farm
4.5
Other
1.7
TOTAL
100.0

16. More Milk in Tanzania Project
Addressing 5 inter-related problems
that face resource-poor milk producers
1. Dominant direct milk sales of
small volumes. This precludes
economies of scale  ↑costs
2. Credit facilities are lacking.
This contributes to low access
to basic inputs and services or
working capital to purchase
them
3. Lack of appropriate
organizational models for
pre-commercial producers.
These are required to
facilitate collective action
4. Seasonality of rainfall and
related effects are strong
Women participate more where there’s
no collective milk bulking and marketing

17. More Milk in Tanzania Project
Addressing 5 inter-related problems
that face resource-poor milk producers
1. Dominant direct milk sales of
small volumes. This precludes
economies of scale  ↑costs
2. Credit facilities are lacking.
This contributes to low access
to basic inputs and services or
working capital to purchase
them
3. Lack of appropriate
organizational models for
pre-commercial producers.
These are required to
facilitate collective action
4. Seasonality of rainfall and
related effects are strong

18. More Milk in Tanzania Project
Addressing 5 inter-related problems
that face resource-poor milk producers
1. Dominant direct milk sales of
small volumes. This precludes
economies of scale  ↑costs
2. Credit facilities are lacking.
This contributes to low access
to basic inputs and services or
working capital to purchase
them
3. Lack of appropriate
organizational models for
pre-commercial producers.
These are required to
facilitate collective action
4. Seasonality of rainfall and
related effects are strong
Milk processing in Tanzania has been declining since 1990

19. More Milk in Tanzania Project
Addressing 5 inter-related problems
that face resource-poor milk producers
1. Dominant direct milk sales of
small volumes. This precludes
economies of scale  ↑costs
2. Credit facilities are lacking.
This contributes to low access
to basic inputs and services or
working capital to purchase
them
3. Lack of appropriate
organizational models for
pre-commercial producers.
These are required to
facilitate collective action
4. Seasonality of rainfall and
related effects are strong

20. More Milk in Tanzania Project
Huge seasonal fluctuation in milk
supply from traditional herd
Volume of milk (litres/month)
Milk collection by a small scale processor from traditional herd in
Morogoro, 2009
13000
12500
12000
11500
11000
10500
10000
9500
9000
8500
8000
7500
7000
6500
6000
5500
5000
4500
4000
3500
3000
2500
2000
1500
1000
500
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Month
Average/month
Aug
Total supply
Sep
Oct
Nov
Dec

21. More Milk in Tanzania Project
Huge seasonality in milk supply from the
indigenous vs. improved dairy cattle
02/02/2014
NAI/EGM/Mara Region/Kurwijila
21

22. More Milk in Tanzania Project
Less rainfall variation in highlands
30
25
20
15
Lowland/extensive
10
Highland/semiintensive
5
0

23. More Milk in Tanzania Project
Less seasonal milk yield fluctuation with
better feeding
16,000.00
14,000.00
12,000.00
10,000.00
8,000.00
6,000.00
4,000.00
2,000.00
-
Source: SUA dairy research farm)
2009
2010
Average

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

25. Entry Points:
More Milk in Tanzania Project
Spatially overlays was the initial step….
+
Prod systems: arid to
humid/temperate
=
Map A: Mixed prod sys + ↑pop
Persons/sq km (25)
+
=
R-U
R-R
Map A
Market access (0.5& 5hrs)
Maps B & C : Mixed prod sys + ↑pop +
↓ & ↑ market access: = R-R & R-U

26. R-R
Maps B : Mixed prod sys + ↑pop + ↓ market access: = R-R

27. R-U
Maps C : Mixed prod sys + ↑pop + ↑ market access: = R-U

28. More Milk in Tanzania Project
Identified entry points in the field
Maps + stakeholder consultations
Region
District
Market access Cattle
classification
population*
% improved Dominant production
dairy breeds system
Kilosa
R-to-R
215,100
1
Extensive/Agropastoral (zebu)
Mvomero
R-to-U
187,350
5
Extensive/Agropastoral (zebu) with
significant
semiintensive & intensive
(improved)
Handeni
R-to-R
126,780
1
Extensive/Agropastoral
&
Extensive/Sedentary
(all zebu)
Lushoto
R-to-U
119,492
24
Extensive/Sedentary
(zebu) with significant
semi-intensive
&
intensive (improved)
Morogoro
Tanga
Detailed value chain assessments have been conducted at these sites

29. More Milk in Tanzania Project
Morogoro: Kilosa and Mvomero

30. More Milk in Tanzania Project
Tanga: Lushoto and Handeni

31. More Milk in Tanzania Project
Which Hub Model might be appropriate?
Hubs are localized groups of smallholder producers with common interests in accessing
inputs (feed, breeding, animal health) and services (training, credit, insurance), as a means
to achieve a critical mass of supply
Diversified Profit-Max Model for CPs
Some EADD
Hub Models
being tested
-
-
Collection
Center
Chilling Plant
Processing Plant
Sales to Processor
-
-
-
-
Sales to
individuals and
vendors
Diversified profit max through:
higher prices for milk sold locally
lower costs (transport, chilling) overall for milk handled

32. More Milk in Tanzania Project
Outcome Mapping identified the following
hubs for piloting in the Tanzania context
Dairy Market Hubs (DMHs) with emphasis on
improving access to inputs and services through
business development services (BDS) and check-off
arrangements:
a) DMHs revolving around chilling plants or accessing
them (if under-utilized) through transport arrangements
that provide both outputs marketing and inputs and
services through check-offs;
b) DMHs revolving around check-offs for inputs and
services provided through milk traders; and
c) DMHs revolving around check-offs for inputs and
services provided through cattle traders.

33. Illustration of a hub for provision of inputs and services
on credit without collective bulking and marketing
Producers
BASIC Dairy Market
Hub
for Provision of Inputs and
Services on Check-off
Traders
Milk
Cattle
$$
Payment agreement
Inputs &
Service
Providers
Targeting 50 villages with 8000 cattle keepers across 4 districts

34. Design of integrated R4D to extend the frontiers of dairy
value chains to achieve wider impact in Tanzania
Addressing the whole value chain with downstream emphasis
Consumers
Intervention with development partner
Value chain development team + research partners
Strategic Cross-cutting Platforms
• Technology Generation (Feed, genetics, health
• Market Innovation
• Targeting & Impact (includes gender)
Cross-cutting: M&E, communications, capacity building
INTERVENTIONS TO
SCALE OUT NATIONALLY
Baseline for
M&E
planned for
Dec 2012

35. Integrating other actors into the Tanzania dairy
value chain R4D
SUA
/TALIRI
Irish
institutions
Other
Investors
(e.g., IFAD
BMZ)
Research
Private
Sector
Dev
Partner
NGO
ILRI /
Other CG
partners
MLDF
TDB, other
NGOs (DDF)
Investors
(e.g., BMGF)
Development

36. Organogram of DDF and stakeholder
linkages
Dairy Development Forum
Secretariat: Tanzania Dairy Board
Advisory Committee
Govt
Membership
Academic &
res institutions organisations
Dairy development
organisations
Stakeholder organisations
Civil
society
Private
sector

37. More Milk in Tanzania Project
Key messages on entry points
• Validity of the need to focus attention on ‘growing’
the existing informal system of milk production (with
zebu cattle) and marketing to extend the frontiers of
commercial dairying
• New organizational models to achieve economies of
scale for access to inputs and services required to
unleash incentives for raised productivity to levels
that will justify bulking
• This is riskier than classical approaches but more
inclusive and promises wider impact on marginalised
• Policy support for pro-poor shift needed