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Maziwa Zaidi updates. Amos Omore. MilkiT Coordination Meeting 22 Jan 2014, Morogoro, Tanzania. What is ‘ Maziwa Zaidi ’?. Coined to domesticate CGIAR Livestock and Fish ( LaF ) Program in Tanzania - PowerPoint PPT Presentation
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Maziwa Zaidi updates
MilkiT Coordination Meeting
22 Jan 2014, Morogoro, Tanzania
Amos Omore
What is ‘Maziwa Zaidi’? • Coined to domesticate CGIAR Livestock and Fish (LaF)
Program in Tanzania• It’s a dream for pro-poor transformation of the
Tanzania dairy VC over the next decade++ that is not ‘yet’ fully funded
• The impact pathway for Tanzania dairy VC defines how to get there
• Seeks to enrol/get buy-in by non-LaF dairy R&D partners for greater synergy
What is ‘Maziwa Zaidi’? • Individual projects help us to achieve ‘Maziwa Zaidi’
but they are not singly• Other rationle:
– Reduce confusion among stakeholders regarding which projects they are collaborating with,
– Encourage synergy among collaborating projects, – Rally value chain research and development partners towards
a shared purpose.
What is ‘Maziwa Zaidi’? ‘Maziwa Zaidi’ projects so far:
Name Donor PI Theme ObjectiveMilkIT IFAD B Mass Feeds Feeds
innovations/IPsMoreMilkiT Irish Aid A Omore/L.K VCD HubsSFFF2 (ACIAR?) BMZ/GIZ D Grace A4HN Food safety
(nutrition?)Cow Killer BMZ S Alonso /D.
GraceAnimal Health/FS
Disease prev survey
CGP IDRC A Galie / (A. Omore)
Gender/M&E Food security
What is ‘Maziwa Zaidi’? ‘Maziwa Zaidi’ projects proposals/pipeline
Research & piloting partnerships (e.g., MoreMilkiT, MilkiT; SFFF2; new proposals)Maz
iwa
Zaid
i pla
nnin
g
Place of LaF R4D in ‘Maziwa Zaidi’
More milk, income, assets and better health & Nutrition thro’a) access to quality inputs and services b) access to reliable, well-coordinated, marketing arrangementc) access to quality, safe and nutritious products at affordable prices
Scaling out development partnerships (e.g., EADD2? + +)
Time 10 years
Maziwa Zaidi Strategic Research
Scaling out development partnerships (e.g., EADD2)
Highlights of progress of Flagship Project (More MilkiT) and other integrated projects
Objectives (derived from Irish Aid Country Strategy Paper for Tanzania and ASDS)
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, and low-income consumers have better access to affordable milk.
More Milk in Tanzania Project
Contributing Objectives over 5 yrs1. Develop scalable value chains approaches with improved
organization and institutions serving resource-poor male and female smallholder dairy households
2. Generate and communicate evidence on business and organizational options for increasing participation of resource-poor male and female households in dairy value chains
3. Inform policy on appropriate role for pro-poor smallholder-based informal sector value chains in dairy sector development
More Milk in Tanzania Project
Addressing 4 inter-related problems that face resource-poor milk producers
1. Dominant direct sales of small volumes by smallholder producers that preclude economies of scale
2. Credit facilities for basic inputs and services or working capital are lacking. This discourages investment to improve productivity
3. Lack of appropriate organizational models for pre-commercial producers (complex cooperative models and technology-driven solutions have largely failed)
4. Seasonality of rainfall and related effects are strong (with MilkIT)
Milk marketing outlets (NBS, 2003)
Milk Buyer%
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
More Milk in Tanzania Project
Addressing 4 inter-related problems that face resource-poor milk producers
1. Dominant direct sales of small volumes by smallholder producers that preclude economies of scale
2. Credit facilities for basic inputs and services or working capital are lacking. This discourages investment to improve productivity
3. Lack of appropriate organizational models for pre-commercial producers (complex cooperative models and technology-driven solutions have largely failed)
4. Seasonality of rainfall and related effects are strong (with MilkIT)
More Milk in Tanzania Project
Women participate more in milk related tasks
Addressing 4 inter-related problems that face resource-poor milk producers
More Milk in Tanzania Project
Milk processing in Tanzania has been declining since 1990
1. Dominant direct sales of small volumes by smallholder producers that preclude economies of scale
2. Credit facilities for basic inputs and services or working capital are lacking. This discourages investment to improve productivity
3. Lack of appropriate organizational models for pre-commercial producers (complex cooperative models and technology-driven solutions have largely failed)
4. Seasonality of rainfall and related effects are strong (with MilkIT)
Addressing 4 inter-related problems that face resource-poor milk producers
1. Dominant direct sales of small volumes by smallholder producers that preclude economies of scale
2. Credit facilities for basic inputs and services or working capital are lacking. This discourages investment to improve productivity
3. Lack of appropriate organizational models for pre-commercial producers (complex cooperative models and technology-driven solutions have largely failed)
4. Seasonality of rainfall and related effects are strong (with MilkIT)
More Milk in Tanzania Project
Milk processing installation 1995-2000. (Total approx. 315,000 l/day)
Processor name Installed capacity (litres/day)
1 Azam Dairy 3,0002 Tommy Dairy (Hakifanyikazi) 15,0003 Tan Dairies 15,0004 Tanga Fresh Ltd 40,0005 Ammy Brothers Ltd 2,0006 Brookside (T) Ltd (Hakifanyikazi) 45,0007 International Dairy Products 5,0008 Mountain Green Dairy 1,5009 Arusha Dairy Company 5,000
10 Kijimo Dairy Cooperative 1,00011 Longido (Engiteng) 50012 LITI Tengeru 50013 Terrat (Engiteng) 50014 Orkesumet (Engiteng) 50015 Naberera (Engiteng) 1,00016 Nronga Women 3,50017 West Kilimamnjaro 1,00018 Mboreni Women 1,00019 Marukeni 1,00020 Ng'uni Women 1,00021 Kalali Women 1,00022 Same (Engiteng) 50023 Fukeni Mini Dairies 3,00024 Kondiki Small Scale Dairy 1,200
25 Musoma Dairy 40,00026 Utegi Plant (Ex TDL ) (Hakifanyikazi) 45,00027 Makilagi SSDU 1,50028 Baraki Sisters 3,00029 Mara Milk 15,00030 Mwanza Mini Dairy 3,00031 Kagera Milk (KADEFA) 3,00032 Kyaka Milk Plant 1,00033 Del Food 1,00034 Bukoba Market Milk Bar 50035 Bukoba Milk Bar - Soko Kuu 50036 Mutungi Milk Bar 80037 Salari Milk Bar 80038 Kashai Milk Bar 80039 Kikulula Milk Processing Plant 1,00040 Kayanga Milk Processing Plant 1,00041 MUVIWANYA 1,00042 SUA 3,00043 Shambani Graduates 400044 New Tabora Dairies 16,00045 ASAS Dairy 12,00046 CEFA Njombe Milk Factory 10,00047 Mbeya Maziwa 1,00048 Vwawa Dairy Cooperative Society 90049 Gondi Foods 600
Less than 5000 litres/day
5000-30,000 litres/day
More than 40,000 litres/day
Key
26
12
16
6
7
8
12
9
4
5
10
3
11131415
17
18
19
20
2122
23
24
42
45
25272829
3031
32
3233
34 35 3637 38 39
4041
43
4647
48
49
46
D.R.C
Pemba
Unguja
LINDI
RUKWA
TABORA
IRINGAMBEYA
RUVUMA
SINGIDA
MOROGORO
KIGOMA
PWANI
ARUSHA
DODOMA
SHINYANGA
TANGA
MARA
KAGERA
MANYARA
MTWARA
MWANZA
MANYARA
KILIMANJARO
DAR ES SALAAM
I N D I A N O C E A N
KENYA
UGANDA
RWANDA
BURUNDI
ZAMBIA
MOZAMBIQUE
Milk processing installation 1995-2000. (Total approx. 315,000 l/day)
Processor name Installed capacity (litres/day)
1 Azam Dairy 3,0002 Tommy Dairy (Hakifanyikazi) 15,0003 Tan Dairies 15,0004 Tanga Fresh Ltd 40,0005 Ammy Brothers Ltd 2,0006 Brookside (T) Ltd (Hakifanyikazi) 45,0007 International Dairy Products 5,0008 Mountain Green Dairy 1,5009 Arusha Dairy Company 5,000
10 Kijimo Dairy Cooperative 1,00011 Longido (Engiteng) 50012 LITI Tengeru 50013 Terrat (Engiteng) 50014 Orkesumet (Engiteng) 50015 Naberera (Engiteng) 1,00016 Nronga Women 3,50017 West Kilimamnjaro 1,00018 Mboreni Women 1,00019 Marukeni 1,00020 Ng'uni Women 1,00021 Kalali Women 1,00022 Same (Engiteng) 50023 Fukeni Mini Dairies 3,00024 Kondiki Small Scale Dairy 1,200
25 Musoma Dairy 40,00026 Utegi Plant (Ex TDL ) (Hakifanyikazi) 45,00027 Makilagi SSDU 1,50028 Baraki Sisters 3,00029 Mara Milk 15,00030 Mwanza Mini Dairy 3,00031 Kagera Milk (KADEFA) 3,00032 Kyaka Milk Plant 1,00033 Del Food 1,00034 Bukoba Market Milk Bar 50035 Bukoba Milk Bar - Soko Kuu 50036 Mutungi Milk Bar 80037 Salari Milk Bar 80038 Kashai Milk Bar 80039 Kikulula Milk Processing Plant 1,00040 Kayanga Milk Processing Plant 1,00041 MUVIWANYA 1,00042 SUA 3,00043 Shambani Graduates 400044 New Tabora Dairies 16,00045 ASAS Dairy 12,00046 CEFA Njombe Milk Factory 10,00047 Mbeya Maziwa 1,00048 Vwawa Dairy Cooperative Society 90049 Gondi Foods 600
Less than 5000 litres/day
5000-30,000 litres/day
More than 40,000 litres/day
Key
26
12
16
6
7
8
12
9
4
5
10
3
11131415
17
18
19
20
2122
23
24
42
45
25272829
3031
32
3233
34 35 3637 38 39
4041
43
4647
48
49
46
Less than 5000 litres/day
5000-30,000 litres/day
More than 40,000 litres/day
KeyLess than 5000 litres/day
5000-30,000 litres/day
More than 40,000 litres/day
Less than 5000 litres/dayLess than 5000 litres/day
5000-30,000 litres/day5000-30,000 litres/day
More than 40,000 litres/dayMore than 40,000 litres/day
Key
26
12
16
6
7
8
12
9
4
5
10
3
11131415
17
18
19
20
2122
23
24
42
45
25272829
3031
32
3233
34 35 3637 38 39
4041
43
4647
48
49
46
26
12
16
6
7
8
12
9
4
5
10
3
11131415
17
18
19
20
2122
23
24
42
45
25272829
3031
32
3233
34 35 3637 38 39
4041
43
4647
48
49
46
D.R.C
Pemba
Unguja
LINDI
RUKWA
TABORA
IRINGAMBEYA
RUVUMA
SINGIDA
MOROGORO
KIGOMA
PWANI
ARUSHA
DODOMA
SHINYANGA
TANGA
MARA
KAGERA
MANYARA
MTWARA
MWANZA
MANYARA
KILIMANJARO
DAR ES SALAAM
I N D I A N O C E A N
KENYA
UGANDA
RWANDA
BURUNDI
ZAMBIA
MOZAMBIQUE
D.R.C
Pemba
Unguja
LINDI
RUKWA
TABORA
IRINGAMBEYA
RUVUMA
SINGIDA
MOROGORO
KIGOMA
PWANI
ARUSHA
DODOMA
SHINYANGA
TANGA
MARA
KAGERA
MANYARA
MTWARA
MWANZA
MANYARA
KILIMANJARO
DAR ES SALAAM
I N D I A N O C E A N
KENYA
UGANDA
RWANDA
BURUNDI
ZAMBIA
MOZAMBIQUE
Addressing 4 inter-related problems that face resource-poor milk producers
1. Dominant direct sales of small volumes by smallholder producers that preclude economies of scale
2. Credit facilities for basic inputs and services or working capital are lacking. This discourages investment to improve productivity
3. Lack of appropriate organizational models for pre-commercial producers (complex cooperative models and technology-driven solutions have largely failed)
4. Seasonality of rainfall and related effects are strong (with MilkIT)
More Milk in Tanzania Project
Farmer groups are struggling in most places except in Tanga
Performance of milk collection at Nnronga women dairy co-operative Society, Hai
Kilimanjaro and CHAWAMU-Muheza Tanga (1994-2007)
050000
100000150000200000250000300000350000400000450000500000550000600000650000700000750000
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Year
Volu
me
of M
ilk (L
itres
)
Nnronga
CHAWAMU-Muheza
More Milk in Tanzania Project
Key messages on identified 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
• 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 in ensuring wider impact on marginalised
• Policy support for pro-poor shift needed
Identified field sites
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.
Hubs for piloting in the Tanzania context
Producers In
puts, $$
Inputs & services
$$
Payment agreement
Milk, C
attle
Check-off agreement
Inputs & Service Providers(BDS)
Traders Milk
Cattle
BASIC Dairy Market Hubfor Provision of Inputs and
Services on Check-off
Illustration of a hub for provision of inputs and services on credit without collective bulking and marketing
Milk Trader
Training Service Providers
(BDS)
Regulatory Authority
Certific
ation/Lice
nsing
Training & certification of
competence
Accreditation & monitoring
Reporting
Cess f
ee
Training guides
BDS linkages in milk quality assurance in informal markets (with TDB)
Hygieniccans
Fee
(Trialled in Kenya, Uganda and Tanzania (Arusha & Mwanza)
It is evolving and continuing to catalyze policy dialogue for a pro-poor transformation of the dairy value chain…
DDF update:
MoreMilkiT update:
• R&D partnerships formed for piloting have started to mobilize value chain actors for piloting of interventions
Range of partnerships :1. Strategic Research Partnerships
• SUA• TALIRI
Reinforced by CGIAR (ILRI/CIAT) and ARIs partnerships
2. Development Partnerships• Servicing the system: Heifer and SNV• From the system: TDB, FAIDA MaLi
3. Mechanisms for strengthening relationships
• DDF• Local platforms
MoreMilkiT update:
DMH category Criteria for becoming a DMH
a): Collective bulking and sale of milk by members of a farmers group
Farmers group i) is registered at district level
ii) has at least 1 link with a milk trader/ buyer and at least 1 link with an input & services provider
iii) members are able to access inputs & services on check off system
b) and c): Individual members of a farmers group sell milk and/or cattle directly to traders
Farmers group
i) is registered at district level ii) members are able to access inputs & services on check off
system
Criteria for becoming a dairy market hub defined
Hub for provision of inputs and services on credit without collective bulking and marketing
Impact pathway and MLE developed
• Monitoring, learning and evaluation (MLE) framework) developed
• Several targeted research activities and ex-ante assessment of interventions initiated, some through students
Baseline (benchmark) results available
• Most findings re-affirm VCA findings, with figures
• It’s mostly about feed, less so other constraints!
1. Dominant direct sales of small volumes by smallholder producers that preclude economies of scale
2. Credit facilities for basic inputs and services or working capital are lacking. This discourages investment to improve productivity
3. Lack of appropriate organizational models for pre-commercial producers (complex cooperative models and technology-driven solutions have largely failed)
4. Seasonality of rainfall and related effects are strong (with MilkIT ++)
MoreMilkiT: Main Successes and challenges
Successes • Entry points for piloting of interventions identified, the project
is now ready for take-off• Early success in preparing for impact in the dairy value chain in
Tanzania in the long-term through DDF and ‘Maziwa Zaidi’ value chain transformation agenda
Challenges• Lengthy bureaucracies in reaching agreements with partners• Delays in recruiting additional staff • Innovating for inclusive upgrading of dairy value chains is
riskier but has more potential for wider impact
CGIAR is a global partnership that unites organizations engaged in research for a food secure future. The CGIAR Research Program on Livestock and Fish aims to increase the productivity of small-scale livestock and fish systems in sustainable ways, making meat, milk and fish more available and affordable across the developing world.
CGIAR Research Program on Livestock and Fish
livestockfish.cgiar.org
In support of: