DAIRY INDUSTRY IN TANZANIA Value Chain Analysis

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Contents Summary and Introduction Industry Overview Market Overview Value Chain Assessment 1

Executive summary Purpose of VCA Overview of Dairy Industry Main Challenges Ultimate aim is to encourage interventions that will increase the competitiveness and long-term performance of Tanzania s dairy sector with particular attention to increased benefits for poor VC participants including smallholder dairy producers and local service providers Cattle serve as a critical source of livelihood for a large portion of rural Tanzanians, especially in the Northern and Coast regions of the country Tanzania s cattle population is 21.0M (2008), more than 97% is indigenous, which contributes ~70% of total milk production The livestock sector contributes 16.3% of the agricultural GDP and 4% of the national GDP. Dairy contributes approximately 1.2% of GDP Since 2005, dairy production has grown on an average of ~4% per annum Production: lack of solid input provider and capital support; lack of production education; far distance between farm and milk collection center / processor; seasonal price and production fluctuation Milk Collection Centers / Processors: supply of milk; access to capital; irregular power supply; poor equipment; low demand for processed products (processors only); high operating costs / taxes (processors only) Retailers: lack of cold chain; supply constraints; low demand for milk Traders: necessary evil in the supply chain; quality and hygiene concerns Consumption: affordability; incorrect beliefs; small school feeding campaign Enabling Environment: TDB and TAMPA in nascent stage; local government support dependent on region 2

Contents Summary and Introduction Industry Overview Market Overview Value Chain Assessment 3

Tanzania s dairy industry has changed significantly over time 1921 Colonial govt starts dairying in Tanzania with establishment of Temeke Dairy Farm, ~5km from Dar By 1960 Colonial govt withdraws completely from dairy industry Pre-independence (-1961) 1965 1973 National Dairy Board (NDB) under dairy industry law 1975 Dairy Farming companies established to produce milk for urban consumers and breeding stock for smallholder farmers Nationalization (1961-1985) Mid-1980 s Economic liberalization led to privatization of all seven TDL processors 1988 Milk prices de-regulated Privatization (1985-Present) 1952 1961 Dairy Industry Ordinance of 1961 established Zonal Dairy Boards Dar es Salaam municipality establishes and has a system for registering dairy farms 1961-1965 Early 1980 s Tanzania Dairies Limited (TDL) formed to process milk from large farms; failed due to poor mgmt Private commercial farms Processors managed by Zonal Dairy Boards Farmers had 25-40% owned shares Early 1990 s 2004 Dairy Industry Act catalyzed formation TDB and Annual Council Major thrust on smallholder dairy dev. projects (Iringa/Mbeya from Swiss, Kagera/Tanga from Dutch) Source: EADD workshop; FAO Dairy Dev Institutions in East Africa, 2011 4

Livestock significant part of Tanzanian economy, with dairy roughly 30% of livestock value GDP by Economic Activity Livestock in the Economy Trillions Tsh, current prices $30 $25 $21B $25B $28B Dairy Livestock Agriculture, remaining 3-5% of total GDP, growing at rate ~7% per year (2007-2009), ~9% slower than GDP $20 $15 $10 $5 $0 $18B $16B $14B 2004 2005 2006 2007 2008 2009 GDP, remaining Contributes to the livelihood of 2+ million households and over 100,000 intermediaries 21M cattle 15M goats 6M sheep Tanzania has the 3 rd largest herd of cattle in Africa after Ethiopia and Sudan Source; Ministry of Livestock and Fisheries, Tanzania Milk Processors Association, National Bureau of Statistics 5

Dairy production has been growing at 4% per year, with the traditional sector responsible for 70% of production Cattle Milk Production Dairy in the Economy Billion of Liters; cow milk 2.0B 1.8B 1.5B 1.3B 1.4B 1.4B 1.4B CAGR: 4% 1.5B 1.6B 1.6B Improved Traditional sector (mainly produced by indigenous cattle) are responsible for 70% of production 1.0B 0.8B 0.5B 0.3B Indigenous Less than 5% of production is formally marketed, as 70-80% is consumed or lost at farm level and 15-25% passes through informal markets 0 2005 2006 2007 2008 2009 2010 Note: Improved cattle consist of Friesian, Jersey, Ayrshire breeds and their crosses to the East African Zebu. Indigenous cattle are raised as dual purpose animals for milk and meat production, Source: Ministry of Livestock and Fisheries, RLDC Dairy Sub Sector Development Strategy 6

Increase in production is mostly explained by growth in cattle population; yield stagnating in recent years Dairy Cattle Population and Yield Total size of cattle population vs. yield per cow 20.0M 18.0M 16.0M 14.0M 12.0M 10.0M 8.0M 6.0M 4.0M 2.0M 0 17.5M 14.1M 12.9M 162 175 174 1980's 1990's 2000's 500 kg/cow 450 kg/cow 400 kg/cow 350 kg/cow 300 kg/cow 250 kg/cow 200 kg/cow 150 kg/cow 100 kg/cow 50 kg/cow kg/cow CAGR (1995-2005)* Population 3.5% Yield 0.0% Production ~4%* Yield stagnation due to variety of factors, including Lack of farmer education on production Poor nutrition Disease Weak extension services Potential untapped opportunity in increasing yield Note: *Middle years taken due to averages in data points Source: ILRI, FAO 7

Over 1.3M households benefit through dairy production, with 55%+ in Northern and Lake areas Dairy Producing Households Number of households, Millions Households by Region Households rearing cattle by region, 2007 1.4M 1.2M 1.0M 0.1M Southern Highlands Region 19% Central Region Eastern Region 16% 7% 1% Southern Region 0.8M 0.6M 1.1M 1.3M Northern Region 25% 32% Lake Region 0.4M 0.2M 0.0M HH with indigenous cattle HH with dairy cattle Total Majority of cattle-owning households concentrated in Northern and Lake areas, with over 55%+ Source: Ministry of Finance and Economic Affairs Household Budget Survey 2007 8

Opportunity to increase productivity through improved breeds, as currently comprises only <1% of national herd ~70% of Tanzania cattle concentrated in Lake, Northern, and Central regions but improved dairy herds congregate in the North, East, and S. Highlands Total cattle size by region (2008) 9.0M Total exotic dairy cattle herd size by region (2008) 300K 8.0M 7.0M 6.0M 5.0M 4.0M 3.0M 8.1M ~20M+ total cattle in Tanzania 250K 200K 150K 100K 253 ~500t+ improved cattle in Tanzania 2.0M 1.0M 0.0M 3.9M 2.8M 2.3M 2.2M 1.7M 0.1M 50K 0K 104 103 35 7 5 5 Notes: Lake includes Mwanza, Shinyanga, Mara, Kagera; Southern Highlands includes Rukwa, Mbeya, Iringa, Ruvuma; Central includes Singida and Dodoma; Northern includes Arusha, Manyara, and Kilimanjaro; Eastern includes Tanga, Morogoro, Coast, and Dar; Southern includes Lindi and Mtwara; Western includes Tabora and Lindi Source: Ministry of Agriculture, Food and Cooperatives 9

Estimated 34% Tanzanians under poverty line, with possibility to move farmers through dairy interventions Annual Farmer Income Thousands, TZS for every 28 days (2007 data) 100% 80% 60% 66% 100% Although Tanzania has achieved growth rates of 6-7% over the past 10 years, this has not lifted millions out of poverty because growth has occurred in [noninclusive] sectors like mining, tourism most of the population (80%) depend on agriculture for their livelihoods and have been left out. Lusato R. Kurwijila Professor at Sokoine University of Agriculture 40% 20% 0% 17% Below food poverty line 17% Below basic needs poverty line Above poverty line Total TZ population Commercial (Smallholder) dairy production has high potential for poverty alleviation in rural areas due to regular income and employment generation it is therefore highly supported by the government of Tanzania as a tool in the national poverty reduction strategy. Tanzania Dairy Board Notes: Food poverty line at 10,219 Tsh/28 days; basic needs poverty line at 13,998Tsh/28 days Source: Household Budget Survey 2007, National Bureau of Statistics 10

WIP: Checking if we have data for milk production yield for dairy cattle available (per CWG comments) Tanzania generally average on milk production, cattle population, and yield compared to region Milk Production Cattle Population 5B 4B 3B 2B 1B 0 Cow, fresh milk, (liters/year) 4.2B 2.9B 1.6B 1.2B 0.4B Tanzania Kenya Ethiopia Uganda Rwanda 60M 50M 40M 30M 20M 10M 0 # of cows 50.9M 21.0M 17.5M 12.1M 1.3M Tanzania Kenya Ethiopia Uganda Rwanda Milk Production Yield Indigenous Cattle Population 6 5 4 3 2 1 0 Liters per cow per day 4.90 2.00 1.69 1.75 1.20 Tanzania Kenya Ethiopia Uganda Rwanda 120% 100% 80% 60% 40% 20% 0% 98% 99% 94% 81% 77% Tanzania Kenya Ethiopia Uganda Rwanda Years: Uganda 2010; Tanzania 2008; Ethiopia 2009/2010; Rwanda 2010 milk and cattle and 2008 indigenous cattle population; Kenya 2009 Source: World Bank Uganda Dairy Supply Chain Risk Assessment, 2011; Uganda Bureau of Statistics 2011; Ethiopia Central Statistics Agency 2010; Rwanda MINAGRI FY10-11 Annual Report; Rwanda Dairy Master Plan 2009; RARDA 2009; Tanzania Ministry of Livestock and Fisheries; Kenya Dairy Master Plan 2010; Kenya 2009 Census 11

Government recognizes importance of agricultural sector and has invested in industry, but dairy has not been a priority Dairy policy has improved slightly to facilitate industry growth Annual milk weeks established in pilot project (2001) Annual milk week established VAT exemption on machines and equipments used in the collection, transportation, and processing of milk Stakeholders felt that the industry lacked direction, because the government did not have clear cut rules and directives. Land O Lakes, 2007 Agricultural Sector Budget Allocations Financial year budgets, TZS 1,000B 750B 500B 250B 0 Represents ~8% of total annual budget, still short of the 10% proposed under Kilimo Kwanza initiative. 370.0B 450.0B 667.0B 904.0B 2007/08 2008/09 2009/10 2010/11 Key Government Programs Agricultural Sector Development Program Began in 2005-6, national program Estimated 750B TZS budget cost Program objective is higher level agricultural growth and poverty reduction Sub goal of promoting agricultural private investment based on an improved regulatory and policy environment Local level support through District Agricultural Development Plans (DADPs); 75% of budget Kilimo Kwanza (Agriculture First) Designed in 2009, supported by The World Bank Goal to transform agriculture sector into modern, commercial one through investments SAGCOT (Southern Agricultural Growth Corridor of Tanzania) Initiated at the World Economic Form (WEF) Africa Summit in 2010 Public-private partnership with participants like Unilever, Government of Tanzania, USAID, AGRA Tanzania is, in essence, an agricultural country therefore, agriculture holds a unique position with respect to the socioeconomic wellbeing of Tanzania and her people. Jakaya Mrisho Kikwete, President of Tanzania Source: MAFSC budget speeches 2007 to 2010, Budget books for 2007/08 2010/11 12

Contents Summary and Introduction Industry Overview Market Overview Value Chain Assessment 13

Milk reaches consumers through many disparate channels, the most significant being the informal market Non-marketed milk On-farm human consumption Calf consumption / Wastage Farmer Transporter Marketed milk Milk Collection Center Trader Processor Non-retail Retail Retail Outlet Non-Retail Consumer / raw milk Consumer / processed milk Total INFORMAL MARKET (~90%) FORMAL MARKET (~10%) Source: TechnoServe field research; Ministry of Livestock and Fisheries; Rural Livelihood Development Company 14

Demand growth outpacing local production by ~2% annually, but supply shortage still present; sizeable imports and limited locally marketed/processed milk Annual Dairy Consumption (L) 2008 annual dairy production & imports per capita (L) 1,800M 1680.6K 1497.6K 16.6K 16.6K 149.8K 1,200M Product Breakdown 2011 Retail Sales Value Based on 14 Days Yoghurt Ice Cream Other 600M M Cultured Milk 16% 30% 8% 7% 7% 31% 2000-2010 annual dairy consumption per capita (L) UHT Fresh Pasteurized Fresh Very low consumption of dairy products outside of milk Most processed milk consumed only in urban areas Source: TNS Tanzania Dairy Survey Report, 2011; Ministry of Finance and Economic Affairs 15

East Africa per capita consumption is well below the WHO recommended consumption per year Yearly Consumption Per Capita 200 150 100 50 0 Litres per year WHO Recommendation 111 50 43 40 19 Tanzania Kenya Uganda Rwanda Ethiopia East Africa per capita consumption has increased but remains far below WHO recommendation Kenya, however, much higher than the region Ethiopia has the lowest consumption in East Africa, with a 200 day fasting period for 44% of population Years: Uganda 2009; Rwanda 2011; Tanzania 2010; Kenya 2009; Ethiopia 2007 Source: World Bank Uganda Dairy Supply Chain Risk Assessment, 2011; Ethiopia Central Statistics Agency 2010; FAO 2007; Rwanda Dairy Master Plan 2009; Tanzania Ministry of Livestock and Fisheries; Kenya Dairy Master Plan 2009 16

Seasonality creates severe fluctuation in production, affecting supply further down the value chain Seasonal variation in production Thousands of milked cows, 2007-2008 800 Wet season 600 Dry season 400 200 0 Shinyanga Arusha Tanga Morogoro Iringa Avg number of days cows milked, 2007-2008 Wet season 200 Dry season 150 100 50 0 Shinyanga Arusha Tanga Morogoro Iringa Seasonal Drivers Availability of key inputs like grass and water fluctuate with seasons Most interviewed farmers do not plan ahead for seasons, like storing water or grass Effect on Value Chain Processor supply can drop up to 50% in dry season due to lack of milk Prices fluctuate throughout the year E.g., In Rukwa, avg price in wet season 297 TZS skyrockets to 575 TZS in dry season Consumption decreases in dry season due to lack of availability and increased prices Source: 2007/08 Agriculture Sample Census: Preliminary Report 17

Tanzania government figures suggest demand growth forecasted to outpace local supply growth, with a ~50% gap by 2020 Annual domestic dairy demand and supply (liters, B) 5.0 4.0 MLFD national demand CAGR + 7.75% (2011-2020) 3.0 FAO suggests lower per capita consumption, but the metric seems low when compared to production and import figures Tanzanian local supply CAGR + 3.57% (2011-2020) 2.0 1.0 FAO national demand CAGR + 4.13% (2011-2020) 0.0 Notes: MLFD national demand based on current 43 liters/capita; FAO national demand based on 2007 figure of 23.1 liters/capita; Tanzanian local supply calculated by growing published historical data from 2005-2010; Population growth factored into equation, based on historicals Source: World Bank, FAO, Ministry of Livestock and Fisheries 18

Quality of processed and raw milk is low, however most people boil before consumption mitigating most risks ~35% of milk samples in Tanzania found to have antibody residue Observed practices/factors that pose threat to public health Adulteration Source: ILRI Research Report 19, 2009; TechnoServe field research, 2012 - Notably widespread in Mwanza Use of plastic containers or sub-standard metal containers - Plastic milk containers used by ~83% of sampled market agents in Tanzania; plastic containers difficult to sterilize Low use of milk preservation methods - ~75% of sampled market agents did not take measures to preserve milk before resale Low levels of training - Only 5% of milk market agents interviewed received any training in milk handling and quality control - Training usually only lasted ~1 month Recommendations for increasing milk quality in Tanzania Adulteration - Training and public intervention Use of plastic containers or sub-standard metal containers - Increase use of hygenic metal containers through education and tax cuts Low use of milk preservation methods - Most common method in Tanzania is through refrigeration; education on benefits of boiling Low levels of training - Community development centres may be ideal for institutionalizing simple training programmes 19

Tanzania is a net importer: imports from Europe, other East African countries, and South Africa prevalent Shortage in supply drives increase in imports Majority of imports come from Europe and South Africa Dairy imports and exports $m USD (2010) European imports [Tanzania] animal and dairy products do not qualify for export for health and quality reasons. - Dept. Agriculture, S. Africa ~0.0M Milk powder and butter are key imports from the European Union Domestic dairy products cannot compete in external markets partly because they are not rendered longlasting before they perish. - Minister of Livestock & Fisheries South African imports UHT, milk powder, and cheese are most typical products Source: Business Times, Tanzania; Ministry of Livestock and Fisheries; Rural Livelihood Development Company Dairy Sub Sector Development Strategy, 2009 Middle East imports UAE is major source of UHT Oman a key source of butter Kenyan imports UHT milk and butter are most typical products New Zealand imports New Zealand is a key supplier of cheese 20

Ability to address deficits in milk consumption by opportunities in Northern and Lake regions of Tanzania, though in part due to low consumption rate Figure 4: Average bovine milk production in Tanzania Figure 5: Average bovine milk consumption in Tanzania Figure 5: Surplus/Deficit of milk in Tanzania Source: ILRI, CIAT 21

Contents Summary and Introduction Industry Overview Market Overview Value Chain Assessment 22

Exclusively Formal Main activities and industry structure for Tanzanian dairy value chain Activities Industry structure Retailer Sale to individuals and institutions May involve delivery Fixed shops: kiosks, canteens, shopping centers, and large supermarkets Trader Informal sector: from producer to retailers or consumers Transporting, delivery Mobile structure: large number of traders selling milk door to door or in town centers Unregulated sector, with lack of equipment Processor Pasteurization and production of dairy products Processing, packaging, quality testing Consist mainly of small and medium size plants with capacities of 500 to 50,000 liters per day Current national processing capacity is ~400,000 liters Largest processors: Tanga Fresh, Asas, Musoma Dairies, Mara Milk, Tan Dairies Bulk and Chill Local aggregation of dairy products Additional activities may include: Cooling Quality testing A number of bulking centers across Tanzania Few chilling plants, not all operational Few cooperatives present in Tanzania Transporter Formal sector: transportation from producer to processor, from processor to retailer Small number of milk transport businesses, as many processors/mccs are vertically integrated into this value chain segment Producer Milk production on farm Milking cattle, caring for animals and breeding Growing fodder and feeding animals Estimated ~1.8M livestock owners, ~1.3M cattle owners Most farmers pastoralists who apply zero grazing method 23

Stakeholder value addition and margins differ based on formal vs. informal value chain participation ILLUSTRATIVE Informal value chain Value creation for 1 liter of raw milk, estimated, 2012* Formal value chain Value creation for 1 liter of processed fresh milk, estimated, 2012* TZS 1,200 TZS 1,000 Note: this only portrays one of many routes to market TZS 1,200 TZS 1,000 Profit / Value Add Costs TZS 800 TZS 800 TZS 600 TZS 600 TZS 400 TZS 200 Profit / Value Add Costs TZS 400 TZS 200 Note: this only portrays one of many routes to market TZS 0 TZS 0 Note: *Estimate following key informant interviews, 2012. Large variation exist across the country. Source: TechnoServe field research, 2012 24

Majority of Tanzania dairy industry resides in raw milk channel, usually from farmer to trader or direct consumer Consumer / raw milk Consumer / processed milk Markets Kiosks Regional market Local supermarket, shop, restaurant Regional market, shop, restaurant Distribution Processing Trader Processor Medium Scale Processor Medium Scale Processor Chilling/ Bulking Co-operative Production Smallholder Farmers Medium Commercial Farmers Large Commercial Farmers Imported milk powder RAW MILK PROCESSED LONG LIFE MILK CHANNEL 1 Farmer Consumer CHANNEL 2 Milk Centre, Raw CHANNEL 3 Milk Centre, Processed CHANNEL 4 Medium Scale CHANNEL 5 Large Scale Producers CHANNEL 6 Imported milk powder

Consumers can access milk and milk products from most points of the value chain Producer Typically sell fresh milk, may also sell other dairy products Informal, trust-based contract; payment right away; delivery typically not included Individual Consumers Traders Shops and Kiosks Restaurants, Hotels, etc Sell milk at open markets or door-to-door No contract, but consumers will return and buy from traders they trust Kiosks and canteens typically sell fresh milk, at times processed milk; supermarkets sell both No contract, typically based on most convenient location Dairy products are consumed on location, depending on occasion Dairy products are purchased for household consumption Consumers generally buy milk from the same location consistently based on convenience and price When income allows, milk is purchased daily in a planned manner, particularly if children or the eldery are present Other dairy products are typically bought unplanned, for the holidays or produced at home from surplus milk 26

Most consumers recognize health benefits of milk, but strong preference for local raw milk prevalent Perceptions About Milk Milk Processed milk isn t really milk they add so many chemicals and take away all the fats so it doesn t taste good. Plus, I think it s only for rich, foreign people. Rural consumer, Tanga Region Milk is really only for children. When the adults do drink though, it s raw milk, as it s available, fresh, and cheap. Urban consumer, Arusha Region contains a lot of vitamins and proteins, and is good for the body s health in general. Urban consumer, Iringa Region People drink milk for its nutritional value although local raw milk is preferred. It becomes questionable when coming from other regions. Livestock Officer, Morogoro Region Consumers understand health benefits of milk (strengthening bones and teeth, contains proteins and calcium) All interviewed consumers prioritize quality, recognizing potential health hazards; roughly half do not know how to quality check Dairy products from local cows are preferred, given high fat content and better taste Fermented milk and yoghurt very popular due to taste preferences Pasteurized milk for some is viewed as unnatural, and some see processed milk as fake milk Most cited consumption factor is family size (children, elders, etc.) Source: TechnoServe field research, 2012 27

Consumers call out prices and lack of availability as major barriers to consumption Motivation to make purchasing decisions Ability to make purchasing decisions Opportunity to make purchasing decisions Consumption Barriers Other products available satisfy needs Skepticism about benefit of milk for adults Poor perception of processed milk Rising dairy prices and/or lack of payment options Uncertainty about milk quality and adulteration Lack of educational/knowledge about benefits of milk Lack of trustworthy fresh milk suppliers in the neighborhood Market shortages during dry season Ideal Consumption Common listed constraints to dairy consumption were 1) high prices, 2) lack of availability in dry season, and 3) retailer locations too far away from home Potential to increase consumption by ~20% by flattening seasonality Processed milk is far too expensive for majority of consumers Most livestock officers interviewed believe large dairy consumption is still untapped 28

Consumers can buy processed dairy products from retailers or unprocessed products and raw milk from kiosks Processor MCC Retailers Fresh milk and yoghurt most popular products; butter and cheese in smaller quantities Some retailers have quality issues from processors (spoilage) Consumer Trader Producer Milk Kiosks Raw milk and yoghurt are main products purchased Quality and milk temperature may be an issue coming from producers and MCCs Most sellers to kiosks are male due to long distances and MCC ownership Consumer 29

Retailers and Kiosks typically add 15-50% value to milk price depending on season and product type Value for 1L of fresh processed milk ILLUSTRATIVE Figures in TZS 1200 1000 800 650 600 900 100-350 1000 Processed milk tends to be lower margins than fresh due to specific mandates by companies Ex. Tanga Fresh mandates that 1 pack of fresh milk, which costs ~400TZS, be sold for 450TZS in Tanga 400 200 0 Price purchased - low Kiosks/retailers unwilling to give cost breakdown, but only large supermarkets had a cold chain. Price purchased - high Value addition Price sold Margins fluctuate during seasons as well. Large shops have difficulty selling milk in rainy season, as 1) milk is plentiful, and 2) people stay indoors or on their farms Source: TechnoServe field research, 2012 30

Purchase decision for Retailers are based on price, convenience, and consumer demand Price (TZS/L) Convenience/Quality Relationship 800-1500 TZS + Delivers to retail outlet + Quality usually non-issue - High purchase prices - Forced retail prices Price set by processors No financial contract Agreed upon price Payment right away Processors 700-900 TZS + Provides transportation + Provides sufficient quantity - Common quality issues Price usually set by traders Financial contracts 100% payment right away, agreed upon price Trader Retailers 700-900 TZS + Tests for quality - Most do not deliver MCC sets price No financial contract Agreed upon price Payment later MCC 31

Purchase decision for Milk Kiosk/Canteen are based on price and convenience Price (TZS/L) Convenience/Quality Relationship 500-700 TZS + Fresh milk - Very common quality issues with dilution - Traceability - Unstable supply of milk Price usually set by producers No financial contract Agreed upon price Almost always payment right away (~85% of interviewed retailers) Producer Milk Kiosk 600-900 TZS + Provides transportation + Provides sufficient quantity - Common quality issues Price usually set by traders Financial contracts 100% payment right away, agreed upon price Trader 32

Many retailers complain of capital supply as main deterrent against a robust cold chain; see value in seller formalization Rules and Regulations The milk we buy is not in high quality we sometimes accidentally buy old milk No formalization of sellers make it difficult for retailers to pick out quality sellers This leads to wastage Imports priced at equally or even lower compared to local brands Flow of information Retailers Support Services I have very small capital the loans we receive are not enough Access to credit common complaint amongst kiosks and canteens This leads to inadequate cold chain No training deemed necessary on milk quality Most retailers obtain pricing information from their milk sellers, as well as nearby shops Retailers wary of quality from all sellers, including processors (ex. Retailers in Tanga must watch out for Tanga Fresh products spoiling before reaching store) 33

Traders are value chain intermediaries that play a role connecting producers to markets in the informal markets Traders Larger bulk purchases Producer Smallholder farmer Raw milk, produced within past 24 hours Unregulated, local market Kiosk Comprise ~75% of sales from interviewed traders ~50% of kiosk purchasers are women (Iringa) Small purchases Many consumers are regular customers Typically no refrigeration or quality checks Health and hygiene issues from dilution or poor transport facilities Consumer Comprise ~25% of sales from interviewed traders ~50% purchased by women Prevalent in town centers Consumers buy in frequent, small quantities MCC Uncommon, as MCCs typically purchase from farmers directly 34

Farmers are motivated to sell to a trader when other channels exhausted or far away; prices usually favorable Price (TZS/L) Convenience/Quality Relationship Trader TZS 600 800 + Picks up direct from farm + Favorable prices - Unstable buyer Bulk/delayed payments Agreed upon price Prices negotiable Producer Milk Kiosk TZS 500 700 + Permanent location + Easy debt followups - May not take all milk - Transport not provided No official contracts Agreed upon prices Medium farmer loyalty Consumer TZS 400 1000 + No transport costs + Fast payments - High price fluctuation - Unstable demand High farmer loyalty Strengthens neighborhoods Informal contracts MCC TZS 400 600 + Consistent buyer of milk + Traceability for payment - Transport not included - May be far away Financial contracts common Bulk/delayed payments Low farmer loyalty to MCC Traders seen as a necessary evil, as many processors and MCCs are not present in rural areas. Traders tend to give better prices than MCCs, and during wet season when farmers have high milk surplus, they push much of their milk first through traders. 35

Trader margins of 20%, with greatest costs in fuel ILLUSTRATIVE Sample Financial Statement Revenue TZS / Week Liters Sold per Week 1,400L Sale Price per Liter 850 ACTIVITIES Pick-up milk from farmer network, transport to town market Maintains network of buyers, which are often a mix of coolers/kiosks, restaurants, hotels, and direct consumers May own/operate own cooler in town to sell to individuals Milk Income 1,190,000 Expenses COGS 840,000 Fuel 50,000 Salaries 30,000 1 STRENGTHS Strong knowledge of market, consumer needs 1 WEAKNESSES Do not refrigerate milk in transit; milk temperatures raise significantly, lessen quality and safety Machinery (includes maintenance, insurance, and depreciation) 30,000 Costs of Production 950,000 2 Perceived as bad guys by other actors/ stakeholders in the value-chain Net Profit 240,000 Profit Margin 20.17% COST DRIVER(S) Costs well-split between fuel, salaries, and machinery. Source: TechnoServe field research, 2012 36

Farmer-trader relations strengthen during high season as farmers eager for more market access Quotes During dry season, I cannot buy enough milk to satisfy my customers Instead of selling 50 liters a week in high season, I sell around 20 or 25 during low season There times of the year where I can t sell all the milk I buy! This usually happens during wet season, when there is so much milk availability that no one needs to purchase from me I will change my pricing from wet to dry season. In dry season I buy for 800 TZS, and in wet season I will buy for 700 TZS. Trader demand and supply changes dramatically throughout the year. Demand lifts slightly in high season as availability of milk drives an increase in consumption In low season, supply drops sharply, forcing prices up In high season, traders have more pricing power with farmers, as producers are looking for any market outlet. However, traders lose pricing power with consumers given availability of milk. Source: TechnoServe field research, 2012 37

Traders have little to no support from external parties, but have a good feel for production and market fluctuations Rules and Regulations The government doesn t like us, but they don t do anything to stop us No formalized system No taxes/charges No price regulation Government banned informal milk channel Very little enforcement of regulatory activities Trader Support Services Our business is on its own no one is supporting us No access to credit No extension or training services provided by gov t nor private sector Flow of information There are times when I cannot buy enough, and times when I cannot sell all of my milk Biggest issue is seasonality; traders find it difficult to manage demand and supply Consumers generally trust traders milk quality Traders trust producer quality 38

Few independent transporters in Tanzania, as most processors are vertically integrated Transporter Producer MCC Very few third-party transporters collecting milk from MCCs and producers for processor delivery; most processors are vertically integrated into this segment (Tanga Fresh, Tan Dairies) Third party transporters rarely have pricing power on demand / supply Typical volumes can range from 500 27,000 liters per week Women are not present in this segment at all, as they cannot travel long distances alone Processor Women have to stay at home and take care of the family of course women cannot be transporters. That is a man s job. - Processor from Musoma, Mara 39

Transporter margins one of the lowest in the industry, due to high prices in and low prices out Cost structure for 1L of fresh milk Figures in TZS 1200 Most significant costs around fuel and labor 1000 800 600 400 455 Profit margins of 7.10% 45 24 2 18 19 43 606 Poor road infrastructure is one common complaint amongst transporters, as bad conditions lead to delayed deliveries and spoiled milk (wastage) due to lack of refrigeration 200 0 As Tanzanian fuel prices continue to increase, this may put further pressure on transporter margins Note: Other bucket includes equipment purchase, water Source: TechnoServe field research, 2012 40

Tanzania currently processes 100-150K liters per day across the country, comprising only 2-3% of total milk production Processors Producer Retailer Small canteens and kiosks Large shops and supermarkets MCC Transporter Some processors have vertically integrated into chilling & bulking, very few into production Pasteurized milk, yoghurt, cheese, and butter are common products; only 1-2 processors have UHT capability Key barrier: low supply of milk due to seasonality and poor infrastructure forces plants to run at underutilized rates, keeping profits low Non-retail outlet Few school feeding programs Hotels and restaurants buy direct from processors 41

The country has 60+ processers spread across most regions, producing ~110,000 litres per day Distribution of processors Most processors sell dairy products locally, with the exception of large processors (Tanga Fresh sells 80% into Dar es Salaam) Mara accounts for ~40% of national milk processing capacity Tanga has ~15% of total installed capacity Arusha processors have ~20% national capacity Note: Position of processing plant bubbles only indicative of region, not true location; removed plants not operating from analysis Source: Ministry of Livestock and Fisheries Department, 2009; Niras Survey on Dairy Products Market in Tanzania, 2010 42

Thousands Processors producing far below capacity, with national average 25-30% Processor Production and Capacity Daily capacity and utilization (L), 2009 16 14 Daily capacity 12 Average attained 10 8 6 4 2 0 50K 30K Increasing supply requires increasing coverage of MCCs and transportation High supply fluctuations due to seasonality Ex. Tanga Fresh processes at or above capacity in high season, but below 25% in low Farmer prefer selling to traders due to higher prices Source: Ministry of Livestock & Fisheries, 2009 43

Top 2 processors responsible for ~50% of total production, but remaining market fairly fragmented Processed milk market share % of total processed milk, 2009, top processors highlighted Musoma Dairies 27% Tanga Fresh 22% 6% ASAS 5% 35% 5% Mara Milk Tan Dairies Remaining processors Processors have local monopolies, but competition tough in Dar Largest processors welldistributed throughout Tanzania Tanga Fresh in Tanga ASAS in Iringa Musoma Dairies and Mara Milk in Lake Zone International and Kilimanjaro Dairies in Northern Highlands Tan Dairies and Azam in Dar / Coast region Source: Ministry of Livestock & Fisheries, 2009 44

Major processor cost drivers are infrastructure-based: power, transport, water, and government taxes Cost structure for 1L of fresh processed milk Figures in TZS 1200 1175 Profit margins of 1000 ~13% 800 600 400 200 0 600 30 25 100 100 160 160 We can improve our margins if we have more constant supply of milk during dry season. - Production Leader, Tanga Fresh Most significant costs are Power, Transport, and Taxes Power: significant costs arise from outages that result in high generator use and spoiled milk Transport: Collection from farmers require significant travel; fuel costs have also risen Prices sold are based off highly competitive market with cheap imports Currently only Mara Milk operates a UHT factory (from interviewed); profits are negative for the product Note: Other bucket includes water, transport, taxes Source: TechnoServe field research, 2012 45

Purchase decision for Processors are based on price, ease of transport, and quality Price (TZS/L) 550-700 TZS Convenience/Quality + Large quantities of milk + Traceability + Tests for quality - Transportation not included Relationship Pricing based on negotiations between the two parties; contracts occur in some relationships MCC 300-900 TZS + Sells on credit - Many do not deliver - Does not test for quality - Price fluctuation - Quantity fluctuation Pricing power mixed between producer and processor; unofficial contract in price and continuity Producer Processors N/A + No transport costs + Supply predictability - Large amt of time and investment required N/A Own supply Common challenge in back linkages is convenience, as price and quantity fluctuates heavily throughout the year. Processors see benefits in creating own supply, but lack of capital is an issue. Source: TechnoServe field research, 2012 46

40%+ of processor supply comes from smallholder farmer, with high processor interest in upstream investments Processor supplier profile % of annual supply, 2011 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% ESTIMATES Smallholder farmers Commercial farmers Own supply A little under half of processed milk supply is sourced from smallholder farmers Another ~45% is sourced from commercial farmers Processors have high expressed interest in upstream investments that would increase production and yield We have tried to educate farmers on production, but we can only reach so many we have seen small training improvements, but more needs to be done. - Production Leader, Tanga Fresh Note: This does not reflect all interviewed processors, as some did not keep records or refused to answer Source: TechnoServe field research, 2012 47

Milk collection centers few and far between in Tanzania, though remain a key part of linking the farmer to the market Producer Chilling & Bulking Collection step in value chain Largest processors in Tanzania are vertically integrated (Tanga Fresh) Geographically placed in high farmer density areas with milk supply Processor Trader Transporter Infrastructure listed as key constraint: power shortages, difficult roads, and transport and cooling costs Quality of milk is a key concern at a few MCCs Difficult to plan ahead due to high seasonal fluctuation in supply Kiosk 48

Bulking and chilling plants run on 10% margins, which can drop in low seasons; labor, machinery, and power are the biggest costs Chilling plant cost structure per litre ILLUSTRATIVE Figures in TZS 700 650 600 550 500 400 300 200 100 0 17 10 6 0 2 65 Profit margins of ~10% Largest cost drivers are labor, machinery, and power Power shortages remain one of the most common complaint Some chilling plants run on subpar equipment that frequently break down Meager profits not sufficient to invest back in the MCC through equipment purchases, etc. Source: TechnoServe field research, 2012 49

Enabling environment can be improved through gov t policy, training, facilitation of capital and information flow Rules and Regulations Processor buyers are registered with the government, but milk producers rarely are Some milk collection centers cite government subsidy help with equipment and packaging Some milk collection centers say additional taxes and charges are enforced by the government Flow of information I m not too sure what the market prices are for milk I just pay what my buyers ask for MCC Support Services Lack of capital is a big issue even the loans we currently have are not enough Some larger milk collection centers able to borrow money, though loans small Training services rarely performed by government (exception in Morogoro, where SUA and the gov t provide training Half interviewed MCCs are not aware of market prices in their region Informal contracts dominate the market, with sellers coming regularly and prices set ahead of time 50

There are ~1.3M households in Tanzania who own cattle Producers Inputs High milk production fluctuation due to seasonality (poor feed/grasses, lack of water during dry season) Large amounts of milk consumed on farm and never marketed Ex. In Central Tanzania, a study showed ~75% of milk produced is consumed or lost on farm An estimated 1.15M households own indigenous cattle which produce ~70% of total milk An estimated 125,000 households own dairy cattle which produce ~30% of total milk Average milk yield is low due to low genetic cows producing 0.5 2 liters per lactating cow/day (6-7 liters for dairy cows, on average) Formal Chain Traditional Chain Source: TechnoServe field research, 2012; Rural Livelihood Development Company 51

Coast, North, and Southern Highland geographies are competitively endowed to supply milk to existing market systems Dairy farm locations Lake (A) North (B) A Farmers Productivity Environment 1.5M farmers 8.1M cattle <1% improved dairy cows 1-2 liters per cow per day 120-170 milk days/year Most farmers are pastoralists, zero grazing rare Some areas close to rivers, Lake Victoria Coast (C) B 0.7M farmers 3.9M cattle 6% improved dairy cows 2-4 liters per cow per day 140-170 milk days/year Zero grazing applied frequently due to lack of grazing land Fertile lands, forested, frequent water access C 0.9M farmers 1.7M cattle 6% improved dairy cows 3-6 liters per cow per day 140-200 milk days/year Mix of zero-grazing (Morogoro) and freerange (Tanga) Abundant water and grass (evergreen) Southern Highlands (D) D 1.2M farmers 2.2M cattle 5% improved dairy cows 2-4 liters per cow per day 100-140 milk days/year Lack of green grasses and water in Iringa in dry season Smallholder farmers employ free range *Farmers defined as rural households involved in agriculture Source: TechnoServe field research, 2012; National Sample Census of Agriculture (2007/2008); Ministry of Agriculture, Food and Cooperatives 52

Density maps show high production and consumption potential in the Lake Region, Northern, and Coast regions Milk offtake per sq. km People per sq. km Cattle per sq. km Note: Densities of livestock species in 2000, calculated on total land area Source: FAO (2001), LandScan (2002), FAO (2005) 53

Production is characterized by low usage rates of inputs due to lack of knowledge, accessibility, and affordability Farming management Breeding Feeding Best Practices High quality AI - Increase genetic quality of cows to produce milk Sufficient nutrition: balanced intake of energy, protein and minerals - Mix of bulk and supplementary forages, concentrates and minerals Tanzania Use of local bulls as well as AI - Perpetuate low genetic quality - Increase risk of disease Deficient nutrition - Common pasture grazing with no supplemental minerals or proteins - Fresh green grass is mostly water containing a low level of nutrients - Dependent on weather conditions Some farmers were not educated on farming techniques or proper herd care Dairy breeds seen as unaffordable by most farmers (quoted price around 800K 1M TZS) Farm management highly dependent on season and natural availability of water/grass Water Access to water at all times Water availability dependent on seasons; during dry, access drops to as low as 50% of the time Health Preventive health care, including vaccination, regular spraying and warming Minimum preventive health care, if any; cited as too far away and/or too expensive for most farmers Proper veterinary services at times inaccessible and unaffordable 54

Dairy income Other Milk can be a significant part of income for farmers with cows, having both cultural and nutritional implications Total dairy farm income Figures in TZS Depending on region, cows are seen as economic or cultural, sometimes both Mara: long tradition of cattle farming, though rarely for milk Arusha: Masai tradition of keeping many cows Livestock perceived as assets as well as income-generating assets Cows typically used for agriculture, meat production, and milk Cows also held as sources of emergency cash High interest from farmers in increasing dairy income given large portion of overall household income Note: Includes large commercial farms as well as smallholder; Survey N for Tanga =12, Arusha = 10, Iringa = 10, Morogor = 10, Mara = 10, Source: TechnoServe field research, 2012 55

Farmer economics local cows ILLUSTRATIVE Sample Financial Statement Revenue TZS / month Liters Sold per Month 100 ACTIVITIES Typically employs 1-2 laborers, family labor also typical Cows often open graze Sale Price per Liter* 650 Milk Income 65,000 Caveat: Estimate relies Expenses Labor on farmers' ability to accurately report the volumes and prices of 2,825 Feed/Fodder milk purchased, as well as monthly costs 9,750 Water 250 Artificial Insemination 0 Other 1,550 STRENGTHS 1 Very low production costs 2 Disease resistant; can handle dry season 1 2 WEAKNESSES Low yield, limited opportunity to increase production per cow given poor breed quality Open grazing exposes cattle to outbreaks Costs of Production 14,375 Costs per Liter Margins are high ~140 / liter given most farmers see dairy as a side Net Profit product of general 50,625 Profit Margin agricultural activity 78% COST DRIVER(S) Feed / fodder and labor are the biggest cost drivers, which are fairly stable and predictable Source: TechnoServe field research, 2012 56

Farmer economics exotic cows ILLUSTRATIVE Sample Financial Statement Revenue TZS / month Liters Sold per Month 1,000 ACTIVITIES Typically employs 2 laborers, rarely uses family labor Employs cut-and-carry model to feed cows Sale Price per Liter* 750 Milk Income 750,000 Caveat: Estimate relies Expenses Labor on farmers' ability to accurately report the volumes and prices of 104,245 Feed/Fodder milk purchased, as well as monthly costs 121,000 Water 18,800 Artificial Insemination 4,000 Other 30,635 Costs of Production 278,680 1 STRENGTHS Greater output per cow by improving breed 2 Morphology means larger sale price 1 WEAKNESSES Poor availability of feed and fodder in certain seasons and areas frustrates efforts to improve output 2 Requires much more attention and costs 3 Prone to disease Costs per Liter Margins are high ~280 / liter given most farmers see dairy as a side Net Profit product of general 471,320 Profit Margin agricultural activity 63% COST DRIVER(S) High costs of feed and fodder threaten the financial viability of the cross-breed/exotic cow business models. Also requires much labor and attention to combat disease and death. Source: TechnoServe field research, 2012 57

Business case for milk collection centers depend on increasing dairy production due to farmer s preference to sell into informal channel ILLUSTRATIVE Surplus Sold to MCC/ processor (400-600 TZS/L) 4-6 Liters Sold to traders/ retailers (500-800 TZS/L) Only when individual household s production exceeds 6 liters, can the milk collection center / processor add value proposition by providing collective marketing This number increases when market dynamics become stronger i.e., closer to town Large potential to increase cow yield can filter more milk towards the formal channel When cows productivity reaches maximum, the only way to increase production is to add more cows Key issue: Many farmers interviewed said they could produce more milk. But with limited channels (and cheap prices), they are choosing not to 2-4 Liters Sold to neighbors (400-1,000 TZS/L) 1-2 Liter Consumed within household Traders typically provide higher prices for milk Convenience in transportation Farmers will sell a few liters first to the MCC/processor to maintain ties for wet season. Sales to neighbors increase as percentage of farmers in the area owning cows drops Convenience in payment, buyer network, and transportation play more in selling decision than price Source: TechnoServe field research, 2012 58

Tanzanian farmers use different grazing options based on land scarcity, climate, and other cash crop production Grazing options Fixed assets Land usage Dependence on weather Feeding Zero-grazing Semi-grazing Open-range Forage and concentrates Pasture and concentrates Pasture Production High Medium Low Dairy production systems in Tanzania differ based on region and climate. In Tanga, some farmers apply zero grazing methods, but pastoralist farming is also common. In Arusha, there is a lack of grazing land, so farmers apply the zero grazing concept. In Morogoro, land is used mostly for rice and maize production. Majority of cattle owners prefer the zerograzing method. In Mara, most farmers are pastoralists and zero grazing isn t applied, though land is scarce. Source: TechnoServe field research, 2012; Maastricht School of Management Organizing Milk Collection in the Tanzanian Dairy Sector 59

Depending on region, some producers have a lot of government support, but flow of market information rarely gets to farmer level Rules and Regulations Support Services I don t really think the gov t is involved in dairy I haven t interacted with them The government has been extremely supportive in our dairy production A quarter of interviewed farmers say their buyers are registered with the government, and are thus easier to track down for debt payments Many interviewed dairy producers say they do not see the gov t influence their sector SH Farmers 25% of respondents have the ability to borrow money 50% of respondents have had training or extension services (usually through gov t or local schools) Government subsidies contribute to 33% of respondents (9 in Morogoro, 4 in Tanga, 1 in Iringa) Flow of information I only know the prices that I receive from my buyers I don t know where I would get more information Only 52% of surveyed farmers know what market prices are for milk sold in the region 39% of interviewed producers are aware that different buyers will pay different prices 60

Women less likely to control livestock ownership and decision-making but do the majority of labor Level of Female Involvement Evidence Benefit-sharing Who benefits from what, how, where, when and why? Participation Who is included in what, how, when, where, and why? Medium Medium According to custom, the husband remains in most cases the master of the family patrimony and the woman has no right of control over the assets of the household However, in certain tribes like the Masai, women own the milk, and thus retain the money collected from any milk sales (57% of interviewed farmer families attest to this point) Women tend to have lower participation in co-ed groups, but a few strong MCCs/cooperatives are women-only, such as Nronga Women Dairy Cooperative and Kalali Women s Dairy Coop Decision-making Who controls what, how, when, where, and why? Low 65% of farms managed by men, 30% led by females, and 5% jointly managed by spouses Women unlikely to own/control livestock, and long-standing inequities in land/cattle ownership exist; however, milk is sometimes owned by the woman (dependent on tribe) Decisions to sell cattle for emergency cash falls in the realm of the male only Access Who uses what, when, where, and why? Labor Who does what, how, when, where, and why? Low 2 5 % High Women face constraints on their movement and thus access to dairy markets; Women do not carry milk to MCC or retailers due to distance/travel (77% of interviewed subjects say the man transports) In HH with a man as a head, women still spend more time than men carrying out activities related to livestock production Common beliefs heard in interviews relegate livestock and farm care to women s domain Sources: TechnoServe field research, 2012

Livestock input services have limited reach across Tanzania Livestock Input Provider Input provider usage at low levels, particularly in rural areas Vaccinations are the only input with 100% participation from interviewed subjects; some inputs usage as low as 30% Key barriers to increasing input penetration is (a) affordability, (b) accessibility, and (c) education on proper usage Some extension services are provided by the district/local government extension staff; local staff treat sick cows and give advice to farmers Level of government interaction depends on input Majority of veterinarians are government workers; very few have private practices Large processors working to provide extension services for farmers: Tanga Fresh building feed and veterinary service stations at their MCCs The high cost of supplement feeds as well as persistent drought leads to insufficient feeds, particularly in dry season This leads to low milk production. Arusha Livestock Officer There is very poor distribution of services, as it s difficult to get access in rural areas. Most of the time, farms are not reachable. Iringa veterinarian Producers Source: TechnoServe field research, 2012 62