Knowledge Exchange Strategies BMGF reviewed (upload)

Editor's Notes

• #3: Spread (scale) of farmer technology uptake depends on geographical area and type of technology. It also depends on farmer type, agricultural eco- zoning, ethnic groups, gender, complexity & risk of a technology. Yet, the focus here is on established “good technologies”, which have UNIVERSAL valence.
• #4: The holy grail of achieving large-scale adoption of agricultural innovations among the majority of resource poor farmers has taken many forms through development history. From T&V to farmer- field schools. None has proven to last and being effective at a scale, even if each of them have shown temporary or pockets of context-related success. Difficult to formulate a clear cut advice for IVCTs on how to tackle this challenge, beyond quick fixes (e.g. posters and leaflets, training manuals, use of mass media for marketing the technology etc.) Nevertheless, there are several well “known knowns”..
• #5: The first “known known”: This graph was from an Poverty Action Lab ATAI presentation (and ultimately from a World Bank source). It also shows how there is a big yield gap between developed world and developing world. 50% of increase of yield growth largely depend from new variety improvement for productivity and resistance to biotic and abiotic stress. Good agricultural technologies: a) with demonstrated productivity gains >50% b) relevant to farmers in different country agro- eco-zone c) in line with GAP standards Examples of good technologies with demonstrated productivity gains: Efficient and timely fertilizer application, sowing of improved seed varieties, organic composting, reduced use of pesticides (IPM) and reduced tillage planting techniques.
• #6: The second “known known” This diagram is drawn from the AgDev Strategy Refresh Memo of 2011. It just shows one set of examples, but there is a very high yield gap in Sub-Saharan Africa , despite the existence of good seeds. Yet, yield gaps for food security crops (up to 200- 400% increase potential for sorghum millet and maize) show clearly the opportunity of increasing productivity by just adopting or adapting already “existing technologies and varieties” Effective delivery of extension/KE services create the enabling environment where small-holder farmers can access and adopt beneficial agricultural technologies at scale to narrow the large yield gap. KE can also engage farmers to provide feedback to research, during R&D investments for the development of new technologies.
• #7: This is a well “known known”In Malawi only 18% of farmers have had more than one contact with an Agricultural Extension Officer ( There is a great need to have more cost-effective KE models scalable through public National Agricultural Systems (also viable and scalable business models of “private” delivery KE delivery difficult to be achieved for, without public financing There is a great scope for making use of fellow farmers as extension agents as cost- effective and scalable mechanism of extension (difference between progressive farmers and peer farmers! see Yale study (http://ssrn.com/abstract=2315229 ) There is scope to use input dealers as a vehicle for extension delivery (need for public control mechanisms to avoid biased advice) There is a need of reaching the majority of farmer through radio and mobile with Universal good agricultural technologies.
• #8: There is lack of evidence and data from rigorous research because of: a) lack of methodology dealing with complexity b) cost of RCT c) no systematic ways to harvest farmer feedbacks. Swanson, B. E. and R. Rajalahti. (2010) Strengthening Agricultural Extension and Advisory Systems: Procedures for Assessing, Transforming, and Evaluating Extension Systems. Agriculture and Rural Development Discussion Paper 45. The World Bank. http://siteresources.worldbank.org/INTARD/Resources/Stren_combined_web.pdf Anderson, J. R. and G. Feder. (2007) Handbook of Agricultural Economics. Agricultural Extension. 3: 2343-2378. Waddington, H., B. Snilstvedt, H. White, J. Anderson (2010) The Impact of Agriculture Extension Services: Protocol, 3ie Synthetic Reviews – SR009. http://www.3ieimpact.org/admin/pdfs_synthetic/009%20Protocol.pdf
• #9: The Foundation has in the past five years a number of KE strategies have already identified strategic intervention strategies (Steiner2008:2009, Kentaro Toyama 2012, Witt, 2013, Steiner 2013) The KE new strategy 2014, builds on this body of knowledge and offer increased focus in service to crop value chains and sustained productivity goals per Ag TOC. About 30% of all AgDEV grants in 2011 had some last mile KE component Good KE Models: 1. Cost Effective 2. ICT integration for content mgt. 3. Collecting real time feed-back 4. Facilitating interaction at village level (last-mile) Impact Research & Data Mainstreaming toolkits Innovation & Extension Model Farmer organizations and networks ICT & Advocacy as crosscutting Scaling through partnerships with country national Ag systems Steiner, 2008 Internal consulting Research on models (exploration, evaluation, etc.) Diagnosis in anchor countries Advocacy for KE Shared grant making Vertical, integrated support in anchor countries Global community building around KE Toyama, Interim strategy and 3 top priority, 2012 Effective adoption of best practices and inputs requires a new farmer-centric R&D – Knowledge Exchange paradigm Provides real-time, appropriate and context-specific information Is scalable at low cost due to mass customization Can be holistic with integration of multiple information streams Empowers extension workers and farmers due to interactivity Witt, 2013 Deep understanding of smallholders and their trusted knowledge networks Drive scale by dramatically lowering the cost of extension services Exponentially increase access to quality extension content Catalyze continuous improvement and learning networks Steiner, 2013 Good KE Models:
• #10: In red are BMGF investments that are not managed by the KE POs but that have a great relevance in disseminating information and facilitate repeated interactions with farmers. These models have to be adapted and integrated for different information needs/specific focus in different Crop & Livestock Value Chains and scaled thorough Country National Programs e.g. ATA, ADD, NRLM. Broadcast: Limited farmer engagement Narrowcast: Frequent farmer engagement and farmer groups organization support
• #15: KE Role – Identify and spread cost-effective models in support of VCs with different farmer engagement intensity and Action-research on models and adoption as added value to crop & livestock Value Chains.
• #17: Direct investments= as functional technical unit (11%) Collaborative investments= together with specific VC POs and/other units e.g. MLE, data or with PO within the same unit. VC specific KE approaches Examples: Improved seeds: mother and baby trials, Valuation Evaluation Observation trials as marketing strategy for seed entrepreneurs Agronomy adaptations: ICT supported models for soil fertility (e.g. e-Koutir). Livestock: Delivery of extension for dairy cooperatives, village poultry vaccinations and AI inseminators. Ag. content management: Collaboration for global, national and local mechanisms of content provision and dissemination relevant to farmers, including digital solutions.
• #18: Feedback mechanisms on content and technologies have always been a core function of extension. Historically, extension has been of pivotal importance for adoption of mechanization in agriculture in the US too. The repeated interaction between tractor and implement manufacturers and farmers is what has been reported to be a key success factor in the adoption of mechanized agriculture in the US. “Extension provided training, advocacy, links between researchers and companies and farmers, experimentation” There is also an important time factor in considering large scale adoption of a technology. Farm tractors in the US –1930: 920,000 –1940: 1,567,000 –1950: 3,394,000 –1960: 4,688,000 There was also significant levels of public support spending. (Paul McNamara, University of Illinois at Urbana, Nov. 2013, “Scaling the Uptake of Agricultural Innovations: The Role of Sustainable Extension and Advisory Services” USAID, Washington DC.)
• #19: It is important to learn and absorb lessons on how to increase adoption of basic Ag technologies by poor resource farmers and get real time feedback about their value, in order to bring about the desired changes described in the Ag strategy TOC. Key messages: KE isn’t just information input. Trust and repeated engagement are also critical (these elements tend to require human intermediaries). KE is about research on cost-effective models (exploration and evaluation), and about doing the catalytic part of scaled impact. KE’s work directly contribute to VCs without competing or substituting for what they’re already doing i.e. add to the VC metrics. For example, let’s say the PO who owns Superwheat X is already spending $Y million on private-sector extension workers to sell Superwheat X to farmers in Ethiopia, so that 100,000 farmers will generate Z tons of Superwheat X in 2015. What KE might do (just an example), is to use DG in Ethiopia to influence an additional 10,000 farmers to grow W tons of Superwheat X in 2015. This is just an example, but the idea is that we would add to VC goals, not substitute their KE parts for them (unless they want that). KE is in the business of “pipes and plumbing”, the critical conduit reaching directly farmers, which means KE is agnostic about the content flowing through the pipes. That allows KE to align with VC goals, to supplement them without competing on other competency area and/or PO experiences.
• #21: Scaling Technologies: Is 20% valid in the agriculture? Does it differ in relation to crops (cash versus food crops?) Institutional base of extension and inputs and complementary services and supportive policy Many components of a functioning Ag Innovation System Repeated engagement rather than one-time push Longish time scale of major agricultural innovations Farmers and their assets Green revolution targeted best regions for irrigated rice and for wheat production (not more difficult rain-fed uplands and more marginal zones) US agric productivity built on base of literate farm population, secure property rights, functioning cooperatives, access to credit, commercial agribusiness involvement and investment, infrastructure, substantial public funding