TechFit : A Tool for Prioritizing Feed Technologies

1. TechFit : A Tool for Prioritizing Feed Technologies Adugna Tolera

2. Objectives • To have a common understanding, interpretation and application of the tool • To learn how to score and match technology attributes and context attributes of farmers • To customize the application of the tool to the local context

3. Background • Reality No. 1 (Reality of farmers) • Livestock production is important • Feed is a major constraints (FEAST & Other reports) • Farmers are looking for a remedy to the problem • Reality No. 2 (Reality of research & development efforts) • Various feed technologies generated by the research system • Lack of systematic approach for prioritizing available feed technologies • Poor adoption rate of available technologies • Wastage of substantial efforts and resources

4. Feed interventions often do not work – why? • Failure to place feed in broader livelihood context • Lack of farmer design and ownership • Neglect of how interventions fit the context: land, labour, cash, knowledge etc FEAST Techfit

5. What is TechFit? • A discussion tool for prioritizing feed technologies • Helps to identify suitable technologies for evaluation and screening • Designed to filter best bet technologies from a basket of technologies available to farmers • Provides better understanding of why and why not technologies work or do not work

6. How does it work? • Technology options to address feed problem (list of potentially available technologies) • Technologies are filtered at different levels • Only technologies with high total scores carried forward to the main filter

7. How does it work? (Cont …) • Main filter – involves combining scores of technology and context attributes to arrive at total score • Technology attributes – requirement of a given technology for land, labor, cash/credit, inputs and knowledge • High score => low likelihood of adoption • Context attributes – availability of land, labor, cash/credit, inputs and knowledge • High score => high likelihood of adoption

8. Match farmers’ context to technology If technology demands land => low score for land If farmers do not have or have very small land holding => Low score for land

10. How to do scoring and ranking? • List of potential technologies obtained from the research system • Context relevance and impact potential – by experts at each specific location • Technology attributes (requirement of the technology for land, labor, etc. ) – by experts • Context of farmers (availability of land, labor etc.) – by farmers (interview a group of representative farmers and ask them to score)

11. Cost benefit analysis • Short list the best 3-4 technologies for cost-benefit analysis • What does the technology cost? (type of feed, amount used, % of total feed, cost, % of total feed cost) • What does the technology deliver? (animal performance measure, % contribution to the performance change, % contribution to income gain) • Is it worthwhile?

12. Cost-benefit analysis • Method not yet well developed and refined • Mostly based on a number of assumptions using partial budget analysis • Compare additional costs and additional benefits i.e. marginal benefits

13. Intervention name Clear description focusing processes and actions with pictures and glossary for specific terms • Technical Information • Key technology attributes • Land area required • Labour, including gender • Skills/Knowledge • Cash/Credit • External inputs • Capital / infrastructure • Applicability • Purpose / Addresses constraints – opportunities • Which animal? • Agroecological, farming system suitability including socio-cultural issues (e.g., taboos) if applicable • Scale • History of use • Potential to integrate with … • Benefits • Primary (including time dimension, etc.) • Secondary • … • Adoptability characteristics • (=conclusion: simplicity, observability, use, etc. • …

14. Adoptability Protocol - Process • Past experiences regarding introduction of technologies, including uptake, community feeling, etc. • Ranking of livelihood ambitions/aspirations in general and for agriculture and livestock in particular • After becoming more and more reductionist and analytical, bring it back into the broader perspective Objective  Subjective • FGD on options • Give info on options • Ask community to rank • Discuss ranking, ‘why’, etc. (guiding points/questions) • Link to CBA data • Select trial farmers for AR (model or pioneer farmers)

16. Data we need to derive from FEAST to feed into Techfit • Main constraint • Seasonality • Quantity • Quality • Dominant commodity • Beef • Dairy • Sheep/Goats • Pigs/poultry • Farming system • Pastoral • Agro-pastoral/mixed • Intensive/mixed (crop-livestock) • Landless • Core context attributes • Requirement for land • Requirement for labour • Requirement for cash credit • Requirement for inputs • Requirement for knowledge/skills

17. Seasonality • Consult seasonal calendar – estimate proportion of minimum availability to maximum availability • 1.0 = 0 • >0.75 = 1 • >0.5 = 2 • >0.25 = 3 • >0.0 = 4 • Is minimum in the dry/winter season? – Winter season scarcity • Is minimum in the growing season? – Growing season scarcity

18. Quantity • If you place more basal feed in front of your animals would they consume it? • With extreme enthusiasm = 4 • With considerable interest = 3 • With some interest = 2 • Yes but not immediately = 1 • No = 0 • Something also about interest in supplemental/high quality feed?

19. Quality • If you placed more basal feed in front of your animals would they consume it? • With extreme enthusiasm = 0 • With considerable interest = 1 • With some interest = 2 • Yes but not immediately = 3 • No = 4

20. Commodity focus • On a scale from 1 to 10 how important are the following enterprises to cash income: • Beef • Fattening • Breeding stock • Dairy • Sheep/Goats • Fattening • Breeding stock • Pigs/poultry • 0-2 = 0 • 2-4 = 1 • 4-6 = 2 • 6-8 = 3 • 8-10 = 4

21. Farming system • Which of the following best describes the target group: • Pastoral • Agro-pastoral/mixed • Intensive/mixed (crop-livestock) • Landless

23. Experiences in testing and application of the tool • Tested to prioritize feed technologies for 3 different commodities (dairy, beef, sheep) in different parts of Ethiopia • Preceded by assessment of livestock production and feeding systems using Feed Assessment Tool (FEAST) • Enabled rapid prioritization and short listing of potential feed technologies • The pre-filter (context relevance score) helped a great deal to focus attention on those technologies that are relevant in the area.

24. Strengths of the tool • Enables rapid location specific prioritization and short listing of feed technologies in different agro-ecologies and production systems • Puts feed in a broader context and filters technologies for specific contexts (agro-ecology, production system, farmers’ contexts etc.) • It is robust in screening out technologies that are not relevant in a given context • Gives good indication why some technologies are not easily adopted

25. Limitations of the tool • All scores are based on subjective judgments. Thus one has to be well versed with the subject matter and the local conditions to give a realistic score. • Cost benefit analysis is based on a number of assumptions and the validity depends on the soundness of each assumption. • Most feed technologies make only partial contribution to the total diet  a challenge of partitioning the contribution of the feed in question to the performance of the animal

26. Thank you!