The document discusses content management processes in selected m-Agriculture (mobile agriculture) initiatives in India. It summarizes three case studies of m-Agriculture initiatives - Reuters Market Light, IFFCO Kisan Sanchar Limited, and Lifelines. All three initiatives identified farmer information needs through surveys. They sourced content from experts, databases, and organizations. Content was localized and adapted to format/language for farmers. Feedback was obtained through surveys. Key challenges included limiting formats, sourcing experts, regulating access, validating local/quality of content, and evaluating feedback. The initiatives demonstrated potential for disseminating information and connecting experts/farmers at scale through customization and use of different media on mobile platforms.

1. Content Management Process in Selected m-Agriculture Initiatives in India Pier Paolo Ficarelli

3. M-agriculture is about tools, not about access and dissemination of agricultural information (FAO, Rome 2010)

4. We have farmer field schools for extension. Mobiles add no value to it. (CGIAR Researcher, Delhi, 2011)

6. The Info system describes contextual factors influencing information conveyance to users (design-reality check!)

7. The info chain defines relevance as the functional linkages from content all the way through to users

9. Verifiable, clear and accurate content, delivered timely in an appropriate format and language

10. A time and resource intensive process, normally underestimated

11. A learning PROCESS that requires continuous improvement

13. Targeted to farmers

14. Low-cost devices

15. Exemplary content generation/delivery mechanisms

17. To what extent the initiatives analysed strengthen key extension functions?

18. Is human intermediation a key success factor?

19. Is digital agro-information made more accessible through ICTs?

20. What kind of mobile app and/or media are most suitable for m-agriculture?

22. Business model: spin off mobile VAS of Thomson Reuters

23. Scale: + 15 000 villages 13 states 8 languages (2010)

24. Info Type: push model (SMS; voice messages on testing)

25. Content sources: various Source: Glendenning & Ficarelli, 2011

27. Business model: Partnership with major mobile operator

28. Scale: 1 million active users over 18 states

29. Info Type: push & pull model (Voice messages+ Helpline)

31. Business model: funded project

32. Scale: 150,000 farmers 2,000 villages in 3 Indian states (2010)

33. Info Type: pull model (IVR audio Q&A platform)

35. Content Management: Key Challenges 10 Format Limits of SMS and voice messages on mobile for agro-advisory: Videos? Audio + Pictures? Sourcing Content is dispersed and scattered: Agri-Google? Experts: 24H Access? Motivation? Access Identified trend is towards close access of digital repositories: Regulations? Localisation Mainly based on outsiders’ knowledge and area criteria: Farmer knowledge? Quality It is delegated to experts and relies on implicit knowledge: External validation? Feedback Client satisfaction mainly anecdotal/based on sample surveys: Sufficient? “Infomediaries” Info-need articulation and advice translation require human facilitation: Viable?

37. Why keep engaging with m-Agriculture The problem with the world is not that people know too little, but that they know many things that ain't so Mark Twain 13