Adoptability component




Brigitta to finalise, with Keith


Notes from the May 2013 meeting


Presentation


Working group on Adoptability

Further points to be included in the FEAST excercise

  • What have been past experiences (positive/negative) in the community regarding introduction of technologies or other interventions? Have there been other development projects and how has the uptake been; what does the community feel about this?
  • The priority of livelihood options should be ranked and not just the average of 9 persons be taken – in the community discussion. à consider to include this in the focus group discussion? Add some future perspectives and ambitions/aspirations by the farmers regarding livestock species or livelihood options.

Hold a focus group discussion (FGD) with guiding questions or keywords – related to Everett Rogers’ theory to Diffusion of innovations (headlines)



Factor
Adapted definition
Comments from the working group
Relative advantage/superiority
How improved an innovation is over the previous generation.
à Maybe this is more reflected in the CBA, but also in the ranking of best-bet options after the discussion by the FG
Compatibility
The level of compatibility that an innovation has to be assimilated into an individual’s/community’s life.

Complexity/simplicity
If the innovation is perceived as complicated or difficult to use, an individual is unlikely to adopt it.

Trialability
How easily an innovation may be experimented. If a user is able to test an innovation, the individual will be more likely to adopt it.
à This is more intrinsic
Observability
The extent that an innovation is visible to others. An innovation that is more visible will drive communication among the individual’s peers and personal networks and will in turn create more positive or negative reactions.
à To move up as a column (filter) into the TechFit tool? Because it is more intrinsic to a particular technology/intervention?

Process for assessing adoptability

Hold a focus group (FG) discussion on best-bet option technology/intervention options, including participants from the FEAST but also a full representation of the community, including leaders, elders and key informants.
  • Provide some specific information on best-bet option technology/intervention options followed by a discussion on pros and cons.
  • Finalize with ranking of best-bet technology/intervention options by the community.
  • Discuss the “whys/why-nots”with the community.
  • Try to capture the below main criteria from the discussion.
  • The final decision of what best-bets will be advanced for action research by comparing the discussion points with the CBA on the best-bets. Some options will be knocked out, for others that have similar “adoptability” the CBA may help for the discussion. We opt for a “common knowledge” decision coming out of a discussion and not to have scores.[1]
  • Farmers for action research are selected according to the probability to create a successful model of the technology/intervention – they need to be livestock farmers; farmers could be recognized as ‘Model/pioneer farmers for feed intervention’ according to the cultural context. Willingness of farmer(s)
Relative advantage/Superiority à probably more reflected in the CBA, but also in the ranking of best-bet options after the discussion by the FG.
  • Is there a qualifier for labour required? Is it easy work or drudgery?
  • Can children do something alongside, e.g. herding – like reading a book?
Compatibility
  • How is the risk level – partly intrinsic to the technology/intervention, but also due to individual/community attitudes of risk aversion.
  • How is the social acceptability, e.g., do taboos exist; how is the new technology/intervention affecting gender aspects? Child labour?
  • How is the capacity to adapt the technology to the local situation?
Complexity/Simplicity
  • Is the new technology/intervention an add on to something already existing? Then it would be more likely to be adopted than fully novel interventions.
  • Is there a certain level of familiarity – more likely to adopt anything related to a known crop for example than for a newly introduced.
Trialability à this should be part of the Techfit filters?
Observability à move up as a column (filter) into the TechFit tool? Because it is more intrinsic to a particular technology/intervention?
  • What is the incentive to adopt – benefit(s) is/are quickly visible to the adopter; for example increase in milk yield in the bucket.
  • Significance of the change induced – will the farmer notice it sufficiently?

Delivery process à should already come out from the FEAST
  • What contact/fequency of visits do you have with extension officers? How qualified you feel they are? Potentially leading to capacity building and empowering of local extension service by the project or other players.
  • What is the potential to strengthen the enabling environment to promote change?



[1] For example initially, adoptability was thought to be reflected in scores (0-4)






Original notes from the march 2013 meeting

Adoptability – to be discussed by farmers + other key informants in focus group (scores 0-4)

  • Risk level – intrinsic technology plus individual/community attitude
  • Familiarity – more likely to adopt with known crop for example than with introduced
  • Add ons likely more adoptable than novel interventions
  • Past experience
  • Capacity to adapt technology to local situation
  • Incentive to adopt – benefit quickly visible to the adopter
  • Social acceptability, e.g., taboos, gender
  • Significance of the change induced – will the farmer notice it sufficiently
  • How can enabling environment be strengthened to promote change?
  • Availability of extension
  • Others… ???


IP: Impact potential of an intervention – intrinsic for each technology (scores 1-5)

  • Absolute impact = Improvement in productivity under ideal conditions (potential)

  • Should we change this to an indicator of potential beneficial outcome, including other factors, e.g., environmental impact, equity?

A: Adoptability – to be discussed by farmers + other key informants (scores 0-4)

  • Risk level – intrinsic technology plus individual/community attitude
  • Familiarity – more likely to adopt with known crop for example than with introduced
  • Add ons likely more adoptable than novel interventions
  • Past experience
  • Capacity to adapt technology to local situation
  • Incentif to adopt – benefit quickly visible to the adopter
  • Social acceptability, e.g., taboos
  • Significance of the change induced – will the farmer notice it sufficiently
  • How can enabling environment be strengthened to promote change?

Predicted impact score = IP x A

Note
Delete column on “Scope for improvement of attributes” but consider this under adoptability
Scores should be preferably impair, and 0-based (all attribute scores, adoptability)