Steve LeGrand

University of Guelph

March 11, 2013

Lens for exploring the generation, spread, and use of new

agricultural knowledge, along with the social, economic, and

political forces that shape the process1,2,3

Research Extension Farmers

Culture

Values Economics

Politics

• Innovation is putting something new into use2,3

• Technological or institutional (way of organizing or process)1

• Not necessarily brand new, just new to the user3

• Often many innovations in a ‘package’ and often spur more innovations2

• Blurred roles…all actors can generate, spread, and use knowledge3

Environment

• Multi-year project to improve beekeeping training and

participatory extension in Vietnam

• Involved two universities, a national ministry, and a bee research center

• Introduced new basic hive design which required project team

to adapt instruction methods

• Both have spread rapidly in the wider region

• People are modifying hive design….these are spreading too!

• Multi-layered value chains have established themselves

• People are better off!

Docile native

bees

Minimal added

labor

Honey acts as

store of social

capital

Insatiable

demand for

honey

‘Spaces’ for

learning and

sharing History of

beekeeping

• Classic methods fall short

• Innovation systems are unique and constantly changing5

• comparisons or generalizations impractical5

• Need to adopt a learning approach to evaluating AIS performance and interventions

• Delve into how and why to understand trends6

• Qualitative techniques are useful for understanding complex situations

• Paint a focused, rich picture

• Key Questions7:

• Who are the players and how do they interact? What drives them? What influences the system? What is/not working?

• Many tools and methods for various needs and stages

• Mix, match, and adapt for the specific situation!

Exploring

Analyzing Deciding

Acting/Implementing

Experience Refle

ct

Conceptualize

Experim

ent

ation

Mapping [For

data collection]

Theory of

Change

Matrix

Foresighting

Most

Significant

Change

Stakeholder Analysis

SWOT

Innovation Histories

Crowd Source

Maps

Visualizing

Net-Map Social

Network

Analysis

Mind

Mapping

Social Media Consultations

Priority

Setting

Action

Planning

Nominal

Group

Scenario

Planning

Stakeholder

Dialogues

Journaling

Observations

/ Visits

Venn Diagrams

Flow

Diagrams

Outcome

Mapping

Causal Process Training

(adapted from

presentation by

Hambly Odame,

2013)

• Social Network Analysis

• Understand who is involved & how they are connected

• Explore motivations, power, structure of network

• Participatory

• Diverse actors & vantage points requires everyone to get involved and have a stake in running the show

• Story/Experience

• More useful than numbers for understanding how and why things are the way they are, especially at Micro & Meso scales/timeframes

Boru Douthwaite

idrc.ca

• Ex-ante approach where stakeholders reflect on experiences

• Build innovation timeline , network maps, and learning histories

• Similar to case studies

• Used in situ: improving performance, ex situ: general strategies

• Beekeeping Extension in Vietnam:

• Chronicle the spread of hive designs, instruction methods, and subsequent innovations

• Map extension, project, community, and value-chain networks at various stages

• Gather stories of stakeholders

• Strengths: detailed profile, builds shared understanding

• Weaknesses: hindsight bias, lessons not immediately apparent

• Participatory tool for understanding social networks

• Easily adaptable to a wide array of situations and needs

• Key stakeholders map out connections between system actors

• Depending on purpose, aspects like motivation, influence, and strength of connections can be examined and plotted

• Used for planning, reflection, monitoring, evaluation

• Beekeeping Extension in Vietnam

• Map extension system (before, during, after, ideal)-who is talking to who?

• Map community networks-who is excluded from ‘learning space’?

• Strengths: wide application, easily used with other tools

• Weaknesses: requires strong facilitation skills, possible reluctance to share sensitive information

• Flexible alternative to traditional logic model

• Contribution to an outcome rather than claim attribution

• Guides intervention by focusing on actors, behavior, groups, and relationships

• Begins with participatory visioning exercise, then the paths to achieving the vision are plotted out

• Monitoring is built in to each step along the path

• What do we expect to ‘see’ at Stage X?

• Beekeeping Extension in Vietnam

• At beginning of project, subsequent projects by Vietnamese extension staff

• Strengths: adaptable, works with classic approaches

• Weaknesses: data collected by project team, unexpected outcomes

• Method for cooperatively managing change with diverse group of actors…think ‘coalition management’

• Four steps:

1. Engage for shared understanding of context and perspectives in group

2. Formalize group: agree on goals & roles, establish operational structure

3. Implement and evaluate: plan (outcome mapping), define success

4. Build further: learn from stage 3, adapt operational structure, solidify institutions

• Beekeeping Extension in Vietnam

• Layered dialogues with program team, ministry, universities, bee research center tied in with regional and local stakeholder dialogue groups

• Strengths: pool resources & expertise, address complex issues

• Weaknesses: time commitments, requires openness & understanding

• How can quantitative methods contribute to understanding

Agricultural Innovation Systems?

• Will it be easier to incorporate them at certain scales and timeframes?

• How can other fields use the ideas and principles of AIS?

• What can they take away? What are some areas AIS can learn from?

• What are some ethical concerns here?

fao.org fao.org

1. Hall, A., Dorai, K., & Kammili, T. (2012). Monitoring agricultural innovation system interventions. In: Agricultural innovation systems: an investment sourcebook. Washington, D.C.: World Bank.

2. Hall, A., Mytelka, L., & Oyeyinka, B. (2006). Concepts and guidelines for diagnostic assessments of agricultural innovation capacity UNU-MERIT, Maastricht Economic and Social Research and Training Centre on Innovation and Technology.

3. Assefa, A., Waters-Bayer, A., Fincham, R., & Mudahara, M. (2009). Comparison of frameworks for tudying grassroots innovation: Agricultural innovation systems (AIS) and agricultural knowledge and innovation systems (AKIS). Innovation Africa: Enriching Farmers Livelihoods, , 35-56.

4. Otis, G. (2013). Beekeeping extension in vietnam. Video: <http://www.youtube.com/watch?v=44vn_jonGVg>

5. Hambly Odame, H. (2012). Assessing innovation for prioritizing investment. In: Agricultural innovation systems: an investment sourcebook. Washington, D.C.: World Bank.

6. Hambly Odame, H., Hall, A., & Dorai, K. (2012). Assessing, prioritizing, monitoring, and evaluating agricultural innovation systems. In: Agricultural innovation systems: an investment sourcebook. Washington, D.C.: World Bank.

7. Schiffer, E. (2012). Using net-map to assess and improve agricultural innovation systems. In: Agricultural innovation systems: an investment sourcebook. Washington, D.C.: World Bank.

8. Douthwaite, B., & J. Ashby. (2005). Innovation histories: a method for learning from experience. ILAC Brief 7, CGIAR.

9. Kammili, T. (2011). A briefing paper on monitoring and evaluation practice for rural/agricultural innovation: how do you measure the impact of innovation initiatives? LINK Policy Resources on Rural Innovation, Hyderabad: Learning, Innovation, and Knowledge (LINK).

10. Kunkel, P., Gerlach, S., & Frieg, V. (2011). Stakeholder dialogues manuel. Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH www.collectiveleadership.com

Qualitative Techniques for Assessing Agricultural Innovation Systems by Steve LeGrand is licensed under aCreative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.