The Role of Knowledge Management in Agricultural Innovation Systems (AIS) by Martina Spisiakova, Knowledge Management Coordinator, Asia Pacific Association of Agricultural Research Institutions (APAARI)

1. Mar$na Spisiakova, Knowledge Management Coordinator
Asia Pacific Associa$on of Agricultural Research Ins$tu$ons (APAARI)
17 August 2020
The Role of Knowledge Management in Agricultural
Innova$on Systems (AIS)

2. Content of this Presentation
• Introduc1on
• Key KM Concepts
• Research-prac1ce gap: Key issues
• KM in Agricultural Innova1on System (AIS) perspec1ve
• Capacity Development for Agricultural Innova1on System (CD for AIS)
• KM for strengthened AIS – Key principles

3. Introduction:
Why share knowledge? Why innovate?
• Globaliza1on, climate change, environmental degrada1on, migra1on,
spread of diseases and pandemics, conflict
• Good prac1ces are quickly becoming obsolete
• Making sustainable impact on the agri-food sector and poverty
reduc1on requires the capacity to implement proven prac1ces and
respond to new challenges and opportuni1es – ABILITY TO INNOVATE
• The complexity and diversity of agri-food systems call for improved
solu1ons to problems to achieve the SDGs

4. Introduction: KM and Innovation
• KM and innova1on are two mutually suppor$ng processes
• KM processes are the channels for capturing, documen1ng, dissemina1ng, adop1on,
replica1ng and scaling up of innova1on and its integra1on into policies
• KM is a key ingredient of innova$on as it feeds ideas into the innova1on processes
• KM focuses on learning from good prac1ces, research/science, experiences
• Innova$on focuses on experimenta$on and crea$on of the good prac1ces of tomorrow
• Innova1on oRen a higher-risk, but KM encourages harmoniza$on around proven
prac1ces
• KM thrives on communi1es marked by commonali1es, but innova1on thrives on
diversity, crossing boundaries and ques1oning established knowledge
• INTEGRATION OF BOTH IS CRITICAL so that they feed into each other

5. Main concepts: Data
• Qualitative and quantitative
collection of numbers, characters,
images or other outputs
• The lowest level of abstraction
from which information and then
knowledge are derived

6. Main Concepts: Information
• Facts provided or learned about something or someone: a
vital piece of information (The Oxford Dictionary of English)
• Used to generate knowledge…
About 89 percent of the total Iranian agricultural products in the
last 5 years have come from the irrigated land
(FAO, country profile or Iran (Islamic Republic of)
http://www.fao.org/3/ca0339en/CA0339EN.pdf)

7. Main concepts – Knowledge
• Knowledge is what you know…
• Experience, insights, skills, concepts, ideas, ways of thinking
and working
• Intangible – difficult to measure
Despite increasing water scarcity in Iran and advanced
technology use, irrigation water use is still inefficient.
Why? What can be done to address it?

8. Iceberg Metaphor taken from http://ro.wikipedia.org/wiki/Fi%C8%99ier:KM_iceberg.png
Main concepts –
Tacit versus explicit knowledge

9. Main Concepts – KM Defini$on
• An integrated, systema1c approach to
iden1fying, managing and sharing an
organiza1on's knowledge, and
enabling groups of people to create
new knowledge collec1vely in order to
achieve the objec1ves of the
organiza1on (UN)
• The crea1on, organisa1on, sharing and
use of knowledge for development
results (UNDP)

10. KM Defini$on by Peter Senge
Author of the book: The FiRh Discipline: The Art and Prac1ce of the Learning Organiza1on

11. Main concepts –
KM Cycle and its Main Pillars
• KM Processes
• KM Tools
• KM Infrastructure
• KM Strategy
• KM Culture
Knowledge Management Cycle
Dalkir, 2005

12. Main concepts –
Innovation
Agricultural innovation is the process whereby individuals or
organizations bring new or existing products, processes or
ways of organization into use for the first time in a specific
context, to increase effectiveness, competitiveness and
resilience with the goal of solving a problem.
(Source: FAO)

13. Key KM/Innova$on challenges
1. Availability of skilled human resources and
exper$se (e.g. ICT, KM generally)
2. Lack of coordina$on between research,
educa$on and extension
3. Understanding target group for KM ac1vi1es
4. Capturing and dissemina$ng lessons learned
and good prac$ces
5. Collec$on, compila$on, and analysis of data in
real $me to generate knowledge
6. Documenta$on of research findings
7. Insufficient funding for effec1ve infrastructure
(internet services, KM soRware and tools)
8. Unavailability of fast band width and access to
ICT among farmers and fishers
9. Insufficient funding for KM
10. Lack of centralized ins1tu1onal repository for
file sharing
11. Ins$tu$onal support for KM
12. Embedded org. culture and prac$ces
13. Poor response by collabora1ng partners
14. Lack of $me for appropriate review, edi$ng
and produc$on of knowledge products
15. Keeping abreast with fast emerging systems
16. Collec$ng right informa$on
17. Insufficient $me for KM/overlapping
priori$es
18. Understanding which communica$on
channels are most effec$ve

14. Research-Practice Gap – Key Issues
• The linear technology transfer process
(generated by research and passed on to the
extension system for adop1on by farmers) has
failed in tackling contemporary agricultural
development problems and complexity
• The lack of a close working relationship
between national agricultural research and
extension organizations, and with different
farmers and farm organizations, is one of the
most difficult institutional problems confronting
many developing nations
Source: h*ps://www.researchgate.net/figure/
Visualized-Ac<on-Research-process-used-in-
the-farmers-mee<ng_fig4_238792891

15. Researchers/Scien$sts:
• Focus on the technical aspects for
genera1ng useful technologies.
• Complain prac11oners ignore them.
• Claim that even if research is used,
prac11oners do it wrong!
• Speak technical language.
Development Prac$$oners:
• Focus on the acceptance & adop1on of those
technologies by users.
• Complain research is irrelevant & imprac1cal.
• Claim that even if relevant, research is not in
any form that can be readily translated into
prac1ce!
• Speak simple language.
Research-Practice Gap – Key Issues

16. • Technical training, technologies – VERY
IMPORTANT, but NOT ENOUGH
• FARMERS are responsible for implementa1on of
produc1on changes and accountable for their
success
• ORen, highly technical projects and training are
“missing out” on the human aspects that speed up
technology applica1on
• These human aspects are measured in sod skills –
func$onal capaci$es
• Sod-skill training that matches industry needs – a
major determinant of project/ins1tu1onal success 16
Research-Practice Gap – Key Issues

17. Agricultural Innova$on System (AIS)
• Tropical Agriculture Plagorm (TAP) hosted by FAO
• Agricultural innova$on system is a complex network of actors
(individuals, organiza$ons and enterprises), together suppor$ng
ins$tu$ons and policies that bring exis$ng or new agricultural
products, processes and prac$ces into social and economic use.
Source: Tropical Agriculture PlaJorm (TAP) – Common Framework on Capacity
Development for Agricultural Innova<on Systems (CD for AIS)

18. KM in the context of AIS: System thinking
Source: Common Framework on Capacity Development for Agricultural Innova<on Systems – Conceptual background, CABI

19. KM in the context of AIS –
Conceptual diagram
Source: Common Framework on Capacity Development for Agricultural Innova<on Systems – Conceptual background, CABI

20. An integrated framework of behavioural factors affec$ng farmers’ adop$on
of environmentally sustainable prac$ces
20 Source: https://academic.oup.com/erae/article/46/3/417/5499186

21. Analysis of farmers’ behaviour, based on two case studies in Bolivia shows that:
• KM modali$es affect innova$on behaviour among small farmers
• Schemes, which involve mul$ple agents, can influence farmers’ ajtudes
towards innova$on and adop$on
• The extent to which farmers adopt innova$ons is determined by the degree to
which they are embedded in social networks
• Farmers evaluate poten1al benefits and costs of innova1ons on the basis of
opinions of other farmers, and agents offering knowledge about innova1on
• Technology adop1on amongst smallholders in developing countries, requires
developing farmers’ capabili1es and communica1ng the learning process to a
variety of actors
(Source: h*ps://agris.fao.org/agris-search/search.do?recordID=GB2013203352)
KM for agricultural innovation: lessons from
networking efforts in the Bolivian Agricultural
Technology System

22. TAP Common Framework on
Capacity Development
for Agricultural Innova$on Systems (AIS)
• Focus on func$onal capaci$es (sod or
people skills) – ajtudes, communica1on,
crea1ve and cri1cal thinking, work ethic,
teamwork, networking, decision making,
mo1va1on, flexibility, problem solving –
akributes one needs to achieve their goals
and effec1vely put technical skills in use

23. The Common Framework iden1fies 4 + 1 key capaci$es for AIS to perform effec1vely.
These apply to all three dimensions of CD..
Capacity Development for AIS:
Functional capacities
Source: h*ps://tapipedia.org/framework/4-1-capaci<es

24. Capacity Development:
Focus on Facilitation of Engagement

25. • All KM as part of a larger KM/learning strategy of an organiza1on
• The KM processes/approaches need to consider characteris1cs of how
adults learn best – guiding par1cipants to their own knowledge rather
than supplying them with facts; connec1ng learning to par1cipants’
experience and knowledge base; providing opportuni1es for everyone to
interact; using methods that support knowledge sharing
• All KM ini1a1ves should also aim at strengthening rela$onships and
networks as it helps get things done, get right informa1on, learn about a
new way to tackle a challenge, link with the person who has the know-
how; understand where the linkages are strong or weak to help focus
knowledge-sharing efforts
KM for Strengthened AIS – Key Principles

26. KM strategy needs to integrate:
• capturing and dissemina$on of knowledge to learn from lessons and good
prac1ces; replicate and ins1tu1onalize innova1ve prac1ces; and avoid
duplica1ng past mistakes
• genera$on and sharing of knowledge to document successful prac1ces and
lessons learned to improve future ac1vi1es; facilitate beker processes of
reflec1on, which can draw out tacit knowledge and generate new knowledge
• explora$on of a problem and iden$fica$on of op$ons to solve it – many
issues, including, many stakeholders
• strengthening and sustaining KM by integra1ng KM in organiza1ons’
business processes, promo1ng a culture of knowledge sharing
KM for Strengthened AIS –Key Principles

27. • Development of KM and learning systems in a way that become part of the
“way of doing business” – integra1ng KM processes to every stage of the
project cycle, training and ac1vity, administra1on and management level
• Different ways of working, rather than add on!
• More focus on cri$cal reflec$on and collec$ve learning that leads to learning
how to innovate and adapt in response to changing social and environmental
condi1ons
• Ques$oning and analysing experiences, observa1ons, theories, beliefs,
assump1ons, things that are normally taken for granted – What did not work or
is not working? Why? What are the implica1ons? What do we do next?
• System analysis – a problem-solving methodology to iden1fy linkage problems
KM for Strengthened AIS: Key Principles

28. KM for Strengthened AIS: Key Principles
• Crucial role of KM: facilita1on, reflec1on, learning, documenta1on,
enabling agricultural innova1on
• Facilita$on: Beyond ‘conven1onal’ facilita1on tasks (one-way
communica1on with trainees and other stakeholders, informa1on sharing,
PPTs, and/or managing logis1cs) to bring more interac1on, par1cipa1on
and engagement
• Fostering synergies that link people and resources, enhancing their ability
to make collec1ve decision, ensure strong implementa1on, and influence
change
• All actors become poten1al sources of knowledge and change

29. i) Scale up and out of successful agricultural prac1ces
and innova1ons to improve produc1vity,
environment, food security and reduce poverty
ii) Akract investment in key areas of agri-food research
and innova1on systems
iii) Build trust that empower policy/decision makers to
design improved policies, and other stakeholders to
take collec1on ac1on
iv) Avoid duplica1on of efforts speeding up learning and
knowledge transfer to benefit the society
Why KM for AIS?

30. • Fundamentals of Knowledge Management (self-
study course):
hkps://www.unssc.org/courses/fundamentals-
knowledge-management-self-study-course/
• KM Toolkit: hkp://www.kstoolkit.org/
• Introducing Knowledge Sharing Methods and Tools
– a facilitator’s guide
hkps://usaidlearninglab.org/library/introducing-
knowledge-sharing-methods-and-tools-facilitators-
guide-0
• TAP Common Framework on Capacity Development
for Agricultural Innova$on Systems
hkps://www.tapipedia.org/content/tap-framework
KM resources

31. THANK YOU!