What kinds of ‘systems’ are we dealing with implications for system research and scaling by Dr. Cees Leeuwis & Seerp Wigboldus
1. What kinds of ‘systems’ are we dealing with?
Implications for systems research and scaling
International Conference on Integrated Systems Research, Ibadan March 3-6 2015
Cees Leeuwis & Seerp Wigboldus
Knowledge, Technology and Innovation group
2. We talk about different systems (nested)
Cropping systems
Livestock systems
Farming systems
Livelihood systems
Agricultural systems
Land-use systems
National systems
Global systems
Innovation systems
3. And we talk about systems (and how they
change) differently.
Systems seen as:
‘Machines’
‘Organisms’
‘Meanings’
‘Psychic prisons’
‘Arenas of struggle’
‘Rules’
Change strategy:
Optimise towards a goal
Re-balance and adapt
Dialogue, learning, agreement
Shock therapy
Coalition building, competition
Change incentives
6. ... mediated by human practices, and
associated with social outcomes ...
7. ... that are shaped by wider social conditions
and practices ....
8. ... that are again shaped by other bio-
material and social phenomena ...
9. So how do complex configurations change?
And what/how can research contribute?
10. So how do complex configurations change?
Key challenges for us:
There is no central steering and control
Farmers cannot change if others do not simultaneously
change
Disagreement and diverging interests
Actors experience uncertainty (a.o. about others)
There are always multiple simultaneous scaling processes
involved (intended and unintended)
11. Intensifying milk production:
Multiple scaling processes at farm-level
Milk production/cow
No. of dairy farms
Milk production/farm
Use of herbicides
Use of antibiotics
Use of growth
hormons
Manure production
Farmer income
Grassland
biodiversity
Automation of farm
management
Groundwater
quality
Education level
of farmer
Productive
life of cow
Methane gas
emission
No. cows
outside (field)
No. of pasture
birds
Cow fertility
12. ... and beyond farm level ...
Milk production/cow
No. of dairy farms
Milk production/farm
Use of herbicides
Use of antibiotics
Manure productionGrassland
biodiversity
Automation/hightech
in farm management
Education level
of farmer
Productive
life of cow
Methane gas
emission
No. cows
outside (field)
No. of pasture
birds
Cow fertility
Groundwater
quality
Diversification to
non-agrarian income
Societal concerns
re: animal welfare
Cost of business
acquisition
Rural
population
Cooperation
Collaboration
No. of potential wives
for farmers
Available
services
Image of dairy farm
amongDutch citizens
Specialisation
in subsectors/
nichemarket
13. In hindsight: what where the key triggers that
enabled to this re-configuration?
Guaranteed / subsidized prices (followed by quota)
Land-reform / land consolidation
Promotion of entrepreneurship identity/ideology
Cooperative, public and private service delivery (e.g.
credit, extension, veterinary)
Cooperative, public and private technology development
Driven by: Common vision, shared story and corporate
organisation and investment
14. I.e: a combination of individual, institutional and
technical leverages arising from shared purposes
‘Individual’ reasons for
behaviour (KAP++)
Formal and informal
institutions
Property / access rights
Market / pricing rules
Standards / certification
Organisational set-ups
Incentive systems
Procedures
Regulation / litigation
Patronage / clientilism
15. So what can systems research contribute?
(What is our ToC about the role of research?)
Integrative description/understanding of systems?
Identifying key areas of leverage?
Responsible experimentation with technical and
institutional options?
Becoming a leverage in its own right?
16. Integrative description/understanding of
systems?
Trying to understand the complexity
● Describe diversity
● Investigating dynamic interrelations between
variables / levels (modelling)
● Predict how scaling of one phenomenon relates to
scaling of other phenomena (trade-offs)
17. Integrative description/understanding of
systems?
Worries:
● notoriously difficult to integrate social aspects
● data intensive and time consuming
● hard to make contextual
● hard to link to contextual/stakeholder questions
● is detailed targeting really needed/efficient/possible?
18. Identifying key areas of leverage:
Opportunity, foresight and visioning
Analysing emerging
windows of opportunity
● Trend analysis: what
is already scaling up
or down?
● How / what could we
connect to that for
development
purposes?
19. Identifying key areas of leverage:
Addressing constraints
Analyse individual,
institutional, technological
constraints
● What are the key
barriers for scaling
best bet solutions?
● Which strategies and
leverages may
effectively address
such barriers?
20. Responsible experimentation with technical
and institutional options: Creating variation
Varieties
Land tenure contracts
Litigation platforms
Pricing systems
NRM surveillance
Transport modalities
Water governance
Weeding practices
Etc.
21. Responsible experimentation with technical
and institutional options: Creating variation
Evaluating forward looking scaling questions such as:
● Who is likely to benefit? How will risks be
distributed?
● What other impacts can we anticipate in the future?
● What is it we do not know?
● Who will take responsibility when things go wrong?
● What is the legitimacy basis for pursuing this
option?
22. Becoming a leverage in its own right?
None of these forms of research are likely to have much
impact in an isolated / extractive mode
● Not so much because users may not hear about the
results
● Not so much because we would be unable to
capture local knowledge and understanding
23. Becoming a leverage in its own right?
But because research processes have a greater potential
to contribute to impact than eventual research results!
● meeting, talking, bridging, sharing, working, fighting
Help to solve critical challenges at the level of the
configuration!
● No central steering, interdependence, disagreement,
uncertainty
Ex-post diffusion strategies do not deal with these
24. Becoming a leverage in its own right?
This process potential is why R4D / innovation platforms are
critical
25. This requires us to refine RBM, Impact
Pathways and Theories of Change
26. This requires us to refine RBM, Impact
Pathways and Theories of Change
Widen array of ‘research inputs’
● e.g. demand/agenda articulation, visioning, mediation
Widen array of ‘research outputs’
● e.g. new relationships, trust, visions, agreement,
coalitions
Widen array of ‘research outcomes’
● e.g. shifting pressures, discourses, institutional change
27. We may also consider different scaling
pathways
‘Go with the flow’
● connect to what is already scaling / ongoing
● societal experimentation with multiple options to
enhance the chances of a fit
● foster reflection on responsible innovation questions
28. We may also consider different scaling
pathways
‘Overthrow the system’ (system innovation)
● emphasis on vision and coalition building
● focus on identifying leverages – individual,
institutional, technical
● societal experimentation with multiple issues to
create leverage (an enabling environment)
29. ‘Going with the flow’ vs ‘Overthrowing the
system’ require different process strategies