1. The way aid works
The way the world works
The way aid could work

3. adapted to local conditions...”
“…the smallpox eradication effort evolved over time in response to the practical realities in the field, the development of new approaches through research, the active involvement of local leadership and peoples, and imaginative quality control measures and supervision. It developed different approaches and strategies
adapted to local conditions...”
DON HENDERSON, DIRECTOR OF SMALLPOX CAMPAIGN
How was this achieved? By breaking every rule in the WHO book.

4. Development and humanitarian aid efforts are dominated by certain mental models
The machine metaphor - universe as Newtonian clockwork, Taylorist scientific management principles rule
The future is knowable given enough data
Development and disaster recovery broken down to simple cause-and-effect relationships
Breaking down parts would reveal how the whole system worked
Aid is the search for the search for the right
Evidence of which can be found throughout strategic, learning, performance and organisational frameworks
“…We commonly think of the economy, the natural resource systems we are exploiting, and societies in general as machines that are analogous, essentially, to a windup clock.
Each can be analyzed into parts, with the relations between those parts precisely understood, and each is believed to be nothing more than the sum total of its parts.
As a result, we believe we can predict and often precisely manage the behaviour of these systems...”
The role of aid researchers, managers & leaders is to predict and control - increasing levels of control (over nature, over people, over things) would improve processes, organisations, quality of life, entire human societies

5. Cognitive and operational biases in aid
Systems
Relations
‘…where machines work well. Such approaches would be ideal where there is a straightforward task to perform, a stable context and operating environment, identical, duplicable products, and compliant, predictable and reliable parts – which includes the human ‘components’...”
Behaviours
Dynamics
GARETH MORGAN IMAGES OF ORGANIZATION

6. “…All malaria programmes were obliged to adhere rigidly to a highly detailed, standardised manual of operations. It mandated identical job descriptions in every country and prescribed specific charts to be displayed on each office wall at each administrative level. The programme was conceived and executed as a military operation to be conducted in an identical manner whatever the battlefield... the premise of the programme was that the needed knowledge and technology was available and that success depended solely on meticulous attention to implementation detail. Research was considered unnecessary and was effectively suspended from the launch of the programme…”
“…The tendency to think in terms of silver bullets to attack malaria has been a constant feature over the past 40 years. In 1969, the Pearson Commission confidently pronounced the disease ‘virtually eliminated’. How, then, did the situation reported in 2010 come about? ‘ [The 1960s eradication campaign] was far too monodimensional, relied too much on DDT
[insecticide] spraying, and neglected the palpable problem that the delivery infrastructure was not in place
in too many parts of the malarious world. The emergence of widespread
mosquito resistance to DDT, and parasite resistance to the cheap mainstay of therapy compounded the difficulties.’
In short, the narrowness of the response allowed the mosquito to become
resistant. The silver bullet problem has, unfortunately, also proved resilient.
As clinical microbiologists Richard Carter and Kamini Mendis see it, for the
most part, the types of tools available and used for malaria control today are the
same as those during the ‘virtual elimination’ era.60
This point does need some nuancing. There was one approved insecticide
during the first eradication effort; there are now a dozen. And the use of treated
nets—which weren’t around in the 1960s—has been responsible for a large
decline in malaria incidence in some countries. However, even in these countries,
there is growing acknowledgement of the need for a better combination of
responses if progress is to be made....”

7. “...The Newtonian model is staggering about the global stage like a mortally wounded Shakespearean actor...”
Rather less portentously, Duncan Watt’s quip

8. The way aid works
The way the world works
The way aid could work

9. The problems we face in science and policy
Organised simplicity
Disorganised complexity
Organised complexity

10. The world is rife with ‘complex adaptive systems’
Many interacting agents and organizations of agents
Adaptive
Designs and strategies evolve over time
System
Macro patterns emerge from micro behavior

11. Complexity science helps development scientists better understand systems, networks, behaviours and dynamics
Emergent systems
Adaptive behaviours
Diverse networks
Dynamic change

12. (Compare to the institutionalised operating assumptions of aid)
Systems
Relations
Behaviours
Dynamics
GARETH MORGAN IMAGES OF ORGANIZATION

13. The way aid works
The way the world works
The way aid could work

14. Systems thinking approach to malaria reduction (IWMI)
Holistic management of anti-desertification programmes in Zimbabwe (Operation Hope)
System dynamics in conflict (UWM)
Social ecological systems (Indiana)
BEHAVIOURS
Agent-based modelling in agriculture (French Development Agency)
Agent-based models of national political economy (World Bank)
Evolutionary approaches to dealing with malnutrition (Save the Children)
Problem-driven iterative adaptation (Harvard, Bank)
NETWORKS
Complexity, networks and growth (Harvard Center for International Development)
Social network analysis of disaster responses (Red Cross)
Global economic fragility (IMF)
Irrigation and water temple networks in Bali (Santa Fe)
DYNAMICS
Non-linear epidemiology (Sahel)
Emergent education (NIIT, IFC)
Mhealth approaches in Africa
Scaling up health interventions (Future Health Systems Consortium)
There are growing numbers of applications of these ideas across the system and in parallel systems

15. Network analysis: from atomised actors with formal relations to informal, social cliques and groups

16. Case study: Atlas of Economic Complexity
A network-based approach to economic development
Networks of productive knowledge condition and shape the development of nations
The structure of network explains growth and stagnation
Best predictor of national growth available

17. The product space

18. Ghana vs Malaysia

19. Ghana vs Malaysia

20. What complexity research brings
Distribution
Systems
Behaviours
Relations
Dynamics
Organized simplicity
Organised complexity
Disorganised complexity
Systems are open, dynamic, interconnected and interdependent. Macro patterns emerge from micro behaviors and interactions
Humans are adaptive tinkerers;
subject to
errors and biases; self-organize
and co-evolve with system and each other
Relationships, networks, flows, ties, values, beliefs are vital. Are path dependent and historical
Change is non-linear, unpredictable, with phase transitions, characterized by power laws and discontinuities
What complexity research brings

21. What complex systems research brings to development sciences
Behaviours
Relations
Dynamics
Sciences of simplicity
Systems and problems are closed, static, linear systems; reductionist
Individuals use rational
deduction; behaviour and action can be specified from top-down
Actors can be treated as independent and
atomized
Change is direct result of actions; proportional, additive and predictable
What sciences of complexity bring
Systems are open, dynamic, interconnected and interdependent. Macro patterns emerge from micro behaviors and interactions
Humans are adaptive tinkerers;
subject to
errors and biases; self-organize
and co-evolve with system and each other
Relationships, flows, ties, values, beliefs are vital. Are path dependent and historical
Change is non-linear, unpredictable, with phase transitions, characterized by power laws and discontinuities

22. Closing thoughts

23. ‘We cannot solve problems by using the same kind of thinking
we used when we created them.’
ALBERT EINSTEIN

25. Thank you!