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Week 4: Social Innovation at the Macro-Level - Systems Thinking for Social…
Week 4: Social Innovation at the Macro-Level - Systems Thinking for Social Innovation
Part 1: Social Innovation Ecosystem
Definition
“A social innovation ecosystem refers to the
evolving set of actors, activities, and artifacts, and the institutions and relations
that are important for the innovation to create social or environmental impact.”
The notion of social innovation ecosystem is based on the concept of innovation ecosystems
The idea of ecosystem goes back to the idea of ecology that conceptualizes the
flow of material and energy
(but ecosystem innovation has nothing to do with organisms in the environment)
A system is composed of a set E of elements and a set R of relations
Objectives
An understanding of the wider ecosystem
helps to identify
the following
Enablers of social innovation
Barriers to social innovation
The unintended consequences of social innovation (‘if the social innovation changes what it intends to change, what other effects will that have?’)
MPESA as an example of a social innovation ecosystem
Once customers have signed up, they pay money into the system by handing cash to one of Safaricom’s 40,000 agents (typically in a corner shop selling airtime), who credits the money to their MPESA account
Customers withdraw money by visiting another agent, who checks that customers have sufficient funds before debiting the account and handing over the cash
Customers can also transfer money to others using a menu on their phone - cash can thus be sent from one place to another more quickly, safely and easily than taking bundles of money in person
MPESA is a
mobile money platform provider
. Mobile money is a service that allows monetary value to be stored on a mobile phone and sent to other users via text messages
Key Elements
Large unbanked population, city workers and relatives in rural areas, British commonwealth (DFID), Vodafone, Safaricom, local authorized agents, Kenyan banks, ....
Relations
Vodafone received funding from the British commonwealth, people working in the cities used to send money to relatives in rural areas, Safaricom had an already established relation and network of around 40,000 agents across the country, ...
Purpose and people first; profits will follow
An understanding of the wider ecosystem helps to identify and analyze the following
Enablers of social innovation
: Understanding the wider ecosystem, so the different elements and how they relate, explains why MPESA was so successful in Kenya
MPESA has had a huge social impact by promoting financial inclusion especially among individuals who previously lacked access to formal banking services by extending financial services to rural and remote areas where traditional banking infrastructure is limited
Barriers to social innovation
: Understanding the wider ecosystem explains why MPESA was less successful in Tanzania
• Less pressing need in Tanzania because smaller parts of the consumers were ‘unbanked’
• Cautious regulatory environment in Tanzania (while the Kenyan one was very supportive)
• Small, concentrated agent network (whereas MPESA lived off a large distributed network of agents to make it accessible across rural areas in Kenya)
The
unintended consequences
of social innovation: A recent study suggests that, to a certain extent, MPESA changed some of the social cohesion dynamics between children working in the city and relatives in rural areas, as sending money is easier than travelling home (from cities to rural areas)
Part 2: Systems Thinking
Definition
An
interconnected set of elements
that is
coherently organized
in a way that
achieves something
(a function or purpose)
Framework
for
seeing connections and interrelationships
rather than just things, and for
seeing patterns
rather than isolated events
Systems thinking demands a deeper understanding of the behaviour of systems and acknowledges the relationship between interacting components
Means understanding how systems are interconnected & understanding their dynamic
Systems thinking is
nonlinear
: cause and effect are not necessarily linked with simple step by step chains
Decisions or actions at one point have an impact on another component within the system
Reacting to a problem in one part of the system may have unintended consequences on other components or the process as a whole
About assessing the degree of system complexity, analyzing system dynamics and making decisions that reduce the risk of negative outcomes
E.g. Blind men and the elephant
The principles of Systems Thinking ("Mindset")
Moving from parts to wholes
Means recognizing that
systems are made up of interconnected parts that when put together create a complex whole
Systems consist of
elements that, as a whole, achieve a certain function
; the parts themselves do not
E.g. Electricity systems
Moving from linearity to circularity
Challenges the assumption of linear thinking which often assumes a straightforward cause-and-effect relationship, where a single cause leads to a predictable effect
Helps to explain why it is so difficult to change systems as linear approaches usually focus on what is visible while ignoring the
underlying complex reality
Example MPESA
What we see
: Actors saw that MPESA worked in Kenya
Linear Approach
: Actors assumed that MPESA could, in a linear approach, be transferred to Tanzania successfully
Complex Reality
: Moving from linearity to circularity helps to understand the complex system of elements and relationships that prevents MPESA from being successful in Tanzania
Moving from silos to emergence
Means recognizing that much of today’s problem-solving happens in isolated and independent components within its own boundaries without much interaction with others
Systems Mapping (Tool)
Purpose:
Visualization of the different elements
of a system as well as the
relationships between these elements
Functions:
Help to describe and diagnose the current state of a given system
Allow to discuss a system with others
Helps to decide where a social innovation could best intervene in the system (intervention points)
5R Model
Results
What is or should be the target result that defines the system?
Resources
What resources are currently being used by the system in producing the result?
Are there necessary resources that are missing or are insufficient?
Rules
What rules affect the way the system functions?
Roles/Actors
What roles are actors currently performing within the system?
Relationships
How do these different roles/actors relate?
4 Common Pitfalls
Full Picture vs. Relevant Story
Requires you to focus on the key elements of a system which contribute to your chosen results
Your model vs. The System
Keep your new ideas and interventions for change out of the system and instead focus on mapping what is currently happening and the current results
All Bad vs. Appreciative Stance
If you only look at what you think is not working in the system, you will miss the things that are, the people and organisations who benefit from it, and possibly things that might get in the way if you wanted to make a shift
Only map relevant elements
Characteristics of Systems
(Complex Systems)
Self organisation:
the capacity to create new, ordered structures or patterns out of disorder. There is continual re-organisation based on feedback from the environment
Emergence:
the presence of a new behavior, pattern or structure that results from the interactions between the elements of the system
Hierarchy:
notion that systems evolve from bottom up - from simple to complex. As the system grows, subsystems emerge
Resilience:
ability of a system to recover and adapt following a disruption