Innovation, Complexity and the Sustainable Development Goals

The Sustainable Development Goals (SDGs), are a set of 17 central goals and 169 targets which make up the 2030 Agenda for Sustainable Development. This Agenda was set by 193 nations and adopted at the UN General Assembly in 2015.  It is an agenda of unprecedented scope and significance which aims to end poverty, fight inequality and injustice, and tackle climate change by the year 2030.  The recent report Global Warming of 1.5°C from the UN Intergovernmental Panel on Climate Change (IPCC) underscores just how urgent this is.

While Agenda 2030 is purposely transformative and ambitious, signatory nations across the world are now challenged to develop serious action plans to adequately address climate change and implement the SDGs.  While the national policies of the United States are turning away from Agenda 2030, other nations, especially in Scandinavia, are getting serious.  These nations recognize the significant, global and even existential risks of not realizing Agenda 2030.  They also recognize that addressing the SDGs offers many potential opportunities for business, which will need to be a critical partner, in addition to government and civil society.  Therefore, many efforts are now focused on building new and innovative partnerships to address the SDGs.  One recent example of such an effort is P4G funded by Denmark and joined by several other partner countries, leading companies and organizations including the Global Green Growth Institute, C40 Cities, the World Economic Forum and the World Resources Institute.

Good will alone, however, will not be enough to realize Agenda 2030.  Because the SDGs are dynamic and intricately interrelated, a holistic, complexity-aware approach is needed to implement and measure efforts to attain them.  Linear solutions will not be adequate for the exponential challenges which the SDGs are attempting to address.  Neither will it be adequate to focus on the goals in isolation because they are interlinked across different economic sectors and policy domains.  Even small goal-by-goal efforts run the risk of having unintended spill-over effects. Ignoring (or perhaps not even realizing) these serious consequences could be detrimental downstream.  For example, as illustrated in A Guide to SDG Interactions: From Science to Implementation by the International Science Council, a singular focus on SDG 2, End Hunger, could have negative interactions with SDG 3, 7 , 13 and 15 because of the target to increase agricultural productivity.  Unless sustainable practices are used, an increase in agricultural productivity will have an influence on land use, soil and water quality and important ecosystems.  A decrease in soil and water quality will ultimately affect human health (SDG 3). Agricultural production also contributes greatly to greenhouse gas emissions affecting climate change (SDG 13).  Efforts to curb deforestation (SDG 15) and agricultural productivity (SDG 2) may therefore have negative interactions exacerbated by the demand for biofuels for clean energy (SDG7).  Therefore, a careful examination tracing the interlinkages between the SDGs and efforts to attain them is needed to counteract potential trade-offs.  It will require whole systems thinking.

Most of us have gone through educational systems which have not trained us to think in systems, but rather followed linear, cause-and-effect thinking based on the scientific method.  Methodologies coming out of design-thinking, system-thinking and the complexity sciences, therefore, can be helpful because of their holistic, non-linear approach which is also better at capturing dynamic, evolving situations.  These methodologies often use a lot of visual tools which can be very helpful to facilitate and depict our understandings of complex situations and systems of interest.

Many recognize that addressing Agenda 2030 will require a great deal of innovation.  We need to push boundaries and transcend many of the business, social, educational and political structures that are currently limiting innovation and risk-taking at the scale now needed. We need to think in different ways and draw from creative and perhaps even disruptive approaches.  These are some of the reasons why interdisciplinary and cross-sectoral approaches are needed.   Collaboration and co-creation across untraditional boundaries will foster innovation and creativity.  However, an iterative and adaptive approach will be necessary to experiment with, gather feedback on and adjust these efforts.  We must develop a mindset that is continually in learning mode and provide the time needed to learn and process new knowledge.

It is time to embrace the complexity of the SDGs because addressing them will finally force us to recognize how deeply intertwined our natural, social and economic systems are and, subsequently, the importance of system-wide efforts.  Only by appreciating this complexity do we have a chance at realizing Agenda 2030 and perhaps even saving humankind.  It is not too late, but it is more urgent than ever...

Participatory Network Analysis

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Social network analysis is often criticized for being too static, too far removed from the actors involved and too dependent on expert driven analysis.  Often the participants involved in a social network analysis data collection effort never get to see the final outcome.

Participatory network analysis, on the other hand, is a highly participatory approach to mapping out the actors, types of linkages and their level of influence on a problem or situation which you and your team are facing.  It is a workshop type approach which is highly visual using paper, markers, colorful sticky notes and a skilled facilitator.  The map which is produced in the end represents the collective understanding of the situation of interest of those involved and therefore it is important to involve stakeholders who may have different perspectives.  The final map produced may also be digitized and there is very user-friendly software developed for this purpose.  Digitizing the maps also deals with the problem of these maps being too static because they can be easily updated as actors change and new linkages are developed.

So, why would you want to engage your team or collaborators in a participatory network analysis exercise?  There could be many reasons including:

·         To understand better a situation you are involved in or which needs improvement to help guide your efforts before you commit too many resources;

·         To get a full picture of all of the actors (individuals or larger entities) who influence the issue or situation at stake;

·         To help you and your team uncover the hidden drivers that propel or hold you back from achieving your goals;

·         To help you and your team better plan and leverage both your formal and informal influence network.

We are about to embark upon a new year with much uncertainty and a rapidly changing landscape. It could be critical for your operations and your team to take out a little time to map out the situation you are facing.  It is usually always a very enlightening experience as the discussions unfold and the map takes shape.  Our individual cognitive abilities do not allow us to picture in a snapshot the many nodes and connections of our networks of interest and it is therefore extremely helpful to visualize this on paper.   When done in collaboration with others, new insights are always revealed and a more complete picture emerges.   

If you are interested in learning more or need a facilitator to help guide you and your team and collaborators through this highly interactive exercise, do not hesitate to contact Kirsten Collins, principal of AdaptivePurpose (www.adaptivepurpose.org) at kbcollins@adaptivepurpose.org.  Kirsten is a certified systems practitioner and evaluation consultant with over 15 years of experience working with a variety of clients including non-profits, NGOs and government.

Comparing Lean Startup and Systems Thinking Frameworks

Systems thinking exists as a way of reevaluating problems in order to create new and effective solutions. Instead of only concentrating on cause-and-effect relationships between actors, it focuses on relationships, boundaries, and feedback to put more emphasis on the wider picture. The breadth of the systems framework is one of its greatest strengths, as systems thinking is used in both the non-profit and for-profit sectors, especially when the problem at hand is complex. Surprisingly, its adoption to date has been limited. This is in part a result of the change-resistant nature of organizations as a whole, but it is also because systems thinking has limited exposure outside of academic circles. However, select elements of systems thinking have been cherry-picked and applied in practice. Specifically, the lean startup method emphasizes some aspects of the systems framework while ignoring others entirely.

The traditional business model often starts with a five-year plan, an initial forecast of the market, cash flows, and risk. Underlying this plan is the assumption that all of these categories can be anticipated and projected for years into the future. Unfortunately, consumer feedback has no place in this model. In fact, customer reactions are only known with any certainty after large amounts of funding and development have already been poured into a project. Lean startups are different precisely because they use feedback as a tool for developing adaptive business models. At the core of the lean startup method is the minimum viable product, or MVP. These are in a sense prototypes developed with customer input that aim to test the market in order to determine demand. Ideally, the prototypes continue to evolve and are improved at each iteration so that when significant resources are finally invested into the product, the end result will have a much higher chance of success.

Although lean startups are not explicitly systems aware in that for the most part they do not claim to take a systemic approach to product development, their underlying philosophy tells a somewhat different story. Their commitment to customer input evokes the feedback loops found in systems thinking, and the rapid prototyping used in developing MVPs to test the market is similar to the systemic approach to defining boundaries. After all, defining the consumer and the scope of the product is a less theoretical way of determining the actors and boundaries involved in any given system.

However, it is important to recognize that in spite of their similarities the lean startup method is not just applied systems thinking. While lean startups are “aware”, in the sense that they seek to integrate consumer responses with their products, they do not show the same commitment to understanding relationships that characterizes systemic approaches. Evaluating the market and adapting to it are vital to startups interested in using lean methods, but a detailed understanding of the connections between sources of capital or within the general system that they operate in is not. Ultimately, it is important to understand that systems thinking and lean startups rely on compatible frameworks that overlap in some areas but diverge in others.

References:

Ackoff, Russell L. "Why Few Organizations Adopt Systems Thinking." Syst. Res. Systems Research and Behavioral Science 23.5 (2006): 705-08. Wiley Online Library. Web. June 2016.

Blank, Steve. "Why the Lean Start-Up Changes Everything." Harvard Business Review. Harvard Business Publishing, 01 May 2013. Web. 7 July 2016.

Are you Using Systematic or System(ic) Thinking?

Systematic and system(ic) thinking form the basis of two different approaches to problem solving.  System(ic) thinking is concerned with examining the ‘whole’ of a system of interest, while systematic thinking focuses on the parts using a step-by-step, methodical approach.  There is now growing recognition that system(ic) thinking is needed to better address the complex, interrelated, social and environmental challenges we will continue to face in the 21st century.  However, system(ic) thinking capabilities are weak in the west (1)  Why is this? And how can we best combine systematic and system(ic) thinking to develop the solutions our complex global issues? 

Although many of us may have some intuitive appreciation of system(ic) thinking, it is quite weak for many in the west.  This is likely due to the dominance of the ‘Newtonian’, ‘reductionist’ and individualist paradigm in the west, which has shaped our thinking in many ways and influenced how we have structured our society.  The western tradition of schooling has mostly taught us to think systematically, using an orderly, step-by-step approach as dictated by the scientific method.  This is premised on the view that the ‘whole’ of a phenomenon is best understood by examining it parts.  This is good for in depth understanding of the properties of individual elements, and the determination of linear, cause-and-effect relationships.  To understand the ‘whole’ that emerges from the interactions between the individual elements, however, requires system(ic) thinking.    

To build capacity in system(ic) thinking, it could be helpful to raise awareness of the differences between system(ic) and systematic thinking and to recognize that these two approaches need not be mutually exclusive.  Combining systematic with system(ic) thinking, indeed, could be very powerful if done in the right way.

So, how can we best combine system(ic) thinking with the dominant, systematic and linear frameworks (logical frameworks, budgets, performance assessments, etc.) that structure most of our planning, management and evaluation processes? How do we incorporate the complexity of our operational contexts which these frameworks fail to capture?  Can we develop processes to allow for the reflection and learning which system(ic) thinking can facilitate?  What are useful methods and tools? These are questions AdaptivePurpose is exploring with partners and clients and through the emerging community of practice “Complexity&Praxis” which AdaptivePurpose is helping establish. We will have more blog posts on our activities and capacity-building we are doing to help social and environmental change makers build their system(ic) thinking capabilities.

[1] This essay is inspired by and drawn from Ray Ison’s writings for the course TU812 “Managing Systemic Change” at the Open University, UK.  See reference below.

References:

Ison, R. (2010). Systems Practice: How to Act in a Climate-Change World.  The Open University. London, Springer.

What is the Purpose of Feedback?

What is the Purpose of Feedback?

Representing AdaptivePurpose, I attended Feedback Summit 2015 last week held at the Open Gov Hub in Washington DC.  We spent two days discussing feedback and hearing from various organizations on how they are collecting feedback from their stakeholders, beneficiaries, and citizens (the term to be used was a whole other debate).   Everyone there agreed on the importance of collecting feedback and that we need to do a better job across all sectors collecting feedback from those who are impacted by programming interventions.  This seems difficult to argue against, and it certainly seemed obvious to me as an evaluator because collecting feedback is what I do.  It isn’t enough, though, just to collect feedback. What matters is what you do with this feedback? And anyway, what exactly IS feedback in the first place?  These themes were percolating in discussions among the participants, but the focus of the summit was not specifically on the purpose of feedback, rather it appeared narrowly focused on feedback itself.

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What is Adaptive Capacity?

What is Adaptive Capacity?

While adaptive capacity is relatively well understood in natural systems (i.e. biological and genetic diversification, etc.), it remains an elusive concept in the social sphere where there is much talk about adaptation, but no clear understanding of what is required.

Common themes related to adaptive capacity pertain to having flexibility and the ability to adjust to changes (both positive and negative) and to deal with the consequences in a productive way.  Having the ability to instigate change proactively is another common theme.  Adaptive capacity is also closely associated with the ability to learn; to store knowledge and information; to combine different types of knowledge and to access this knowledge, information and expertise when needed.

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