Design thinking fails to address complex system problems: What can it do better?
Design thinkers face particular challenges when seeking to intervene to improve value and outcomes in complex adaptive ecosystems such as cities, health and social care, education, energy, food production and distribution, the built and natural environment and development. In such systems, the root causes of problems and the origins of poor outcomes are often hard to identify and difficult to address due to their nested, interconnected and dynamic nature, as well as the fact that they consist of a diversity of humans, technologies and resources whose actions and effects are not wholly predictable.
Despite best efforts, many design thinking type interventions that seek to address complex system problems and improve outcomes add only limited or incremental value. They merely tinker around the edges. They suffer from low user participation or engagement, may even create or exacerbate stakeholder conflict, do not scale or are not used on a sustained basis. Worse of all, they can even reduce long-term ecosystem wellbeing in favour of short-term gain.
Design thinking and complex adaptive systems
When making interventions in complex adaptive systems, it is necessary to identify, engage with and satisfy the needs of multiple stakeholders. A designer seeking to create new value must understand how complex systems adapt and evolve in response to the direct and indirect interactions of all stakeholders, the different goals they have, the diversity of resources they can access and use, the outcomes they prioritise and often, the widely different (and sometimes in conflict) values they possess.
Learning about a problem from only one or two stakeholder groups risks leaving important gaps in understanding, leading to the design of partial interventions and piecemeal solutions based on incomplete evidence. Rather like the parable of the learned blind men touching an elephant, focusing on just one part of a complex system problem only ever produces limited insight (especially if you are at the tail end). Such a narrow perspective is one of the main reasons why technologies and solutions fail to become adopted, or do not achieve the hoped-for scale of implementation.
What can be done? Some questions for discussion
Simplistically perhaps, there seem to be two schools of thought when it comes to making interventions in complex adaptive systems.
1) “Downstream” product, solution and experience design thinking preceded by some empathic problem definition with a subset of stakeholders. Perhaps this approach accepts that problems are best resolved through increasing the diversity of options and solutions to address them.
2) “Upstream” deep problem understanding using a combination of analytic and interpretive method, followed by strategy design that shapes solution design. This approach suggests that for more deep-seated persistent, paradoxical, connected and complex human problems (or “wicked” if you prefer) — such as obesity or pollution for example — it is first important to step back and learn the parameters of the problem more deeply.
If you agree that 1) is insufficiently systemic in scope, is piecemeal and lacks scale, and tends to address consequences rather than root causes, and that 2) is an alternative for certain complex, paradoxical, irresolvable problem situations, then what do design thinkers need to do to undertake 2) better? I identify some key questions in four categories to help (maybe there are more?):
How should design thinkers frame complex, persistent system problems? What are the boundaries they need to set? How and what types of contexts to use?
What units of problem analysis are best to use? In particular, how is it possible (or even necessary) to keep upstream problem understanding separate from downstream solution design and thinking when analysing a complex system problem?
Is there an underlying structure of complex systems that can help to organise or guide a problem enquiry, to “see complexity” and then discern important trends, patterns and relationships in relation to the framed problem?
What types of system design and interventions can be made beyond incremental product, experience and service alone? In particular, how are transformational propositions better designed and made?
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