Talking about Design for Resilience

The idea of design for resilience opens multiple conversations. This spring, when Sharable and partners hosted a D4R conference, I wrote about innovating from analogy: experiments in applying the principles of ecological resilience – like, say, modularity – to the design of products, services, markets, or social systems.

I've also been working with colleagues to explore the role of knowledge in designing for resilience. Here are notes for a talk I gave at the Understanding Sustainability conference and will present again at the Association for Environmental Studies and Sciences conference.

Both the talk and associated paper, which will be more broadly available later this summer, are works in progress. We welcome your thoughts.

[Update 08JUN10: I have made slight edits to this article.]
 

Design for Resilience: Cultivating Knowledge

• This is a story about change.
  o  While human activities change the planet,
  o  Many on the planet participate in a revolution, aided by digital networks, in how information and knowledge are created and shared.
• This paper tells a hopeful story.
  o  We inventory and describe opportunities for fostering social-ecological resilience through the creation and sharing of knowledge.
• As an effort to synthesize across a range of ideas – design, resilience, knowledge – this is also a story about language. 

Design

• A word with broader application than many of us would have understood years ago: Urban design. Interaction design. Software design.
  o  Design with Nature (Ian McHarg, 1969). Idealistic. Optimization of land use. Forerunner of contemporary Geographic Information Systems (GIS)-based planning.
  o  Herbert Simon, also 1969, also saw design in idealistic terms.
     •  Design “is concerned with how things ought to be.”
     •  “The proper study of mankind is the science of design.”
• The practice of Design Thinking (as described by business press; Tim Brown) builds on ideas of Simon.
  o  Design Thinking process often described as: Define the problem, Research, Ideate, Prototype, Choose, Implement, Learn.
  o  Similarities with best practices in software design.
     •  Manifesto for Agile Software Development (principle: “Working software over comprehensive documentation”).
  o  How might we evaluate such processes and practices?
  

Design for what?

• In this paper, we discuss “design for resilience.”
  o  The word resilient implies a choice of referent: Resilient to what?
  o  In this paper, we consider social-ecological resilience, i.e., resilience to ecosystem disruptions at multiple scales.
• One key advantage of resilience (over, say, “sustainability”) is that it is a term for which there is scientific literature (e.g., Google Scholar search for “social-ecological” returns 20k results).
  o  The literature provides a set of heuristics and propositions for evaluating our designs.

Design of what?

• Return to the first step in the Design Thinking process: Define the problem.
  o  One approach is: Shifting the problem statement.
     •  From, say: “Design a chair.”
     •  To: ”Create a way to suspend a person.”
  o  In other words, we don’t need the chair, just the service that the chair offers.
• The idea of “product as service” applies this type of thinking to business models:
  o  Zipcar (We don’t need to own a car, we just want the service that the car offers.)
  o  Interface Carpet (We don’t need to own the carpet, we just want the service that it offers.)
• When our goal is “design for resilience,” we are more interested in the design of business models than in that of chairs or carpet, per se.
  o  With the relationship between the carpet and the business model in mind,
  o  Here is an analogous example, from Aldo Leopold’s A Sand County Almanac:
  o  “We are remodeling the Alhambra with a steam-shovel, and we are proud of our yardage. We shall hardly relinquish the shovel, which after all has many good points, but we are in need of gentler and more objective criteria for its successful use.”
  
  

Knowledge Management

• We draw from the language of business and organizational development to label these types of activities – (1) the design of business models, and (2) the development of appropriate criteria – as Knowledge Management (KM) activities.
  o  We define KM as: systematic use of tools and practices to identify, represent, and enable knowledge creation and sharing.
• Other relevant tools and practices for the creation and sharing of knowledge include:
  o  Applications of ecological analysis and earth systems science
  o  Pattern recognition and visualization
  o  Software and website development
  o  Peer review
  o  Peer innovation
  o  Market design
  o  Design of participatory and collaborative practices
  o  Design of forums for idea sharing (like today’s forum)
• In the paper, we inventory and describe illustrative examples of KM tools and practices that can be used to foster social-ecological resilience.
• Note that it’s worth being skeptical about this word “management.”
  o  We are not suggesting that knowledge creation and sharing is a managed activity.
  o  We use the word management to refer to the development and implementation of tools and practices – like this conference – that seek to enable knowledge creation and sharing.
  o  Whether knowledge emerges or not remains to be experienced.

Knowledge

• One of the well-known writers in the KM field is Peter Senge.
  o  In one paper, Senge writes: If you want to separate the practitioners from the charlatans, ask what they mean by knowledge.
• We take knowledge to be the capacity for effective action.
  o  As Senge writes: This definition (the capacity for effective action) presents a high bar.
  o  One benefit is that it allows us to distinguish knowledge from information.
• And in a social context, the bar is even higher.
  o  Senge's paper discusses KM in a business context.
     •  Business goals are clear: profit, shareholder satisfaction, growth, and so on.
     •  Business activities are centrally directed or coordinated.
  o  Whereas when discussing KM in a social context:
     •  Individuals, organizations, and societies embrace multiple goals. (For the purposes of this paper, we take social-ecological resilience as a primary social goal.)
     •  Activities are not centrally coordinated. (Drawing from ideas of Douglass North, we presume activities by independent human agents, acting within and among organizations, under institutional constraints.)

Three explorations

• Having proposed and referenced some ways of thinking about design, resilience, and knowledge, let's briefly explore the role of knowledge creation and sharing in relation to three areas:
  o  Uncertainty
  o  Values and mental models
  o  Social learning
   

Uncertainty

• Scientific understanding of the world around us progresses through the KM practice of peer review.
• An example of how these understandings are bounded by uncertainty appears in a recent editorial by Science deputy editor Brooks Hanson.
  o  “The ability to collect, model, and analyze huge data sets is one of the great recent advances in science and has made possible our understanding of global impacts. But developing the infrastructure and practices required for handling data, and a commitment to collect it systematically, have lagged. Scientists have struggled to address standardizing, storing, and sharing data, and privacy concerns.”
• Collection and management of ecological data are indeed daunting tasks.
• And when we shift topics from global to local ecosystem scales, or shift from the physical sciences to the biological sciences, other complexities arise.
  o  Data – about, say, salmon – may be ecosystem-specific or population-specific – and thus challenging to effectively standardize.
• My colleagues at the State of the Salmon program face these types of challenges in their work to help fisheries agencies improve data standardization and interoperability.
  o  Standardizing the data means creating shared language and protocols: What does it mean to count a fish?
  o  Fisheries biologists may or may not have relevant expertise in library or information science.
• These stories illustrate the uncertainties and difficulties inherent in the data management that informs the creation and sharing of knowledge.

Values and mental models

• Notwithstanding data management challenges related to climate science, the Intergovernmental Panel on Climate Change finds a very high certainty that human activities are influencing the climate system.
• Would this understanding of ACC (anthropogenic climate change) meet our definition of knowledge: the capacity for effective action?
  o  Clearly, we don’t yet have a social capacity for effective action.
  o  If we can’t call it knowledge, what shall we call it? Shall we call it an ecological understanding?
• In effect, there is a gap between understanding and action.
  o  Bridging this gap depends in part on other understandings: social understandings of values, mental models, and so on.
    •  If these propositions are correct, we have re-adjusted the DIKW (data-information-knowledge-wisdom) hierarchy.
    •  Based in part on Russ Ackoff’s 1988 paper “From Data to Wisdom,” Understanding is usually placed in between K and W.
    •  We place it in between I and K.
• In our illustrative inventory of KM tools and practices, we pay attention to opportunities for both social understandings and social-ecological ones.

Social learning

• I’m going to wrap up with another story from the work of Ecotrust and partners, a story about bridging the gap from understanding to action.
• The context for the story is California’s effort to implement a network of Marine Protected Areas.
  o  The understanding is that: Marine protected areas around the world successfully support biological density and diversity. (Halpern 2003, pdf)
  o  The difficulty is that: social conflict can arise from attempts to implement protected areas.
  o  As a result: California’s implementation process had twice been unsuccessful. (Bernstein et al. 2004)
• Tools that illuminate the social importance of the marine environment and practices that facilitate stakeholder participation were used to create a more inclusive planning process.
  o  This time, the implementation of protected areas has been successful.
  o  And the tools have received an award for "innovation in technology and environmental conflict resolution."
• In this paper, we pay attention to these types of processes, in which communities of practice and place create opportunities for social learning.
   

Thanks to my co-authors Cathy and P+T, and to Martin, Ted, Greg, Helen+Don, John, and others for our conversations on these topics. Please join us in thinking – and writing – about design for resilience, either in the comment thread or by sending an email: howard at ecotrust dot org.

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