Surprises

How can resilience benefit from planning?

By Pedro Ferreira

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Pedro Ferreira (biography)

Improved resilience can contribute to the ability to deal with unknown unknowns. Dealing with uncertainty is also at the core of every planning activity. The argument put forward here is that planning processes should be considered a cornerstone for any given resilience approach. An outline of planning and resilience is given, before presenting fundamental aspects of planning that should be strengthened within a resilience strategy.

Planning

From attempting to do as much as possible within a day’s work, to launching rockets into space or managing a nation, everything requires planning. The backbone of planning is widely recognised to be a more or less complex and distributed decision-making process that establishes priorities for the allocation of resources and attempts to reduce (down to levels deemed acceptable) uncertainty associated with the pursuit of such priorities.

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Detecting non-linear change ‘inside-the-system’ and ‘out-of-the-blue’

Susan van ‘t Klooster and Marjolijn Haasnoot

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1. Susan van ‘t Klooster (biography)
2. Marjolijn Haasnoot (biography)

Change can be expected, envisioned and known, and even created, accelerated or stopped. But change does not always follow a linear and predictable path, nor is it always controllable. Novelty and surprise are inescapable features of life. Non-linear change can involve threats or opportunities.

Although it defines the world we live in, who we are, the outlooks we have and what we do, we often do not relate to non-linear change in a meaningful way. What is holding us back from engaging with it? How do we deal with non-linear change? And what are promising ways forward?

Why is thinking about and anticipating non-linear change difficult?

Generally speaking, non-linearity is difficult to define and conceptualize, because there are multiple interacting forces at the intersection of many domains, manifesting on different spatial and temporal scales and many different actors and (often conflicting) perspectives are involved.

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Accountability and adapting to surprises

By Patricia Hirl Longstaff

Image of Patricia Hirl Longstaff
Patricia Hirl Longstaff (biography)

We have all been there: something bad happens and somebody (maybe an innocent somebody) has their career ruined in order to prove that the problem has been fixed. When is blame appropriate? When is the blame game not only the wrong response, but damaging for long-term decision making?

In a complex and adapting world, errors and failure are not avoidable. The challenges decision-makers and organizations face are sometimes predictable but sometimes brand new. Adapting to surprises requires more flexibility, fewer unbreakable rules, more improvisation and deductive tinkering, and a lot more information about what’s going right and going wrong. But getting there is not easy because this challenges some very closely held assumptions about how the world works and our desire to control things.

Let’s not kid ourselves. Sometimes people do really dumb things that they should be blamed for. What we need is to be more discriminating about when finding blame and accountability is appropriate.

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Designing scenarios to guide robust decisions

By Bonnie McBain

Bonnie McBain (biography)

What makes scenarios useful to decision makers in effectively planning for the future? Here I discuss three aspects of scenarios:

  • goals;
  • design; and,
  • use and defensibility.

Goals of scenarios

Since predicting the future is not possible, it’s important to know that scenarios are not predictions. Instead, scenarios stimulate thinking and conversations about possible futures.

Key goals and purposes of scenarios can be any of the following:

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Scaling up amidst complexity

By Ann Larson

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Ann Larson (biography)

How can new or under-utilized healthcare practices be expanded and institutionalized to achieve audacious and diverse global health outcomes, ranging from eliminating polio to reversing the rise in non-communicable diseases? How can complex adaptive systems with diverse components and actors interacting in multiple ways with each other and the external environment best be dealt with? What makes for an effective scale-up effort?

Four in-depth case studies of scale-up efforts were used to explore if there were different pathways to positively change a complex adaptive system.

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Should I trust that model?

By Val Snow

val snow
Val Snow (biography)

How do those building and using models decide whether a model should be trusted? While my thinking has evolved through modelling to predict the impacts of land use on losses of nutrients to the environment – such models are central to land use policy development – this under-discussed question applies to any model.

In principle, model development is a straightforward series of steps:

   • Specification: what will be included in the model is determined conceptually and/or quantitatively by peers, experts and/or stakeholders and the underlying equations are decided

   • Coding: the concepts and equations are translated into computer code and the code is tested using appropriate software development processes

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