Eiffel Over

Tag: iteration

  • Warp from the present to the future

    In a traditional loom, strong fibres are stretched out in one direction, through which a second set of perpendicular threads is tied in. These longitudinal threads are called the warp, and the fibres woven in between are the weft. Together they form the patterns in our fabric.

    The goal of regenerative design is for human and living systems to survive, thrive and co-evolve. This statement describes a future state – a vision for how different things could be. 

    But most of the people we work with, be they clients, colleagues or collaborators – are focused on the present. And if we are honest, so are we. If we were to ask ourselves what we think about most often, the answer probably we would be present-day concerns rather than distant aspirations. 

    Warp threads – linking present and future.

    As futures thinker Bill Sharpe helps us understand, the makings of the future are here in the present. 

    The key to bridging future aspirations and present concerns is use framings that are both relevant to today’s challenges and compatible with the future that we want to build. 

    These framings act as strong warp threads, running through the present and the future. Of the various strands of regenerative thinking, three threads stand out as links between the present and future.

    • Complexity – the character of the present and the future. The present is very complex, and it’s not about to become any less so. Regenerative thinking requires us to work with interconnection and complexity. Seeing and working with complexity is therefore both relevant to the present and the future. 
    • Time – the amplifier of change – whether its through compound interest, network effects or technological acceleration, time has the power to amplify both the good and the bad. Regenerative thinking recognises that things are constantly in flow, evolving and adapting over time time. Applying a long-term view is therefore both relevant to today’s interests and tomorrow’s.
    • Iteration – the means of navigating complexity over time. whether it’s the philosophy of continuous improvement, or the method of iterative problem solving – cycles of action and reaction are part of how we work. Regenerative practice requires long-term cycles of experimentation, feedback and learning.  Therefore iterative working has both currency in the present and the future.

    Complexity, time, iteration – are warp threads that link today and tomorrow. They provide a common language that allows us to address immediate concerns through a frame that is still compatible with our regenerative goals.

    You will see these threads running throughout the patterns in this book. 

    But on their own, they are not enough to guarantee a regenerative future. We can also with with complexity, time and iteration to create other, less desirable futures. 

    What bends these threads is the crosswise threads we weave in between, the weft that bends the present towards the regenerative future. 

  • Design loop the loop

    Design is a continuous, looping process.

    It is a loop that begins with observing a situation, then establishing a brief for your work, developing ideas, and testing those ideas—trying them out in some way and observing what happens.

    Then we are back to observing again. Except we aren’t back in the same place, because the system has changed. It now includes your idea.

    The second time around, we are observing a changed world—a world altered by our developing and testing of ideas in response to a brief.

    Now, we can update the brief to create a better set of requirements—a set informed by what happened the last time we went around the loop.

    Each conversation with a client about needs and possibilities is a journey around the design loop.

    Each time we share sketches with the design team, we go around the loop once more.

    Assembling tender drawings and receiving tender responses—another orbit.

    Early contractor input, detailed design, on-site meetings to resolve design issues—all further revolutions.

    Every time we loop the loop, we learn something more about the system we are working in and how we are changing it.

  • Setting learning goals vs. seeing what happens

    This came up in a recent training course. I always ask people what they want to get out of a training programme. To set themselves some learning goals.

    But how do you know what you want to get out of a training course before you start? 

    An alternative, more emergent approach might be to attend the course, be open-minded, and see what you can take from it. By setting goals, aren’t you shutting down possibilities that you hadn’t foreseen?

    I think the best course is somewhere in the middle: to set out on the training with some intentions, but to be open to what comes up. This requires us to be iterative in our learning. We need to set goals, take some action, and then see what happens. 

    We may discover along the way that there is something else that we wanted to learn. Fine — then adjust your goals.

    But, as my mentor, Prof Søren Wilert once said to me, if you don’t know where you were trying to get to, you can’t assess the success of your actions.

  • Taking time to find the right fit

    In yesterday’s post, I explored the difference between kinetic and thermodynamic products in chemistry. The analogy was about allowing change to unfold more slowly, giving the system a chance to find a state of greater harmony.

    The “system” can be anything—a masterplan, an organisation, or even a supply chain. But the principle holds true: quick change might give us rapid results, but finding the best fit for the system takes time. What’s key here is iteration—testing and adjusting to discover if a better solution can emerge, whatever “better” might mean.

    So why should we care about the best fit? If the goal is just to get the job done, then a fast solution might seem sufficient. But if the goal is long-term success and the thriving of all the system’s parts, finding the best fit helps avoid hidden cracks that could lead to failure, and it reduces built-in stresses that could cause damage over time. Fixing those issues later costs time, energy, and money.

    Best-fit design, enabled by iterative processes and informed by local feedback, takes time—but the reward is a more harmonious, lower-energy system.