Author: Oliver Broadbent

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Join us for the London launch of The Pattern Book for Regenerative Design

We’re delighted to announce the London launch event for The Pattern Book for Regenerative Design — happening on Wednesday 19th June, 6–7.30pm at the Society Building in Clerkenwell.

This is an evening for engineers, designers and other humans who want to help shift the construction industry, one project at a time.

Oliver Broadbent will give a short talk about the book: how it emerged from the Regenerative Design Lab, why it matters, and how you can use it in practice. There’ll be copies available to purchase and sign.

The event is free to attend — but places are limited. Feel free to bring a friend who would enjoy this work.

Register here – and bring a friend too!

Come along, connect with fellow practitioners, and celebrate the next step in this growing community.

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Tools for telling the future

What began as a conversation this week on the blog about how designers predict the future has unlocked some deeper reflections on how we approach regenerative design.

Let’s rewind.

As designers, we are always concerned with the future. Our job is to imagine how things could be and shape the conditions to get there. To do this, we rely on two types of indicators:

  • Lag indicators — evidence of what has already happened. The results of past design decisions. 
  • Lead indicators — signals in the present that suggest how the future will unfold.

When conditions are stable, precedent (ie lag indicators) can be a reliable guide to the future. But in changing, complex systems, the past is no-longer such a reliable guide to the future.

In these situations, rather than predict the future directly, we can try to assess the capacity of the system we are working with to successfully respond to change.

Capacity to change — a key regenerative lens

In regenerative design we use the living world as a template for understanding how to create systems that thrive. Thriving ecosystems adapt continuously to shifting conditions. This capacity to change is a key characteristic of living systems — and is a guiding principle for engineers (and other humans) thinking about how to create thriving systems. 

In the Pattern Book for Regenerative Design, we go on to define four factors that indicate a system’s capacity to adapt:

  • Building blocks that can easily be recombined.
  • Coexistence of diverse variations to allow for different responses. 
  • Feedback loops that reinforce adaptations suited to current conditions.
  • Mechanisms for retaining and repeating what works.

From analysis to a design brief

These four factors are both analytical prompts and design levers.

When we encounter a new situation, we try to establish the extent to which each of these is present and use this as a measure of the system’s capacity to survive and potentially thrive through change.

And they can be used as design requirements, giving us factors that we can build into a design brief to create a brief for thriving. 

In a complex situation it is hard to predict the future — instead, regenerative designers seek to make things better by building in the capacity for people and ecosystems to respond together to changing situations in a way that creates thriving for the whole system.

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Lead indicators for heat stress resilience

Up until now, my discussion about lead and lag indicators has focused on classic building performance factors. But regenerative designers are concerned with creating wider system thriving. So we need lead indicators for things beyond buildings — indicators that can tell us how well a place is likely to adapt to future challenges.

At a workshop earlier this week, I was discussing predictors of how well my street might cope with extreme heat in the future. For example, a short-term lead indicator is the quality and age of the housing stock. Poorly maintained Victorian terraces are far less likely to keep residents cool during heatwaves than newer, well-insulated buildings. This gives us a near-term view — how is the street likely to perform this year, or in the next few years, in response to extremes of temperature?

But what about the long-term capacity of a place to adapt? Here, we need to look at other factors:

Absent landlords — High numbers of absentee landlords who neglect their properties are a lead indicator of declining housing quality. Poor maintenance means homes will become less resilient to heat stress over time.

Street trees — Whether or not there are mature trees in a street is a good short-term lead indicator for local heat resilience. Trees provide shade and urban cooling, helping reduce both air and building temperatures. But for longer-term resilience, we need to ask: Is there a plan for maintaining these trees? Are new trees being planted? Are existing trees diseased or in decline? Tree planting programmes and maintenance plans are long-term lead indicators of a community’s capacity to adapt to rising temperatures.

Residents’ associations — The existence of active local groups can be a lead indicator of a community’s ability to organise for resilience. These groups might campaign for street greening, lobby for insulation grants, or even collectively purchase retrofit services—actions that build systemic capacity to cope with environmental stress.

And that’s the heart of regenerative design: looking beyond immediate outputs to understand how places can build long-term capacity for thriving. With so many conditions changing — from technological to environmental — the question becomes, does the local system have the capacity to change. That’s a key lead indicator for future thriving. 

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Crowd-sourced building-performance data

Here’s an idea that I would like to throw out into the solar systems and see if anyone can do something with it. 

I was writing yesterday about post-occupancy amnesia — how little attention we, as an industry, pay to how buildings actually perform once they’ve been built. And this got me thinking: what if we could crowdsource that data?

Think about how Google Maps works. It aggregates large amounts of data provided my millions of users to understand traffic flows and levels of occupancy of different location. All from data that individuals give Google permission to aggregate. 

What if we could do something similar for building performance?

Many of our devices already capture data on location, movement and temperature. I imagine they can also collect data on noise and light levels. If enough people opted in it might be possible to gather data on how buildings are actually performing, eg: 

  • How many people are in a building, in what areas and when
  • How they move through spaces
  • What temperatures they experience
  • Light, sound and air quality. 

Triangulated with health data (with the right safeguards) we might see new patterns emerge. Patterns of how the complex systems of people in buildings actually behave. What we learn from these lag indicators can become lead indicators for the buildings we propose for the future might perform. 

Of course, there a big questions. What’s in it for the user? Why would people opt in?

And there are precedents. The Zoe Health Study in the UK gathered huge amounts of data from volunteers who signed up because there was a clear, public health need. Energy use and building performance might not feel as immediate, but as the energy crisis deepens, and we become more concerned about whether our buildings make us healthier or not, this might change. 

And maybe it can start with a smaller group. Maybe a community of building nerds using such an app would give us much more insight than we have now. 

Every building is an experiment. It’s up to us whether we pay attention to the results.

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Post-occupancy amnesia

This week, I’ve been thinking about lead and lag indicators. About how a designer’s job is essentially to predict the future. And about what factors we choose to use when making those predictions.

Where we have precedent, we can use past successes guide what we think is possible in the future. But when we’re working in new territory — unprecedented scenarios, or changing environments — we need new lead indicators to inform the models we build for tomorrow.

Take structural performance. We know a lot about how buildings stand up. That field is well established. But when it comes to energy performance, the field is less so.

It’s only in the last few decades that engineers (and other humans) have paid serious attention to how much energy a building uses to stay warm or cool. More recently still, we’ve started worrying about embodied energy — the energy used in making the materials and building the thing in the first place.

Of course, we now have increasingly sophisticated modelling tools to predict how new buildings will perform. But they are just that: predictions. What I find fascinating is how little attention we seem to pay to what actually happens after the building is built.

I call this phenomenon Post-Occupancy Amnesia.

One of the key ideas in regenerative design is that design is continuous. We don’t just design and disappear. We don’t just predict and leave. We stick around — to learn, to update our models, to deepen our understanding of the systems we’re working with and how our decisions change what they do.

The good news is that every building that currently exists is an experiment already running. Every one of them is producing data on how it actually performs. If we can gather that data, learn from it, and feed it back into our design processes, we’ll stand a much better chance of making smarter predictions for the future.

Maybe it’s time to trade in post-occupancy amnesia for the post-occupancy evaluations we should be doing as a matter of course to improve our models.

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Designers tell the future (part 2)

Yesterday, we looked at how the Gothic cathedral architects of northern France used precedent to guide what could be built next.

But what happens when there’s no precedent?

When Antoni Gaudí was designing the Sagrada Família in Barcelona, there was no precedent for the complex geometries he wanted to build. So, he created a model: using hanging chains and sandbags to mimic the geometry and loading of the cathedral’s roof.

This physical model acted as a lead indicator, giving Gaudí insight into whether his structure would stand up. When there’s no precedent, you can’t ask “does that look right?”—because you’ve never seen it before.

The reliability of this kind of lead indicator depends on the accuracy and appropriateness of the model. Selecting or creating the right model improves with training and experience.

Engineers build models all the time. In fact, every engineering calculation is a model of the future. A structural stability calculation gives us a lead indicator about whether a structure is going to stand up. Engineers work very hard to make sure these models are as accurate as possible.

But they are still just models. The truth comes after the fact: did the building actually stand up? That’s the lag indicator. And in those rare cases where something goes wrong, this new knowledge gets fed back into better models for the future.

Thankfully, very few buildings in the UK fall down due to bad modelling. That’s because this feedback loop—between model, reality, and revised model—is quite advanced.

But what about the other areas of engineering where we don’t close the loop?

That’s a question for tomorrow.

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Designers tell the future

Yes, it’s true, designers tell the future. At least that’s what people employ a designer to do when they take them on.

Design takes existing situations and turns them into better ones. Given a design brief, a designer can say this is what the future can be like. This is what we could do here. 

Now you may think I’ve let myself off the hook here, by shifting from will to could. So let’s clarify. Designers are usually very discerning in saying what the future is for, say, a piece of land under development, or a product innovation.

Why? Because they are professionals and their reputation rests on how accurately they can predict what is and isn’t the future of a particular project.

So how do designers get this superpower? By using lead and lag indicators.

The gothic cathedral designers of northern France didn’t use finite element analysis calculations to work out how to construct ever taller cathedrals. Instead they looked at what worked on the last one, and said: we can probably go a bit taller, a bit narrower. 

And so starting with Noyon cathedral in 1150 to Beauvais cathedral in 1225, a sequence of six increasingly ambitious cathedrals were built, all in the same region of France. 

For each cathedral, is the structure standing is a lag indicator that it was a sound design. For the next cathedral design, does the design look like the previous one that worked is a lead indicator that the next one will stand up too. 

In this way, designers use precedents of the past as predictors of the future. Each one acted as a lag indicator for the next—a tangible proof of what was possbile. 

But there are limits to this approach. At Beauvais, the builders reached the edge of possibility at that time. The tower collapsed several times before construction was abandoned. Today, it remains a fascinating half-finished monument—the tallest Gothic nave in the world, abruptly stopping where the tower should have been.

Using lag indicators as predictors of the future can only take us so far. They show us what has been achieved. But they can’t tell us what’s next, especially if the next step reaches too far, or if the conditions are changing.

That’s where we need a different kind of lead indicator.

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Lead and lag indicators in design

This week I’ve been thinking a lot about lead and lag indicators in design.

Whether you floss is a good lead indicator of the health of your teeth. How many fillings you have is a lag indicator.

How many enquiries I have in my business is a lead indicator for revenue. What I end up invoicing is a lag indicator.

Lead indicators are predictors. You can influence them, but they aren’t guarantees. Lag indicators tell us what happened. You can’t change them, but you can learn from them.

We need both in design.

I have many fillings — that’s my lag indicator telling me I didn’t look after my teeth well enough in the past. I now floss — that’s my lead indicator suggesting I’ll still be smiling about my teeth in the future.

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Exploring Policy and Place – a Regenerative Design Gathering at Chatham House

On 7 May, we brought together members from all four cohorts of the Regenerative Design Lab, along with a wider group of thinkers, policymakers and practitioners, for a special event at Chatham House. Titled Regenerative Design: Exploring Policy and Place, the event explored how regenerative ideas are finding momentum across construction, policy, and planning. The event was also the final one in the most recent cycle of the Regenerative Design Lab, which we have been running in partnership with the Sustainability Accelerator at Chatham House

With keynote provocations, a panel of leading voices, and conversation corners during the event, we asked:

Where is regenerative design already working? What are the breakthroughs and challenges? And how do we scale this thinking into real, local action?

We heard from:

  • Joel de Mowbray (Yes Make) on circular construction
  • Rachel Fisher on regenerative thinking in national policy
  • Joe Jack Williams on 100-year business planning
  • Rahul Patalia on regenerative masterplanning
  • Rowan Conway drawing together the implications of regenerative design for policy

The day also marked the first public preview of the Pattern Book for Regenerative Design, offering practicable tools for those looking to deepen their practice.

We’ll share more reflections and write up the day more fully once we’ve had time to digest the many conversations and connections that emerged. For now, a huge thank you to everyone who joined us—and to Chatham House for hosting.

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A book of emergence

The word emergence has an almost quixotic feel for engineers. We are usually employed to maintain control over situations. But if we go back to the old definition of civil engineering—harnessing the forces of nature for the benefit of humankind—the word harnessing captures something important. It speaks of working with the system, not imposing control over it.

It’s the second half of that definition—for the benefit of humankind—that tends to cause us trouble. More recently, definitions have expanded to include protecting the environment for future generations. But it’s the first bit I want to focus on.

The systems we inhabit are complex: communities, ecosystems, supply chains. Their behaviour is not entirely predictable. They resist change, then suddenly shift into new patterns.

When we design with a control mindset, we seek to predict, manage and mitigate system behaviour. And when things don’t go to plan, we throw more time, money, energy and materials at the problem.

But we also know how to work with complexity. We start by observing. We notice trends and look for emergent behaviours. We run small experiments to see how the system responds. We update our understanding. We adapt our plans.

This is the art of emergent thinking. And it is enabled by an emergent mindset: one that tunes into what the system is trying to do, rather than forcing it to behave differently.

Ecosystems have an extraordinary capacity to self-organise around the best-fit solution for a given context. Regenerative designers aim to work with—and as part of—this self-organising capacity.

Several of the motifs in the Pattern Book support this mindset of emergence, for example:

  • Continuous Place-Based Design—working in long-term relationship with place
  • Framing the Question—finding different ways to look at the problems we encounter
  • Changing Mindsets—recognising how shifts in the way we think changes the actions we take

And emergence is also written into the strategy of the book itself. This is a book designed to evolve—through new entries contributed by readers, through patterns that emerge from practice, and through adaptations that prove useful in the real world.

Growing an abundance of tools to support emergent design for our mutual interdependence and thriving—that’s the work the Pattern Book aims to do.