Solving Sustainability Challenges: The Power of Data

Systems in disruption

Three thousand years ago, the world was more connected and technologically more advanced than it had ever been before. The Mediterranean was awash with traders and migrants, exchanging new technologies and ideas. It was an age of creative effervescence in art, literature, architecture; a world that gave us the treasures of Tutankhamun and the frescoes of Knossos, one that understood quadratic equations and algebra.

Then cracks started to appear. Extreme weather caused droughts and crop failures. Populations went on the move. Political and diplomatic relationships fell apart. Almost overnight, civilization broke down in a widespread systems failure known as the Bronze Age Collapse.

This collapse stands as a lesson to remember the fragility of complex and intricate systems: a foundational frailness resulting from interconnectedness. As archaeologist Eric Cline puts it, it was: “a systemic failure with both a domino and multiplier effect, from which even such a globalized international, vibrant, intersocietal network could not recover.”

Today, we live in a similarly globalized environment; one in which we face commensurate systemic challenges, such as climate change, demographic transformation, technological disruption and resource scarcity.

How can we protect our current systems from such demise? That is what sustainability is all about – finding new paradigms, triggering a new normal that mitigates risks proceeding from our complex, modern, interconnected systems, and paving the way to a safer, healthier, fairer, greener, and more resilient world.?

And in this quest, we have a magic wand that our antique forebears didn’t: data.

The people of the past credited their fall to fate. But thanks to modern scientific techniques, we have the ability to understand our world in radically deepened ways; we can measure and observe nature, design and simulate experiments, test theories, and validate or reject hypotheses in a systematic way. As such, we ?can enhance our ability to predict and manage disruption and create a more sustainable future.

Further developing this understanding is critical. As Marie Curie reminds us: “Nothing in life is to be feared, it is only to be understood. Now is the time to understand more, so that we may fear less.”?

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Building sustainable systems

It is this kind of broad and deepened understanding that fuels innovations such as #AI, green energy sources, and carbon capture, all of which have unbelievable potential when it comes to solving some of today’s biggest challenges. But that potential will only be realized if we can also develop the understanding that lets us apply those innovations in ways that align with our long-term goals. Failure to build this understanding can mean that, instead of solving problems, we just end up shifting them around.

Let’s take the case of renewable power. The plummeting cost of #renewableenergy in the last few decades has been one of the most tangible scientific triumphs of the century – the unit cost of solar power alone fell by 85% in the decade between 2010 and 2019, according to the International Renewable Energy Agency (IRENA) .

But even lower energy costs come at a price. These technologies are heavily reliant on rare earth minerals such as lithium, cobalt, and nickel, and extracting these minerals has its own environmental footprint. And it’s going to get worse before it can get better; according to the International Energy Agency (IEA) , demand for lithium alone could grow fortyfold by 2040.

Does this mean we should stop commissioning new renewable power? Of course not. What it does mean is that new projects must be developed with a better understanding of how potential secondary impacts can ripple out through wider networks, and – crucially –?how we can mitigate these impacts.

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For green technologies, this might mean designing components to reduce reliance on these materials, or performing Life Cycle Assessments so that various scenarios can be compared, and the most sustainable paths chosen. It’s something I often see with our customers at @Dassault Systèmes, and I’m incredibly excited that my colleagues are so actively involved in supporting the development of these practical solutions.

Developing a deep and dynamic understanding of whole ecosystems is also critical when it comes to responding to crises on extremely short timeframes, where we can often be forced to rapidly come to terms with – and formulate solutions to – wholly unexpected scenarios.

In his book Material World, Ed Conway provides an interesting example: “borosilicate glass [a fusion of glass and boron] received a sudden flurry of interest in the wake of the COVID pandemic amid worries that the main thing holding back the distribution of vaccinations might not be the pharmaceuticals themselves but the containers in which they would be shipped.” As such, rapid innovation saw the deployment of new glass products made not with boron but with aluminum, calcium, and magnesium, to help satisfy the demand for medicinal vials. To avert disaster, thousands of people along a complex supply-chain stretching from mines to refineries to factories came together.

The ecosystem had anticipated vaccine shortage; it had not expected glass supply to be a similar challenge. But because they were able to build the requisite understanding quickly, they were able to adapt and avert disaster. It stands as further proof that high levels of resilience and agility only come through a deep understanding not only of your own operations, but also of your value chain and of the market in which you exist.

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Leveraging the tools to overcome complexity

So what does this mean when it comes to embracing true #sustainability? Whether that means decarbonizing our economies or protecting ourselves against future disease outbreaks –?the answer is that that we need to start thinking in these complex ways, taking a holistic approach and leaving no detail unaccounted for.

To that end, #data –?and the tools it enables –?will be a differentiating lever. Solutions such as virtual twins,?with their ability to pull in vast amounts of information from a wide variety of sources, and model and simulate countless scenarios – thereby facilitating decision-making based on science and clear and open collaboration?– constitute a paradigm shift in our ability to understand and talk about our world at a systems level.

Because this is a world driven by information, in volumes that can easily overload ordinary human understanding. Simply getting out of bed, boiling a cup of coffee, cleaning your teeth, and catching a train to work may feel mundane, but it rests on an immensely complex mosaic of tessellating systems.

These systems include the power stations providing electricity for our kettles; the chemists designing the ingredients in our toothpastes; and the engineers making the trains that whisk us to work (not to mention excavators digging the tunnels through which we are whisked!). All, miraculously, intersecting to the service of every individual.

Building sustainability in such a world can’t just be about relying on technology. To implement that technology, we must marry it to an understanding of the systems that make up our world in all its complexity, and how they interconnect, at every single level.

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