Towards a circular economy.
As a tech-driven design studio, we’ve heard the term “innovation” paired up with “sustainability” across many conversations and in various constellations. While the buzz around these words might overshadow their true purpose, we believe their combined meaning is, and should remain, relatively straightforward.
Innovate to sustain
For BB, sustainable innovation means combining digital technologies, intelligent design systems and clever communication tools in socially inclusive and environmentally friendly ways. It means building novel solutions that positively impact both people and the planet. If we take a closer look at the word “innovate”, we find that it literally means “to make the new”, to create the novel. In other words, to do that which has never been done before.
So for us, innovation is not just about using new technologies to produce more of the same, but about actively challenging the status quo through new methods, ideas, or digital products. In all our tech-driven design endeavours, we need to ask ourselves: which elements of today’s reality do we want to sustain, and which require a change?
Towards a circular economy
Using design and development as our main tools, lately we’ve been helping companies work towards circular business models. As a digital partner, we're particularly focused on using data analysis and user-friendly interfaces to “close the loop”, on everything from material and energy to the data a company collects, ensuring that as little as possible is wasted. This way, we aim to support ambitious businesses transition towards a circular economy (1) through more efficient, inclusive and transparent processes while helping them sustain their core business along the way.
While the circular economy concept is neither new nor difficult to get our heads around, the hands-on techniques and business models to make these ideals feasible, however, have been harder to get off the ground. The difficult part is finding that sweet spot between long-term sustainability and short-term practicalities. In other words, how can we keep up with the growing demand for new products and services while at the same time minimising waste and pollution? Is there a way to decouple economic growth from resource use, and what role can emerging technologies play in this all?
Learning while doing
Building sustainable businesses through innovation is an ongoing learning process, not only because of how complex the challenges are but because of how rapidly new technologies are developing and how radically they promise to improve industries. As a company, we’re finding our way, too, while testing and exploring new methods and ideas. We're excited to see what these innovations might offer and how we can use them to make a difference.
Design and manufacturing
To sustain a healthy planet, it’s essential that companies reduce material consumption and use lower-carbon alternatives, starting with the design and prototyping of new products. We've seen that machine learning–assisted design solutions can be a valuable solution in this first phase of production. By using all sorts of bespoke parameters, these smart solutions are able to quickly generate design options while learning from each iteration. Long before going into expensive production processes, designers can already imagine and indicate what works and what doesn’t, without wasting physical materials.
This process does not only apply to new production methods. When it comes to existing, large-scale manufacturing, machine learning can analyse production processes and highlight any unnecessary or wasteful steps, before re-engineering them appropriately. For example, natural language processing (NLP) becomes a green technology when applied to large data sets in order to assess climate impact in detail. By making vast amounts of technical information more comprehensible through language automation and data visualisations, manufacturers have far more insight into the ways in which they can turn their production processes around.
Systems and planning
In logistics planning, all sorts of optimisation technologies have long helped improve cargo transport by calculating the most efficient shipping routes. Increasingly though, intelligent systems are becoming integral components of circular business models too. Soon, it seems that AI is set to help tackle the “last mile” delivery problem for good, facilitating the expansion of autonomous driving capabilities or reducing the need for delivery vehicles.
Across the entire supply chain, intelligent demand forecasting, predictive maintenance, and smart inventory management systems are optimising the configuration of the entire supply chain, meaning a more coordinated process for the producer, a better experience for the customer, and a smaller impact on the planet. For example, imagine if you could significantly extend the lifespan of a kitchen appliance by simply suggesting maintenance or repairs at the opportune moment; information that can then be shared with all relevant parties. By gathering product data and analysing it with AI, it's possible to do just that, extending its life cycle and delaying the need to replace it with more new stuff, while reducing costs on the production side.
Use and life cycle
In order to close the material loop, businesses need to also close their “data loop”, which means collecting data about their products throughout the life cycle. By gathering information about their processes and placing it at the heart of their “product-as-service” business, companies can learn more about how their products are used and by whom. This can allow them to accommodate people's needs in a more precise, flexible and data-driven way. Not only does this help cut costs and optimise efficiency, but it also helps them forge long-term, and ultimately more sustainable, relationships with their users.
Making the most of products by maximising their usage and extending their life cycle is yet another way to increase sustainability, and AI is proving to be helpful here too. By learning from both historical data and data gathered in real time from products and their users, AI can spot patterns and make decisions that reduce environmental impact and magnify the strength of circular business models. Learning from the way people use the service, it will be possible to bundle deliverables in the most efficient way and provide insight to customers to improve their habits. Instead of simply responding to the way people engage with a service, insights gained by AI could help inform people and change the way they use the service for the better.
Return and recovery
Once any product comes to the end of its life cycle, what happens to it needs careful consideration so that it might be brought back into the design process and made use of in the most efficient manner. Here, AI can help build and improve the reverse logistics infrastructure by improving processes that sort products, disassemble them, re-manufacture components and recycle materials. Material that was once used for one purpose can be repurposed for completely new use cases*. Gaining insights into the transformation of recycling can create value for both consumers and companies.
We see a recent trend towards “circularity-as-a-service” that's made possible by using high-level optimisation, ensuring that a minimum of energy and material are wasted anywhere in the process. The data we capture creates more transparency and end-to-end traceability of circular products and CO2 abatement within value chains. In addition, we can document the impact and waste reduction to ensure the verifiable impact of the changes companies make, meaning they can also be certified for regulatory compliance. Using AI in this way is valuable for businesses directly involved with sustainability practices, but it could also point to potential improvements for any organisation that undertakes physical processes — helping to ensure that waste of all kinds is reduced and that as much material and energy as possible is recovered. As AI capabilities evolve, so do the possibilities for optimisation, meaning ever-increasing circularity across entire processes.
Across all industries and at every level, sustainable innovations are helping businesses gain a better insight into the possibilities of their materials, the needs of their customers and the ways their products are used. By implementing AI-based technologies like generative design, manufacturers are able to avoid expensive and wasteful prototyping long before production is underway. What's more, emerging technologies are making it easier than ever to precisely match demand with supply, ensuring the longevity of products and making the most of them once they're no longer needed. All these innovations, especially when combined, ultimately mean increased sustainability, circularity and a brighter future for everyone.