Part 1: Planning and iterating for sustainability
Sustainability must be central to the business’s strategic vision, rather than an isolated (or even competing) activity. These are not challenges to be mitigated, but opportunities to harness sustainability goals as a growth engine and, ideally, make them part of the business model and planning.
Moreover, when businesses integrate their sustainability initiatives into digital transformation strategy, they will see an acceleration of both processes. The starting point is to devise a route to sustainability. This will map out how to achieve ambitions such as net zero operations, identifying the tools that the organization requires and the platforms where these may be available. It will highlight potential partners for sustainability initiatives – Siemens’ Xcelerator platform, for example, includes a marketplace to explore, educate, exchange, and purchase alongside a community of customers, partners, and experts. Such platforms can also provide inspiration, offering examples of initiatives successfully deployed elsewhere – at other organizations, or even in other industries – that might now be fit for purpose in a new setting.
A sustainability roadmap will also define achievable goals at appropriate stages – target dates for achieving set emission reductions or carbon neutrality are obvious examples. This will not be a journey the organization takes independently of other business objectives; instead, its sustainability roadmap is integral to the rest of its strategic planning.
By conducting a virtual-reality, real-time representation of a new building, power grid, or even an entire city, it is possible to simulate, test, and fine-tune sustainability prototypes without sinking a single spade into the ground.
Digital solutions will be required to enable that planning. For example, every organization will need to establish a baseline of where they currently stand on their key sustainability goals. For that, they will need tracking technologies such as sensors, edge computing, cloud solutions, data analytics, the Internet of Things (IoT), and artificial intelligence (AI). Connectivity is vital: without accurate data available across the enterprise, businesses will lack the visibility and transparency they need to set meaningful and achievable sustainability goals – and, later, to track their progress toward them (see Part 3 of this report).
Digital technology can also play a key role in assessing plans and products before they are implemented. Digital twins, for example, allow organizations to test sustainable solutions before they are even built. By conducting a virtual-reality, real-time representation of a new building, power grid, or even an entire city, it is possible to simulate, test, and fine-tune sustainability prototypes without sinking a single spade into the ground. The twin can replicate existing operations in digital form, so that project managers can understand the impacts of sustainability measures before going live.
At one Siemens factory in Amberg, in northern Bavaria, the company used digital-twin technology to develop a sustainability path for the facility, in line with its ambitions to decarbonize its factories by 2030.
“We analyzed the factory in its current state: what the building looks like, [how much] energy the industrial processes consume, and the electricity, heating, and cooling needs of the facility,” explains Stefan Niessen, Head of Technology Field
Sustainable Energy & Infrastructure at Siemens Technology. “Then, we fed that data into a digital twin of the factory in order to design a multimodal energy system that develops a step-by-step path to decarbonization.”
The applications of digital twins are not limited to planning and developing more sustainable factories, but can be applied to any aspect of the business. They can be used for simulating, producing, and optimizing any product or space – from prototype cars to airplane designs, and from buildings to whole cities. They even allow the possibility of testing out untried technologies such as hydrogen and electro-thermal to project their likely impact before progressing to full-scale implementation.
You can run a virtual vehicle, or a digital twin of the vehicle, on a digital twin of a road.Eryn Devola, Vice President of Sustainability, Siemens Digital Industries
Transportation is a good example, points out Eryn Devola, Vice President of Sustainability at Siemens Digital Industries. “You can run a virtual vehicle, or a digital twin of the vehicle, on a digital twin of a road,” she explains. “This way, engineers can run through all possible what-if scenarios to find the best-possible solution before the first prototype of a car is even built.”
Other types of digital simulation, including augmented and virtual reality, can add enormous value at the planning and development stage. For example, by asking workers to test proposed new production lines in virtual reality before moving to construction, it is possible to optimize staff health and safety conditions and productivity simultaneously.
The now-emerging real-time, immersive industrial metaverse will accelerate this transformation further. Digital-twin technology is the nucleus and key building block for this virtual world. AI-enabled, photorealistic, physics-based digital twins will drive efficiency and transform industries, taking industrial automation to a new level.
Even as businesses move from planning to implementation, connecting projects, often via edge computing, to data analytics and AI, tools will continue to offer valuable insight. IoT technologies provide a constant reading of assets’ current performance. As this data feeds through into control systems and other applications, areas of inefficiency can be identified and focused upon, encouraging a routine of perpetual improvement.
Case Study: How GeoPard Agriculture is helping farmers build sustainable business modelsCloud-based GeoPard Agriculture uses big data and cutting-edge analytics technologies to promote sustainable, biodiverse crop-farming methods. Its work enables farmers to rethink their business models and plan for greater sustainability and profitability simultaneously.
“Sustainability is a fundamental part of precision agriculture,” says Dmitry Dementiev, Co-Founder of the business. “It’s about how to optimize work in your field to make it sustainable in the long term.”
To deliver that goal, GeoPard sources information from a wide range of data sets, including satellite imagery from the European Space Agency and NASA; topographical data from public-sector authorities; and operational inputs from farmers, including soil analysis and drone imagery.
The aim is to build highly detailed 3D maps of agricultural land. GeoPard’s analytics can then advise farmers on the right crop mix, ideal planting locations, precise amount of fertilizer and nutrients required, and which fields should be rested and
when. Farmers can request different outputs tailored to their goals – for example, to maximize crop yields while also promoting biodiversity, improving sustainability, and moving toward carbon farming.
“Farming is about planning, but there are 500 different parameters that might influence your yield, and [varying] weather conditions mean you cannot directly compare one year with the next,” says Dementiev. “If the farm is not balanced and sustainable for the long term, it will not be as profitable as it could be. Planning for that with data-driven understanding of the potential of your fields is so valuable.”