No longer a nice-to-have, digital twins are shifting to a necessary business tool to turn collected data into a competitive advantage. A digital twin will help a company make better decisions, create operational efficiencies, improve customer experiences, and change behaviours by processing raw data about the workplace ecosystem into easy-to-understand insights. But you need a clear, actionable, and flexible digital twin roadmap to capture bottom-line benefits. The time to start your digital twin journey is now.
The broad scope of the digital twin concept makes a common definition difficult, creating confusion and uncertainty among businesses. Dr Michael Grieves, the man behind the digital twin concept, advises not to get caught up trying to define the term. "If we can visualise it, we can create a digital twin. Focus on the use cases: you want to trade off bits for atoms wherever you can to do things more effectively, efficiently, and cheaper."
To move from proof of concept to proof of scale, companies need innovative partnerships and open collaboration to 'start small, think fast and scale quickly'. Align your digital twin strategy with your business strategy and start with a small pilot study focusing on practical and high-value use cases. It's not always necessary to build your own twin. Buying into existing industrial software solutions will fast-track deployment, but no one company can offer a complete set of solutions. Collaborate with strategic partners that provide distinctive capabilities and are open to innovative partnership models. Modularity of technology is fundamental.
Strategy, capability, culture, and technology all need to align to work towards a successful digital transformation. Most Agile backlogs have nothing to do with the technology, and unless you achieve buy-in throughout the organisation, you are set up for failure. The end users are the true stakeholders, and digital transformations must be a people exercise, not a technology exercise. Without adopting both top-down and bottom-up approaches, you'll find misalignment, misinformation, and misunderstanding, and individuals will struggle to adopt the technology.
Remain Agile and Lean, don't work in silos, communicate your wins, and pick up on lessons learned. Technology should not be viewed as a threat to employees, and it will augment individuals' capabilities rather than replace them with the right culture and climate. In the ideal world, the majority of leaders can tap into the learning mindset in the majority of times and create environments of trust.
Many technology projects fail because there is no strong data foundation in place. Understand the data you have and the data you need to deliver your business value. The data will dictate the technology tools. By deploying a digital twin, data can be cleaned, contextualised and democratised by breaking down silos for a single source of truth to expedite agile decision making. But the right data foundations must be in place at the primary source, and you must be flexible with your technology. Data standards will enable efficient innovation. For Patricia Rangel, VP of Intelligent Operations Digital at bp, "The key to adoption and value lies in augmenting operations and engineering teams with integrated and contextualised data with advanced analytics, automation, and importantly, a simplified user experience." This data foundation will be key to all other technology integration work.
Cyber security is not just about being secure; it's about detecting and being able to respond to an incident. If frontline personnel have not drilled on recognising and responding to a cyber-security incident, an effective, orderly response is not probable. A digital twin can be effectively applied in red and blue team exercises and as a training simulator to develop and hone human response for a more proactive and predictive approach to detecting and responding to cyber compromises – all without the need to travel. But a digital twin is just as vulnerable to attacks as the asset it mirrors and needs to be protected in a sandbox environment with its own security. Practice cyber hygiene and keep your digital twin updated and relevant.
The oil and gas industry needs to change at pace to enable energy security while also driving decarbonisation and achieving ESG goals.
With a digital twin, carbon impact can be built into every single process and decision a business makes, from measuring and tracking emissions to minimising energy consumption through optimising operations – the cleanest energy is the energy you haven't used. By running simulations in a risk-free onshore environment, digital twin analysis can maximise ROI and minimise risk for new offshore developments in hydrogen, CCS, wind, and electrification to support the energy transition.
For Shane McArdle, Senior Vice President of Digital Energy at Kongsberg Digital, "Digital twins are becoming a work surface for the industry, where people come every day to access the data, insights, and updates they need. Digitalised workflows will continue to enable users to leverage existing infrastructure and optimise their time for more efficient and safer ways of working."
However, it is only through the integration and interoperability of different types of digital twins and their data that digital twins will deliver the full potential that they promise. From the predictive standpoint, if our systems don't predict, they will be relatively useless. But Dr Grieve is optimistic, "We're at 54 billion transistors on a chip right now. By 2030, we will have around six trillion on a chip. And by 2040, it will be hundreds of trillions. With AI and Machine Learning, we will have amazing computing capability."