Why Digital Twin technology is the ‘right call’ for the next phase of the telecommunications industry

Telecoms.com periodically invites expert third parties to share their views on the industry’s most pressing issues. In this piece John Hill, CEO of Silico, explains why he thinks Digital Twins are emerging as a key technology for telecoms.

Do you truly know your business ‘inside out’? Before you answer, take a moment to really think about the question. It might sound simple as an exercise, but when taken seriously it can quickly become daunting.

So how do you answer it? For the telecommunications industry, challenges around holistic business visibility and planning have been tackled by complex data strategies and the use of emerging technologies such as artificial intelligence and machine learning.

Whilst these predictive technologies have their merits and have proven useful in helping guide important decisions with a certain level of insight, they should now be seen as parts of a much greater and more in-depth approach to decision-making courtesy of simulation and modelling. Organisations can now ‘play out’ how certain decisions may impact the overall state of their business and its services through a Digital Twin of the Organisation. But what are Digital Twins, and how do they work?

Understanding Digital Twin technology

A Digital Twin is a digital representation of physical systems, products or processes that serve as counterparts for purposes such as simulations. They replicate the impact of decisions in real-time, providing information on effectiveness, performance, and possible future bottlenecks. Through these simulations, businesses can transfer learnings gained in a digital setting to the real world and determine the best courses of action.

As global markets continue to grapple with uncertain economic conditions, it’s little wonder that Digital Twin technology has become an appealing choice for senior leaders across industries. Digital Twin technology is expected to see widespread adoption throughout 2023, with Fortune Business Insights research projecting the global market size to grow to a staggering $96.49 billion by 2029.

Digital Twins aren’t technically a new concept. Historically, they have been used for high-value projects involving mechanically complex systems to monitor product performance and quality. The technology famously transformed the space sector in the 1960s, when NASA used basic twinning technology to support and maintain satellite systems without the need for direct human physical contact – these are known as physical Digital Twins.

Now, Digital Twin technology has evolved to become more accessible to wider industries, offering the potential for equally transformative impact today in new areas of economies just as it did over sixty years ago for the space industry.

Digital Twins in telecommunications

Digital Twin technology is set to continue its rapid adoption across multiple industries, including telco. It’s now possible to incorporate Digital Twins into any given telco’s non-physical systems, through Business Process Simulation (BPS), enabling organisations to build twins of their whole business, called a Digital Twin of the Organisation. This provides several key advantages, such as increased frequency and speed of scenario planning, forward-looking process models, and better alignment of business and financial objectives through a more holistic view.

Telcos can generate forward-looking analytics by creating a large-scale Digital Twin based on real-time metrics. Predicting future challenges by visualising them enables them to make more strategic decisions and take more informed proactive measures. Having seen their simulated outcomes within a Digital Twin, a business can then decide to execute these changes – or not – in the real world.

In an increasingly unpredictable economic climate, businesses must be prepared to adapt swiftly to unforeseen circumstances. Many telcos are experiencing increased expenses due to macroeconomic factors, stagnating revenues and competition from new-age operators. To navigate this, it’s essential to use advanced forecast models to evaluate the optimal response to such challenges, based on their impact on business outcomes.

The power of ‘what if’

A benefit of BPS is using ‘what if’ scenarios to evaluate the ‘as-is’ processes of a business and identify where problems may arise in the future. BPS can then ensure that optimal decisions are made, and resources are concentrated on process improvements that solve upcoming issues. BPS can determine how changes throughout a business may affect processes and, as a result, business objectives by connecting various processes across teams and departments and connecting them to business outcomes. Users are not restricted to statistical distributions when creating such scenarios. Instead, Digital Twins can serve as a reflection of future expectations and policies to help determine how prospective changes will impact each step in the process.

A Digital Twin analyses the effects of a system-wide change, such as the costs and advantages of changing the core support systems for processes. The twin can then outline which immediate problems need to be resolved. By creating a Digital Twin, telcos can trial changes they wish to make, record the possible impacts, and make a strategic decision on whether to commit to making the change to their real-world systems.

By identifying differences between intended and achieved outcomes over time, BPS can assess if additional process adjustments are necessary to accomplish goals. Process experts can then take proactive action throughout the deployment to enhance outcomes, improve client and customer experiences and increase satisfaction levels.

One example of a Digital Twin is the ‘lead-to-cash’ process. Lead-to-cash refers to the end-to-end process from a customer’s initial interest in purchasing a product or service to the generation of revenue and cash flow for a business.

Telcos can use lead-to-cash Digital Twins as management and planning tools, allowing them a series of useful advantages. Not only can these Digital Twins help them accurately predict delivery dates to improve customer experience, but they also evaluate automation and digitisation of process steps which can reduce costs and free up vital staff resources for alternative value-adding tasks.

Digital Twins help businesses foresee any changes affecting the process to intervene proactively. They can create intricate forward-looking scenarios easily and are not limited to historical values, statistical distributions, and events. Instead, scenarios can reflect future policies and expectations to understand how upcoming changes will affect all parts of a process.

The future of telecommunications with Digital Twins

Maintaining profitability in the face of a massive investment load, stagnant revenue growth, economic pressures, and tough competition from new-age operators are all challenges telcos face today. Unlocking value and savings through cost optimisation will be crucial for telco success in a 5G era, assuring a steady stream of investments and profitability.

Using BPS, telcos can transform their business processes and ensure that they support their strategic objectives of simultaneously increasing customer experience and revenues while reducing costs.

The next generation of decision-makers will routinely plan and optimise their business outcomes by using simulations and scenario analysis. A Digital Twin of every operator will be created so that what is discovered in a digital environment can be applied to the physical world. The resulting agility will enable businesses to respond quickly to rapidly changing conditions – particularly important in today’s competitive environment.

John founded Silico in late 2019. He leads in setting and communicating the company’s vision and building a world-class team to make it a reality. John studied Economics to post-graduate level and trained as an Economist at the Bank of England where he worked for over 5 years, primarily on the UK Banking System and Banking System Stress Tests. John left Economics behind to do a post-graduate in Computer Science at UCL before working at a deep-tech simulation start-up in London as Head of Simulation.