For many in the industry, the digital twin concept will likely evoke images of industrial use cases. There are good reasons for that. Firms like Siemens, GE and Dassault Systèmes have been banging the drum for industrial applications of digital twins for a long while and have pioneered solutions that have achieved cut-through. Indeed, according to an Altair study, firms in the aerospace, manufacturing, architecture, engineering, and construction sectors are the most likely to have been investing in digital twin solutions for three years or more.
However, the potential of digital twins has room for growth beyond industrial use cases, with the development of digital twins of entire organisations (DTOs) on the horizon.
The vision becomes a powerful reality
Interestingly, DTOs aren’t a new concept. Gartner has been writing about them for almost a decade.
Momentum is gathering pace today due to an explosion of data across enterprise IT environments – from IoT integration into supply chains to business process automation, and the integration of AI into customer touch points. This is what has been missing all these years, preventing DTOs from moving from concept into application. But now, with more data stemming from business and IT operations than ever, it’s possible to digitally and dynamically map the entire organisation.
At this point it’s important to answer a question – even if it is feasible, why build a DTO? The answer is that DTOs present a massive opportunity to overhaul enterprise transformation planning for the better.
Traditionally, business and IT design has been carried out using static architecture models that existed in isolation from the tracking of business and IT performance. By combining business and IT telemetry data with enterprise architecture models for process, application, organisation or tech design, design and performance can be correlated in a way not possible before.
The high-impact business use cases unlocked by DTOs
Digitisation and its subsequent explosion in enterprise data lays the groundwork for building DTOs. The adoption of DTOs is also accelerated by shifting job personas. Today, more companies are hiring their Chief Operating Officers (COOs) from technology backgrounds. This reflects the increasing digitisation of business operations and supply chains. Technology strategy is now a foundational C-suite concern in a range of enterprises.
Potential use cases of DTO are huge so starting small and demonstrating value is key.
For example, focusing on key processes or customer interactions to demonstrate the value of unifying business process analysis with IT architecture models and analysis to get a holistic view within a defined scope.
Customer journey analysis is a great example. Data from customer touchpoints – which is more readily available through the integration of AI into customer interactions – could be fed into the DTO to grant visibility of customer-facing operations in real-time. This would help transformation leads see where friction and negative customer experiences occur and remedy this by working with relevant product leads.
Another example is the analysis of revenue drivers. Equipped with a DTO, businesses will be able to pivot from retrospective and time-consuming data collection methods to real-time analysis and insight generation. This has the potential to shed light on variables like buying behaviour and demand signals that have been opaque to date.
DTOs elevate data-driven decision-making to new levels of sophistication, but they also hold great potential for longer-term business planning and scenario modelling. That’s because a digital twin looks and acts like the organisation but is, of course, separate. The DTO allows end users to simulate a new product launch or user interface changes and test those updates before they’re rolled out – or even understand how factors like enterprise risk are impacted by implementing a new technology or integration.
The not-so-distant DTO future
There was a point in time where DTOs were perhaps academic and hypothetical. That’s not the reality now. Pulling data from business process steps is increasingly feasible in today’s context. That’s an appealing prospect for tech-savvy business leaders looking to take the end-to-end view of an enterprise to the next level.
DTOs are viable prospects and have high-impact use cases. But where does that leave enterprise architects (EAs) – those in an organisation typically responsible for designing and planning enterprise analysis to execute overall business strategies?
The answer is that it’s a huge opportunity for EAs. DTOs grant all-new ways to communicate the importance of how organisations structure their business and technology systems.
Making explicit links to design and business performance opens doors to new conversations. Suddenly, EAs can offer insight into matters as critical as a business’s revenue drivers and customer acquisition.
EAs who can see this vision are in a position to advocate for their organisation to make a head start by centralising data as much as possible. An approach to enterprise architecture that’s compatible with data from as broad a range of enterprise applications and services as possible will help facilitate such an exercise.
Making sense of the masses of telemetry data that a DTO pulls in requires embedded AI technology to sift through the noise and find the signal. But breakneck-speed developments in AI and machine learning no longer render such technology integration far-off or abstract.
Organisations that see this and start preparing now for a DTO-driven future will benefit from a distinct competitive advantage.
- Digital Strategy
- Infrastructure & Cloud
