Establishing a Digital Twin Program and establishing the why (part 2)

Choosing a Business Case Framework

There are different frameworks that can provide guidelines for a more seamless implementation and adoption process. For example, the UK’s HM Treasury Green Book provides guidance on developing an effective business case for innovative programs such as with digital twin initiatives. This guidance is considered good practice for all projects but is mandatory in certain situations, like the introduction of new public assets or services, significant changes to existing assets or services, or a need to re-evaluate the delivery model of an existing asset or service.

HM Treasury Green Book’s guidance covers five key elements (a five-case model): the strategic case, economic case, commercial case, financial case, and management case. These elements support the development of a holistic and compelling business case and help the owner to systematically consider and present the impact of new capabilities, innovations and technology.

Informing Decision-making

As digital twins can inform a government policy, an organisation’s strategy, or a plan to construct or operate built assets – digital twins are valuable resources for informing decision making. Consequently, it’s important that your digital twin program supports multi-criteria decision-making, allowing for exploring trade-offs and optimal choices across various business departments.

Another model, the ‘Desirability, Feasibility, and Viability’ approach can be used to frame the need for a digital twin and quantify the value for money when justifying its investment, where desirability covers the use cases and reasons for change, feasibility covers financial and management considerations, and viability accounts for the socio-economic and commercial factors.

Another method is the ‘Integrate, Orchestrate, and Operate’ approach, whereby architecture is structured around the use case principle and themes like trustworthiness, integration, and connectivity are embedded into the architecture.

The key focus areas of the architecture are Data Abstraction (collecting, aggregating, wrangling, and storing data from multiple data sources); Analytics (business rules, algorithms, machine learning and simulation requirements to create meaning from the data) and User Interface (providing user interaction capability through dashboards, workflows, human-machine interface screens etc.)

In the early stages, it’s advisable to start by building a minimum viable version of your digital twin to test your assumptions, learn from feedback, and improve rapidly. There is also a role for Proof of concepts, proof of value, prototypes and pilots as part of a phased implementation and to afford time for proper change management and continuous improvement.

Mapping Investment Logic with Decision Makers

Writing a business case provides an opportunity to justify and evaluate the need for a digital twin. That’s why it’s important to start early with the design, build, and operational lifecycle to understand how time and resources will be allocated towards the different elements of the digital twin program.

At the early planning stage, mapping investment logic can help determine priority use cases and enable the evaluation of various plans, including various what-if scenario tests prior to committing to real-world investment. For example, the metaverse may be a desirable future vision and end-state, but it’s often not ready for prime time in terms of the starting point or the core foundational platform. It’s far more practical to start with a digital twin at the core of your technical architecture and think about the various data sources you wish to integrate.

One of the key benefits of digital twin capability is it allows you to incorporate multiple use cases into fewer solutions to promote even further collaboration and new insights. Construction use cases, for example, can range from interface management, material quality, and logistics optimisation to health and safety of workers. One very effective way to get results quickly is to work with a platform that enables multiple use cases initially but then carefully consider and explore the supporting infrastructure and data governance model over the long-term.

Conclusion

Once you’ve prioritised your target use cases, you can determine how they contribute to the overall ROI in terms of cost savings, efficiency gains, revenue enhancement, risk mitigation, quality and performance improvements, strategic and long-term value, and environmental and sustainability impact. Read part three of this Blog Post to understand the capability readiness landscape when establishing a Digital Twin Program.