Across the globe, digital twins are helping to optimise asset performance, improve service for customers and unlock value for their owners.
But building the case for investment can still prove a challenge for built environment organisations. Colin Mann, Consulting Director within our Asia Pacific practice, explains why – and provides some tips for success.
EMBRACING the data-age and the benefits it can bring for productivity and performance is an aspiration of most built environment organisations. And among the current technology megatrends, one in particular – digital twins – is prompting much interest and excitement.
The market for twins is projected to reach USD $48.2 billion by 2026. Examples from across the globe from the Morandi Bridge, Genoa, Italy to the city-state of Singapore are providing ‘real-life’ application and evidence of how twins are enabling asset use to be optimised.
But defining the case for investment in a twin can still prove hard – particularly in an industry which, like ours, has traditionally been regarded as a technological laggard, reluctant to seize on new technologies and adopt new ways of working.
Data and doubts
In the last two to three years, we have supported many clients, primarily infrastructure owner/operators, in the development of strategies and business cases for digital twin development. In each instance, as they have grappled with the ‘why’ and the ‘what’, two fundamental areas have dominated:
- Management: An organisation’s decision makers will cut to the chase and ask for the evidence around questions such as: Can it be done, by our current team? With reasonably procurable resources? Can we avoid sinking cost without ever seeing benefits emerging? and
- Economics: In short – is it worth doing? Industry studies and a vast portfolio of pan-sector examples show us the benefits of twins for enhanced performance, optimised usage, better predictions and better decision-making. But, the question remains – how will it generate benefit for our organisation specifically?
Creating a case with bite
So how to assuage those doubts? How to provide a bullet-proof case, rigorous and comprehensive enough to convince?
My advice is to shape a business case as a collection of real-world proofs which align with specific strategic drivers and collectively provide confidence in managerial readiness and supplier capability. The Management Case is supported by Proofs of Concept and Proofs of Readiness; while the Economic Case is underpinned by Proofs of Value.
Examples of each, based on our recent experience with major transport agencies in both Australia and the UK, are described below.
Proof of Concept (PoC) – it really can be done:
Selecting the right use case to test is key: it must be doable within a reasonable time-frame and budget; while challenging enough to prove feasibility of more complex use cases overall.
Critically, this is not about proving a digital outcome can be achieved once through manual manipulation, but that there is a realistic, systematic solution that can be established as repeatable.
We worked with an Australian rail network operator, undertaking a PoC to connect and analyse maintenance, operational and performance monitoring data for key Turnouts/Points on the network. The objective was to prove the interoperability of data from these three sources, despite siloed management and varying data structures.
Performance of a selected critical turnout/point in the rail network (based on force and current required to transition the point) overlayed with failure incidents and maintenance data: data held in 3 separate systems with differing data structures.
This example is typical of many owner-operator use cases seeking to connect siloed data. Determining data structures, assessing data quality and defining the logic to relate data streams requires expertise, tenacity and rigour. This isn’t an exercise in hypothesising about the potential of ‘AI/ML’; it’s a ‘sleeves rolled up’ effort to identify, master and connect disparate data. The investment will pay off however; in this case, the outputs provided insights previously unseen by asset owners, resulting in strong support for continued investment. Coupling impactful, visual outputs with a design for a repeatable data workflow using ‘here and now’ technology is a big step forward in building executive excitement.
Proof of Readiness – the organisation is ready, willing and able to embrace digital ways of working:
A second key component of the twin case must be proof that the team is prepared for the changes associated with digital twin implementation. This means having an initial design of the new ways of working and an understanding of the collaborative culture which underpins the successful application of digital techniques. A checklist of questions (based on the continued rail example), might include:
- Has the work been done to understand the authority required to change a maintenance regime?
- Has a phased transition plan been considered, with suitable risk mitigation planned?
- Is there an agreed approach for verification and validation of data sources, analytics and outputs to support a Safety Case for reduced maintenance frequency?
In evidencing readiness, program planning and business case creation coincide. The most impactful proofs in this sense are documented commitments from named individuals (not simply an aspirational governance structure) along with a detailed change plan – who, how, and when. This is brought to life by testing the digital processes with real, current, organisational data.
Below: Digital Twin interface used to test digital processes for finding and processing asset information and data to support Proof of Readiness.
Proof of Value – it’s worth doing:
The excitement built from a new visual output will quickly fade if the business value which results from the insight isn’t clear. Continuing with our rail example, it is critical to demonstrate the path from new digital insights to cost/time savings and safety improvements. This is the time to be specific about the ‘data-driven decisions’ that so many business strategies call for.
In this case, the goal is to allow safe decisions to be made to reduce maintenance frequency, moving from a legacy calendar-based approach towards a condition-based and ultimately predictive regime. This not only saves opex budget but also reduces the need to place maintenance staff in a danger zone.
Outputs of predictive potential assessment analytics on a series of similar point motors, with predicted failure rate overlayed with actual historic failure.
Generating a proof of value of this nature can require an extension of the analytics into more enhanced territory. This can be expensive and time-consuming, so for a powerful business case the balance is to do enough to reach a confidence level that the specific data-driven decision is within reach over time.
As a secondary example in the real estate sector, we recently developed a combined Proof of Concept and Value for a national public sector estate owner, with critical estate information and data of their extensive dispersed across multiple systems. With a technically simpler (but highly significant) objective of saving time in finding information, the heart of the business case lay in our functional digital twin environment. The accelerated processes were clearly demonstrated and measurable, using current data for real client assets. This PoC/V resulted in a commitment to a full system build.
Access to spatial, digital engineering and cost data directly from a central twin platform, enabling accelerated processes which can be directly measured as beneficial against the current state
Most organisations and certainly government agencies have defined approaches to business case creation. While most templates I have seen are comprehensive and cover the right topics, they can lead to the author focussing on the document, not the real case.
My advice is to try not to get fixated on the written word and defined business case proforma. Avoid the pitfall of quoting generic benefits – recycling over-used industry rhetoric bestowing the benefits of a digital twin may attract interest but will fail to get a case over the line. Be sure to do ‘real work’ to build a specific and tangible case, while making implementation progress at the same time.
Colin Mann is a Chartered Engineer with significant experience of capital projects, engineering and asset management in the Defence, Energy, Transport and other private sectors.
He specialises in driving value for asset owners through the use of emerging technology, including digital engineering, connected data and analytics.