Innovative technology to improve decision-making

Line of sight in decision-making

The nuclear industry is well known for developing innovative technologies, less so for adopting new technologies at scale. A key reason for this is lower-than-expected improvements to the business outcomes. This isn’t a problem specific to the nuclear sector; our recent survey of CEOs found that almost two-thirds had a clear strategy for digital investment in their operations but only 30 per cent had any confidence of value delivery in the short term.

One major issue facing the nuclear industry is the inability to articulate how any technology would help day-to-day decisions of staff at organisational levels. This prevents staff from endorsing the technology and inhibits wider-scale adoption, resulting in lower-than- expected value from the technology.

We recently deployed digital twins at a UK nuclear site, using an approach that made improved decision-making the main aim. The facility’s leadership wanted help planning a multi-generation project as efficiently as possible, while maintaining the site’s exceptional safety record. They had previously made decisions regarding both long-term strategic investments and day-to-day operational issues using experience and time-based rules. This resulted in a situation where:

• assets were under-maintained, resulting in failures that cost more to repair
• assets were over-maintained, resulting in higher maintenance costs and personal safety risks
• there was little optimisation of asset investment prioritisation.

The first objective we wanted to achieve was determining where the responsibility lay for various parts of the utility network. While going through this process, we found there was no ‘line of sight’ between the performance of the asset and the overall performance of the enterprise. This meant operators would only focus on reaching their daily targets without due consideration to equipment health, leading to a detrimental impact on the asset condition that resulted in significant maintenance costs. At the other end of the scale, senior executives were planning large investments without understanding which parts of the utility network were underperforming.

To build the line of sight between asset and enterprise performance, we engaged with staff at all levels, including maintenance staff, systems engineers, the chief engineer and the CEO, to understand the decisions they were responsible for and the rationale for making those decisions. We then built a digital twin of a part of the utility network using computational fluid dynamics and physics-based modelling, letting users evaluate the consequences of their actions on performance metrics such as safety, cost and delivery.

The digital twins we implemented provided a line of sight between the maintenance teams and the boardroom. With this visibility, the asset maintenance managers were able to simulate the impact of operational decisions on the overall performance of the site and understand specific maintenance requirements. This let senior managers optimize decisions, benefitting the whole site as they could prioritise maintenance across the utility network, not just their process or systems. By optimising decision-making across organizational levels in this way, the digital twin helped identify operational savings of £8 million per year, as well as the potential to reduce carbon emissions by 100,000 tonnes annually.

In our experience, it’s crucial to consider a holistic approach when trialling any digital technology. The nuclear industry has been accused of doing technology for the sake of it, without giving much consideration to the ecosystem the technology will operate in. For example, what are the business process or cultural changes that need to accompany the technology to fully exploit it? In the case of the nuclear operator we worked with, by making decision-making the core purpose of the digital twins, we were able to get employee buy-in from the outset, thereby delivering sustainable value.