20 Oct Using IoT To Counter Evolving Business Risk
Posted at 15:39 in Resilience by Mark Calvert
Last month I found some interesting research by PwC that explored the role of data in decision making and how this varies within specific industries. Surprisingly, the research found insurance and asset management to be at either sides of the spectrum, despite their reliance on accurately predicting and identifying risk.
Even more surprising was the fact that asset management decision making was found to be largely driven by human judgement at the expense of data, a mere 33% of respondents from the asset management industry regarding their decisions as ‘highly data driven’.
While this was troubling last month, it has become even more so in light of the recent National Flood Resilience review, which confirmed just how insufficient our collective flood protection really is.
Those of you that have been reading my most recent articles will be familiar with my opinion on the efficacy of the short term, interim measures we currently employ in the UK. Flood protection needs a fundamental rethink and needs to be underpinned by long term resilience measures and a commitment to Eternal Improvement.
However, in order to effectively implement these measures and stay one step ahead of today’s environmental risks, we need to recognise the importance of data.
For data-driven decision making to be effective, data must be meaningful and applicable. In the right context, data should tell clear stories and provide invaluable insight. Given our collective unpreparedness for today’s environmental flood risks, it’s clear this is what many UK organisations have been missing.
And this is where I believe the Internet of Things (IoT) can help.
Applied intelligently, IoT has the potential to provide tremendous value to utilities, energy companies and power networks. This is especially true in the context of resilience and risk mitigation.
Harnessing The Internet of Things
When harnessing IoT to mitigate risks, there are three fundamental considerations: the data the sensors are collecting, the insights and trends that can be extracted from the data, and most importantly, the applications of the data.
To illustrate my point, let’s consider an IoT enabled substation site.
Using sensors, it is possible for organisations to collect accurate data in a wide range of areas such as temperature, soil quality, water table height, movement, asset uptime, and oil pressure. This data can then be used to optimise protection, performance and maintenance in substations assets, support assets (such as switch houses) and in protective measures such as bunds.
For instance, by measuring the quality of soil on-site, organisations can pinpoint the extent of any contamination following oil leakages, allowing much more efficient clean-up and remedial operations. Sensors in the soil surrounding a substation can also provide useful information about the rate of contamination and the exact location it is travelling to.
Yet another example is the measurement of increases in humidity in switch houses and bunds to detect water ingress.
The possibilities are essentially endless, even in what is a DNO-specific example. You could, for instance, use motion detectors to detect intruders and reduce criminal activity such as lead theft.
However, much of what I believe currently stands in the way of the mass adoption of IoT is the sheer amount of things that can be done. Developments in smart technology have removed the barriers that previously stopped businesses from accessing huge amounts of data.
While this sounds great on paper, many now face a new challenge: figuring out exactly what to measure, and how to exactly interpret this data to minimise risk or create business value that justifies the investment.
Resilience Through IoT
I believe the answer to this lies in combining smart technology with smart thinking. More specifically, I believe IoT should be used as more than a way to detect disruptive events while they’re happening: this is often too late and is exactly why resilience is critical. Instead, IoT should be used to provide solid clues into what is likely to happen, long before it does. This then allows organisations to invest in the most appropriate resilience measures.
Instead of waiting for third parties to commission research, propose new regional measures or policies and pledge resilience budgets, we should preemptively conduct our own research, using IoT to gather data we can actually use to protect assets.
This might be the monitoring and contrasting of yearly rainfall volume for each site in an estate. Similarly, it might be the monitoring of water levels in nearby rivers or dams to determine whether a particular site should be prioritised over another for the implementation of asset resilience measures.
By thinking a little smarter about how we harness data, I believe we spot trends that provide more timely, accurate and reliable warnings than our current efforts do. These trends will allow us to identify the most at-risk sites and implement PPM and resilience accordingly.
Maybe then, the findings of reports like the National Flood Resilience review won’t be such a bitter pill to swallow.