As Kames approaches 30 years of ethical investing, one of the questions we’re being asked the most is essentially ‘what’s changed in that time and why?’
The answer to this is multi-faceted. For many industries, sustainability has become a commercial imperative (see mining example below). But multiple drivers now mean that the sustainable investment opportunity set has increased. Or to put it plainly, there’s more sustainable stuff to invest in. In part this has been technology enabled and we have written about sustainable disrupters frequently (e.g. here, here and here).
But technology can be enabling too. Specifically, enabling traditional industries to seek out operational (and therefore sustainable) efficiencies, which in aggregate can be significant.
Sensors are now pretty cheap, so they can be used to create ‘smart’ industrial equipment- able to monitor their own performance or that of their physical environment, e.g. temperature, pressure, humidity, vibration.
Then you have cheap computing power (combined with communication networks) which is enabling the capture, management, analysis (machine learning) and storage of increasingly large amounts of data (from those handy sensors I told you about). Machinery and industrial assets are becoming digitalised. Welcome to Industry 4.0 and companies like Kames hold* UK-listed Aveva Group Plc and Paris-listed Schneider Electric SE.
Imagine you could predict the future? That’s literally one of the services that Aveva and Schneider Electric are trying to do for their clients using predictive maintenance. Rather than follow a simple calendar-based schedule, using the data generated from the sensors on your physical asset, predictive maintenance uses machine learning to spot problems before they occur. Companies are better able to identify underperforming assets, plan and prioritise maintenance, reduce downtime, avoid costly (and possibly catastrophic) events and improve safety and regulatory compliance. Sensors and computer chips now measure and collect information from jet engines to wind turbine gearboxes.
A ‘digital twin’ – the digital representation of something physical- no longer the stuff of science fiction. Digital twins are now employed in a variety of industries at a multitude of scales. Mining is becoming increasingly energy intensive as ore grades decline, forcing companies to become increasingly efficient. Like a number of others, UK-listed miner Anglo-American** is digitising its mining fleet and using machine learning to improve precision and efficiency.
Less energy and water in + less waste out = less costs + more productivity.
At a completely different scale, Singapore (yes, as in the whole city!) is working on a digital twin. Singapore is known for its efficiency, but its density provides little room for physical infrastructure experiments. A digital model would allow designers, planners and policymakers to explore future city-scapes. Static locational data of every building to bus-stop, alongside dynamic data of where the buses are and even things like dengue fever clusters. The UK wants to do something similar for the whole of the country’s infrastructure network. Incredible.
*As at time of writing 08/03/19 Kames Capital holds
**As at time of writing 08/03/19 Kames Capital does not hold
About the author
Ryan Smith is Head of ESG Research. He joined Kames Capital in October 2000 as an SRI analyst and was appointed to his current position in September 2002. He has 18 years’ industry experience*. His role involves managing the team that conducts the ESG screening process for our Responsible Investing funds. Ryan’s team also provides corporate governance screening and research for all equity investments, and conducts research into environmental and social issues. Before joining us, he worked as an environmental chemist for Severn Trent Water. Ryan has an MSc in Environmental Chemistry from Nottingham Trent University and is a CFA charterholder. *As at 30 November 2018.