Data hunger

Sustainability has become increasingly important to companies across all industries as reporting policies and regulations encourage corporate transparency and accountability, with data analytics providing the actionable insights needed to progress sustainability initiatives.

The attitudes of large institutional investors and asset managers towards responsible investment have changed. Many now incorporate environmental, social, and governance (ESG) metrics into their capital allocation. The United Nations Principles for Responsible Investment (PRI) promote the incorporation of ESG into investment decision-making. The recent World Wildlife Fund Netflix documentary, Our Planet: Too Big To Fail, explores the role of the finance sector in tackling the climate and nature crisis.

Facts and figures

Data plays an important role in helping companies satisfy the requirements of sustainability standards, such as the Greenhouse Gas Protocol accounting standard.

The Global Enabling Sustainability Initiative (GeSI), which brings together leading global tech and communications companies to look at integrated social and environmental sustainability through digital technologies, estimates technology can reduce greenhouse gas emissions by 20% by 2030 compared with a ‘no change’ approach. That would be equivalent to holding emissions to 2015 levels and generate US$11 trillion in new economic and social benefits and an estimated 30% rise in agricultural production using less water.

Further analysis of data can help organisations reduce costs while prioritising and allocating resources to initiatives that have the most impact in reducing carbon emissions in the shortest time. For example, data on building energy ratings can help banks understand the energy efficiency of mortgage portfolios and drive strategies to reward customers who retrofit buildings to improve energy efficiency and reduce carbon emissions.

Then there’s the United Nations Environment Programme Finance Initiative, which has developed principles for responsible banking. Those principles provide the framework for a sustainable banking system, with banks encouraged to integrate data on future changes in extreme events into their risk assessment processes in order to effectively analyse physical risks to their portfolios.

Fast response

More widely, data analytics can help us understand how global energy consumption affects climate change. Tools and techniques can predict global warming trends and extreme weather events such as storms, heat waves and flooding. Predictive analytics can enable decision-making processes in real or near-real time. Given the rate at which climate is changing, data analytics is crucial in providing the information needed to respond quickly.

Data analytics can also help us understand how the development of urban green infrastructure can reduce the effects of climate change and enhance urban resilience and sustainability. Spatial planning and analysis can locate the most suitable places for habitat enhancement projects and guide infrastructure developments away from sensitive nature areas.

Big data, big footprint

However, as a result of such initiatives, the volume of data being collected in the world is increasing exponentially, and it is important that we understand the adverse environmental footprint created by mass collection and storage of data. Data centres and cloud computing form the backbone of the data revolution, creating a heavy footprint via their high consumption of non-renewable energy, waste production and carbon emissions.

Power-hungry data centres use an estimate of 400–500 terawatt hours of electricity each year. That equates to over 2% of global electricity consumption, or slightly more than the UK’s total annual figure.

Similarly, our own personal use of technology and consumption of data has soared since the onset of the pandemic, as we use a range of mobile and fixed devices to connect with each other, and consume large amounts of content from video streaming services such as Netflix. That, in turn, is increasing the energy output of the devices we use, the networks our devices connect to, and the data centres storing and serving up content.

Accounting for sustainability

It is clear that data has become a powerful tool in efforts to measure progress towards sustainability goals. Accountants can use this opportunity to develop skills in data analytics to uncover areas where environmental impacts can be measured and addressed, and to help businesses embed sustainability by developing long-term strategies that build climate change resilience. Accurate measurement and reporting of sustainability activities is a key mechanism in communicating accountability to stakeholders.

Up until now, much of the effort has been directed towards traditional industries, such as the automotive sector, and their impact on the environment. However, the technology sector also needs to look critically at the ESG risks it poses.

GeSI predicts that using artificial intelligence (AI) for environmental applications could reduce global greenhouse gas emissions by 4% by 2030 – equivalent to the combined emissions of Australia, Canada and Japan. Google already uses AI to reduce data centre energy consumption by 15%, with a 6% reduction in cooling, suggesting that the technology industry is rising to the challenge.

Looking ahead, accountants have a critical role in helping companies weigh up different strategies to achieve their sustainability goals. For example, analysis from the Centre for Ecology & Hydrology and the University of Reading found carbon dioxide (CO2) emissions in London reduced by almost 60% during the first Covid-19 lockdown, largely because there were fewer cars on the road as a result of people staying away from the office. This would suggest that even if remote working boosts the load on data centres, it may also be a way to cut pollution and slow climate change.