Can data analytics help mitigate climate change?

The Report of the IPCC released on the 7th of August, 2020, pronounced a ‘Code Red for Humanity’ making a definitive statement compelling every entity to act to battle climate change. It says with high certainty that to stabilize the climate, carbon-dioxide emissions must reach net zero, and other greenhouse gas emissions must decline significantly.

How does humanity get to the point of net zero and how do all corporations combinedly activate themselves to contribute towards this? Here’s a quick dekko at how technology interventions can help by harnessing the power of data and analytics to understand, manage, and subsequently report and track “Mission Net Zero”.

Here are the various ways data and analytics can help ameliorate climate change:

Net zero emissions
What an organisation can measure and analyse, it can manage. So, employing data collection and analytics to track carbon emissions so that they can be reduced through deliberate changes in operations, policies, devices and machinery, systems etc. is essential to realising positive climate change contributions and achieving carbon neutrality.

According to Franck Fourniol, Senior Policy Advisor (Data and AI) at the Royal Society, “Digital technology can help us do things differently and orchestrate the transition to a low carbon society in areas like logistics, consolidating deliveries and ensuring that fewer vans are on the roads. There are sensors to enable a circular economy and to identify, track and trace materials. There's also digital twin technology to reduce emissions, help increase energy input by as much as 20% and set up feedback loops to help predict maintenance requirements. Digital twins can also be used for sectors, such as food, to understand the impact of farming on system resilience.” Much of this digital technology gathers data applies analytics to it to provide solutions towards Net Zero.

It would take a wide array of data and analytics backed multi-pronged financial, policy and energy management measures to get on track by 2030 to achieve net zero emissions by 2050.

Reduction in energy consumption
A multitude of measures and tweaks in operations go into minimizing power consumption by industry, government bodies and other organizations. Recording consumption closely (with the help of meters), and then analyzing the data is imperative to minimizing consumption whether through efficiency measures, introduction of energy efficient equipment or processes.

Data analysis can also throw up new potential areas for pruning demand that add up to shrinking organizational carbon footprint too.

Adopting renewable energy
There are now several renewable energy options available that are not only technologically more mature than 10 to 15 years ago but also more economical. Solar energy can be harvested anywhere there is sunshine and space. Hydropower, solar, wind, biomass, geothermal biofuels etc. constituting modern renewable sources or energy and traditional renewables such as wood, animal waste and traditional charcoal constitute only 22.8% of all the energy used leaving a large potential for adoption.

There are certain challenges with adopting renewable energy sources like wind and solar power as they tend to be highly variable and not accurately predictable in some parts of the world. This can be addressed to a large extent by ML, IoT technologies and of course, data analysis.

Forbes Magazine aptly notes about data on resources used, waste generated and renewable energy that “…organizations can reduce their carbon footprint by utilizing sensors in their built environments to keep track of carbon emissions. Similar IoT sensors can also monitor the amount of waste generated and the energy consumed. When it comes to renewable energy assets like wind turbines, unstructured data can be pulled directly from these sources into the cloud and, utilizing predictive analytics, turned into real-time, actionable intelligence.”

Reduce waste and obsolescence
Waste although significant in terms of carbon and carbon equivalent emissions is either neglected or well recognised for its impact on climate change. Waste could be material or energetic but ultimately it converts to the amount of GHG emissions thereby contributing to climate change. It is something that can be managed and minimized.

Opting for sustainable suppliers
To truly become sustainable, an organization needs to make sure it’s suppliers too are sustainable. This involves being able to have information therefore reporting by the suppliers on various parameters pertaining to legal compliances, human rights and environmental benignity. This information is easier to analyze in the form of data and if present for a sufficient period.

“Big data analytics (BDA) technologies have the capability to continually analyze data and share results in real time to help generate new insights and make decisions to solve complex problems across the supply chain. The application of BDA is likely to result in improved operational performance through accurate and faster decision making within the supply chain, especially when there is access to real-time data. BDA can drive efficiency and effectiveness in supply chain management in terms of improved demand management, faster new product development, better supply chain risk management, better supplier management and development of efficient and robust supply chain designs, thus supporting the sustainability agenda”.

Carbon trading
Carbon emissions trading schemes for carbon dioxide and other greenhouse gases are an approach to limit climate change by creating a market with limited allowances for emissions. The market is heavily data dependent taking in account various factors. ICIS (Independent Commodity Intelligence Services) uses data analysis to offer services to its clients on Market analysis, price forecasts, data and news enabling them to make better trading decisions. The service uses over 2 million data points to model, formulate and provide accurate insights.

Compliance to ESG norms
Environmental, Social and Governance (ESG) are a broad set of performance metrics to measure compliances of companies towards social and environmental factors. ESG disclosures and compliance has also become a critical decision point in the investment process at any major financial institution.

Increasingly, the compliance to Environmental, Social, and (Corporate) Governance regulations has grown to become an eliminating factor for transactions and selection of partners. Data collection and analysis then lends transparency and the ability to monitor compliance internally before being audited by stakeholders. Applying analytics to data also helps organizations to go beyond compliance, set bigger goals and keep on track to achieving them.

It wouldn’t be wrong to thus conclude that collecting the right quantity and quality of data and subsequently analysis of it, is the heart of managing carbon neutrality and taking responsible actions for our next generations through

Predictions – climate forecasts, risk pre-emption
Insights – Deeper understanding of resource use, carbon emissions, energy consumption, waste etc. Monitoring – Give ability to closely watch various crucial parameters relevant to carbon and GHG emissions. A powerful solution like Eka’s sustainability reporting solution, can assist companies in carrying out all the above functions, from predictions, to insights, dashboards and finally monitoring and providing risk alerts, will aid the C-Suite and decision-making members of organizations to ensure a sustainable future for the company and its stakeholders.

-- Ms. Shuchi Nijhawan, Chief HR Officer & Chief Sustainability Officer, Eka Software Solutions.