Global climate changes caused by human activity require industry to switch to environmental tracks. At the company level, this is done using an ESG strategy. At the same time, digital technologies are required to control risks, in particular, it is necessary to analyze large amounts of data. At one of the sessions of the DataFusion conference, experts discussed what needs to be taken into account when collecting and analyzing data, what is the uniqueness of the new energy transfer and how the ESG strategy can be applied even to garbage removal from construction sites in Moscow.

Mikhail Akim, Professor of Practice at the Graduate School of Business, spoke about the role of digitalization in ESG transformation. The ESG program mainly involves large enterprises that can afford to study investments in this area. Medium-sized businesses are little involved in the transformation. 35 trillion dollars of investments is the size of the turnover of the ESG investment industry, and it will grow, because many companies want to "repaint themselves in green." At the same time, some companies are cunning by creating separate legal entities that become responsible for "dirty" production. The main company is "green" at this time. At the global level, the same thing is happening — developed countries are shifting production to third world countries. This is what can be attributed to the sharp increase in greenhouse gas emissions. At the same time, the carbon footprint of products that the EU receives, for example, is growing.

Energy transfer is a global and positive trend characterized by the development of electric transport and the growing share of renewable energy sources (RES). China is in the lead in the latter, far ahead of all countries in the world. There is also a downside. It should be understood, the Mayor noted, that renewable energy sources are good for everyone, but they create a lot of waste (wind turbine blades, solar panels) that need to be recycled — reverse supply chains also have to be taken into account. Digitalization can help track these chains.

As for forest ecosystems, their areas are decreasing today. This is mainly due to the increase in acreage, especially in poor countries. The task of feeding humanity is no less important than capturing carbon. Digital technologies can help assess the environmental footprint of individual industries and their performance. In addition, automation helps to intensify agriculture without increasing the area of land. And remote access technologies have made it possible to reduce the carbon footprint (engineers work remotely) and avoid downtime during a pandemic.

Thus, digital technologies are already having a significant effect on the implementation of ESG. The immediate effect is improved data collection, reporting and analysis affecting every operation and aspect of the business. Another possibility is the digital counterparts of companies to track the effectiveness of digital assets, predict energy use and minimize waste.

Andrey Osiptsov, Professor and director of the Project Center for Energy Transition and ESG (Skoltech), showed the importance of data in the ESG program using the example of a specific case. There is a general consensus among scientists that human influence has led to a warming of the atmosphere. One of the dangerous consequences of rising temperatures on the planet is an increase in extreme, catastrophic natural phenomena. The energy transitions of the past were caused by the inefficiency of existing technologies. But the situation is different now. The fourth energy transition is not caused by insufficient efficiency, but by the effects of climate change.

The introduction of a carbon tax within Russia will lead to a doubling of the cost of heat supply, said Osiptsov. But for the poor, the cost increase will be catastrophic. Therefore, it is important to create conditions in which companies do not shift costs to end users — this is precisely the task of scientists.

The task of the case at Gazpromneft, which Osiptsov told about, was initially far from ESG: it was necessary to collect and digitize data on formations, wells, hydraulic fracturing and production. And then, based on the data, to propose a recommendation system for optimizing hydraulic fracturing — to maximize production. The key point here is that data can solve many problems, regardless of the specifics of the industry sector. Then the task of reducing the volume of materials used, the carbon footprint and the concentration of chemicals was added. The developers collected data from seven internal corporate sources and proposed a database structure. Access to the integrated database was unprecedented. As a result, over four years, the developers have analyzed thousands of wells for hundreds of parameters, giving recommendations for optimizing technologies. Therefore, the main thing is the data infrastructure.

Nazar Sotiriadi, Executive Director of the Integrated Risk Management Department (Sberbank PJSC), spoke about the importance of choosing the right risk analysis horizon. The main problem of risk analysis is the fundamentally incorrect scale of assessments, the horizon. If you look at how ESG risks work in the fundamental theory of macroeconomics, then the quality of the country's economy is directly determined by the state of households. The health of the population, labor efficiency, and so on are the foundation of everything, since it is households that own resources. Most of the people who make decisions on the implementation of ESG work without the necessary information and at the wrong scale. An example of such a case is the "sparrow wars" in China in 1958.

If you look at the statistics of E-risks, you can see that over the past 50 years, the number of incidents of physical climate risks has increased 4.5 times. The S-risks include the aging of the working—age population - there are more and more pensioners per citizen. 

There are two main problems. Firstly, there is a lack of data and methodology, a scientific approach, and secondly, a shortage of domain expertise. Any modeling requires a naturalistic model, that is, specialists who will understand what is being modeled. Using the example of the forecast of the occurrence of fires, it was found out, for example, that it is better not to carry it out at all. The fact of the fire itself does not particularly interest us, it is more important to analyze the pre-fire situation, which will allow us to use resources.

"We have developed a rule of thumb for ourselves: if you cannot describe the economics of the result, then the task is at another hierarchical level of the system. Using the example of fires: if, after predicting fires, we can specifically say who will spend money and who will earn, then the forecast makes sense. If the risk event is an increase in temperature in the region, then it is not at all easy to describe unambiguously and simply how this will affect consumers of products or labor productivity. Therefore, we will have to move to another hierarchical level," Nazar Sotiriadi explained in more detail.

Alexander Filatov, Head of Data Management in Distributed Computing Networks (Moscow Department of Information Technology), spoke about the impact of risks at the city level. As is known from system analysis, each large task is divided into several small ones. The ESG agenda can be applied in a variety of areas: optimization of transport emissions, monitoring the use of infrastructure for people with limited mobility, monitoring the use of resources, garbage disposal in housing and communal services, monitoring air quality in certain areas of the city, and so on. In Moscow, 8.5 million square meters of real estate were built in 2020. Such a huge construction site creates a lot of waste, and of the 3rd and 4th class of hazards. When transporting them in open bodies, there is a risk of loss of these wastes, therefore they need to be covered with soil. Special control over garbage removal from the construction site includes photographing the awning by the driver, which he uploads to a mobile application. The AI then recognizes the awning in the photo. If the awning is installed, a command is given, and the barrier opens. This system has been tested on 66 thousand flights. The accuracy of the model was 80%, completeness — 90%, and this means that it can be applied in practice. Another case related to waste transportation is predicting the success of flights based on 16 parameters. Among them: coordinates, weight of waste, the fact that the car is registered in different systems, etc.

"The implementation of ESG transformation at the city level can go in two opposite ways: the development of top-level strategies or the solution of specific everyday tasks, which gives results in a short period of time. The second way does not require large financial investments," Alexander Filatov summed up.

Anna Kulashova, Director of the Center for Training in Game Design and Development at the FPMI MIPT, spoke about the role of universities in ESG. Approximately five Sustainable Development Goals relate to decarbonization, and seven relate to social issues. It is necessary to maintain a balance between the interests of people, the planet and profit, not focusing only on the last task. The main prerequisites for transformation are the growth of population and consumption with a shortage of resources (and their unequal distribution). Solving the problems associated with these factors stimulates the development of a closed-loop economy in which the product of a socially responsible enterprise is tracked from natural raw materials to collection for waste and recycling. With this approach, resources remain in the economy for as long as possible, and new business models are created. Therefore, knowledge of AI mathematics alone is not enough — you need to understand legislation, trends in society (demographic and public sentiment). Today, the following tasks can be identified that AI can solve: combating poverty and food shortages, personalized social services, preventing corruption, developing sustainable agriculture, preventing epidemics, and developing health and diagnostic systems. All these applications fall outside the scope of the ESG agenda. Accordingly, new areas of research are emerging: ESG as an investment mechanism, information as an element of socio-political impact, etc. The role of universities is key here. Specialists from the fields of politics, economics, sociology, technology, law and ecology will ultimately help solve the problems of sustainable development. As a result, their training will be reformatted into solving applied tasks of enterprises, building the most optimal risk models and finding a balance to ensure sustainable development.