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thematicratings

Thematic benchmarks and ratings: an important tool for investors and companies

The ubiquitous influence of ESG factors has been present in the investment world for a long time now. However, the recent spur in the awareness and acceptance of the importance of ESG factors for companies and investors has led to a surge in thematic ratings and benchmarks. Some of the most valued benchmarks are Access to medicine, Access to nutrition, Corporate Human Rights Benchmark (CHRB), and Know the Chain. Investors and companies use these benchmarks to take informed decisions. Since, most of these ratings/benchmarks are developed by non-profit organizations, there is a constant pressure of optimizing their spending on research. Therefore, partnering with specialised research firms could provide them quick access to skills and at the same time make their research processes lean and efficient.

The need and opportunity for transparent and trusted ratings and thematic benchmarks will continue to intensify with the rapid growth of ESG based investing. Some of the successful names are:

1. Access to medicine Index

The Index analyses 20 of the world’s largest research-based pharmaceutical companies on how they make medicines, vaccines and diagnostics more accessible in low and middle-income countries. It is a product of two years cycle including the review of results of previous cycle, consultation with expert stakeholders to improve the methodology for the next cycle, data collection, verification and analysis.

2. Access to nutrition Index

The Access to Nutrition Index (ATNI) rates 20 food and beverage manufacturers´ nutrition- related policies, practices, and disclosures worldwide on a recurring basis with an objective ‘Spotlight Indexes’ that score and rate the ten largest Food & Beverage manufacturers in each Spotlight Country. Methodologies for the Spotlight Indexes are adapted to fit national realities and give insight into how companies perform in specific markets.

3. Corporate Human Rights Benchmark

The Benchmark provides a comparative snapshot year-on-year of the largest companies, looking at the policies, processes, and practices they have in place to systematise their human rights approach and how they respond to serious human rights allegations. This is to prevent adverse impact of competitive nature of the market on the workers. The benchmark ranks 98 of the world’s largest publicly traded companies, from 3 sectors (Agricultural products, Apparels and Extractives), on 100 human rights indicators.

4. Know the chain

Through benchmarking current corporate practices and providing practical resources that enable companies to operate more transparently and responsibly, KnowTheChain drives corporate action and investor decisions in order to understand and prevent forced labor risks within their global supply chains. Know the Chain published its second set of benchmarks in 2018 covering more than 120 companies. Their benchmarks are Information and Communications Technology, Food & Beverage and Apparel & Footwear.

5. Fair Finance Guide International

The Fair Finance Guide International coalitions have developed methodology to asses and monitor bank policies and practices towards social, environmental, and human rights. These are used for communicating with the banks, informing the public and for better democratic oversight of the financial institution. There methodology covers 23 themes/sectors & over 422 international standards and is regularly updated using the experience and expertise of all coalition members worldwide. In 2017, policies of ninety-five financial institutions in nine countries have been assessed against this methodology and over 45 case studies have been published, in the countries where a FFG operates, comparing policies with practice.

These ratings have evolved to become an indispensable tool for investors as they provide a proxy for a company’s external costs and benefits based on rating and ranking of theme specific performance or/and multi-theme composite performance. With this critical analytical information, investors can spot best performers with better risk management towards current and future regulatory, physical, human, and other risks arising from ESG factors like carbon control, minimum wage laws, etc.
Further, the reputational and competitive advantage of these ratings and benchmarking motivate companies to improve strategies towards various issues. Thematic benchmarks and ratings could help companies be more aligned with the urgent global sustainability agendas

These benchmarks are mostly funded by NGOs or governments. Due to limited funding available, these organisations are under constant pressure to optimize research and expand coverage. They often lack other reporting skills to present their findings in the most effective format for investors, companies, and other stakeholders. Hiring an external partner that can offer reliable, innovative and cost-effective research support, that can go a long way in dealing with some of the obvious challenges such as seasonality of research, expanding coverage, and optimize costs. At Sustainometric, we help rating/benchmarking organizations to improve research processes by:
Building automation;
Designing dashboards for data dissemination for a diversified set of audience;
Data collection and analysis.

For more information, please contact: k.mishra@sustainometric.com

esgautomation

ESG research and state of automation

As the adoption of sustainable investments is on the rise, ESG data and the means to harness it, has become a must-have for ESG investors and index providers. In the quest of gathering quality and comparable data, investors and index providers are seeking integration of machine learning into the data collection process. However, the state of automation is not fully matured in this area due to various limitations. Nevertheless, there are certain possibilities for small automations. Individually these automations can bring small efficiencies however collectively and on a large scale it can lead to substantial savings in costs and improves data quality.
The cost of gathering and analyzing ESG data is a major barrier to using ESG information for investment decision-making. Therefore, the industry is looking out for solutions that can make ESG research more efficient, affordable, and scalable. Many companies are focusing on machine learning to capture the most structured reported numbers. However, as of now, even the ones who are claiming to have developed machine learning, still spend lot of manual time in processing ESG data. Nevertheless, if successfully implemented this could make the research affordable for all.
There are certain challenges in developing automation tools for ESG data:

1. Unstructured/Incomplete data:

Unstructured or incomplete data that are often incomparable across firms, industries, and sectors. Unstructured data include texts, pictures, multimedia content, online reports/presentations, etc. Collating data of such different types without manual work is currently not possible. Moreover, the data is also often found incomplete for automated collection and analysis.

2. Irregular reporting by companies:

Different companies follow different cycles of reporting including annual reporting, biennial reporting, triennial reporting as well as irregular reporting of quantitative data. This makes extraction and storage of data in automated matrix difficult.

3. Complexity of Data:

Data is often not reported in units and metrics required for analysis. This compels some level of manual work in analysis. Therefore, complete automation is difficult. For example, as Health & safety KPI, some companies report LTIFR, some report loss time injuries, some report total injuries, etc. To enable comparison across such companies, certain assumptions and calculations must be made manually.

4. Qualitative Analysis:

A significant part of the analysis is dependent on the qualitative data available. With multiple keywords for a particular aspect, automation becomes very difficult as it would not only involve extracting all the information with the relevant keywords but also sorting through this information to derive a conclusion.

5.Reporting based on different reporting instruments:

There are more than 400 mandatory and voluntary reporting instruments, and automating comparison of ESG performance of companies, that follow different instruments, is difficult.
Nevertheless, as sustainability reporting matures, the ease of collecting and analyzing ESG data will improve. This will also enable sophisticated solutions for automation of collecting and analyzing ESG data. Till we reach there, there are certain possibilities for small automations. Individually these automations can bring small efficiencies however collectively and on a large scale it can lead to substantial savings in costs and improves data quality. For example:

  • Automated trend calculation for various sets of quantitative indicators.
  • Automated graphical presentation of KPIs.
  • Automated data conversion from one unit to another.
  • Automated normalization of data to make it comparable over the years and with other companies.
  • Automated linking of quantitative data on two different metrics to calculate ratios, percentages etc.
  • Automated comparison of company’s performance with policy goals like the SDGs to understand the progress towards them and to identify areas that need focus in order to avoid current/future regulatory risks.

Studies show that the next stage in ESG research process would be to study the causal correlation on how previously distinct strands of ESG data and analysis relate to or reinforce performance in each other. With the above automations in place at this point of time, implementing the emerging stage would also be easier in the future.
At Sustainometric, we focus on understanding clients’ current research processes to make it lean, efficient, cost effective, and scalable. To know more about us, please contact : hello@sustainometric.com

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