Before you start collecting and analyzing data, you need to define your goals and scope for your sustainability reporting and disclosure. What are the key issues and topics that matter to your business and your stakeholders? What are the standards and frameworks that you want to follow, such as the Global Reporting Initiative (GRI), the Sustainability Accounting Standards Board (SASB), or the Task Force on Climate-related Financial Disclosures (TCFD)? How do you align your reporting and disclosure with your sustainability strategy and objectives? By answering these questions, you can narrow down your focus and prioritize the most relevant and material data.
I've always been a big believer in leveraging multiple scenarios in any business analysis - the more scenarios considered the higher likelihood of understanding, the extent of future possibilities and as a result reaching the best possible decision. We have certainly seen an increasing number of "100 year" storms, floods, earthquakes, fires, etc. in just the past 5-10 years which would certainly be on the extreme end of most environmental scenario analysis, and yet may be weighted higher than otherwise into the decision making process due to the high risk potential. Our modeling and analysis capabilities seem to grow overnight and we need to continue to leverage them as much as possible to continue to understand the potential outcomes.
Assessing the feasibility and profitability of renewable energy opportunities in various markets involves evaluating factors like resource availability, regulatory support, and local demand. We analyze the potential for solar, wind, or other renewable sources, considering geographical conditions. Government policies and incentives impact feasibility. Market research helps gauge consumer interest and competition. Financial modeling assesses project profitability, factoring in installation costs, maintenance, and potential revenue. By scrutinizing these aspects, we make informed decisions on pursuing renewable energy projects in diverse markets.
This will be focused on extended producer responsibility and all of the ESG laws being passed in the world. The challenge is the scope keeps changing as these laws are created and agreed upon.
You are absolutely right, before starting to work on your sustainability reporting, it is very important to understand the current scenario, your stakeholders, their needs and expectations, materiality topics, and what matters the most to excel in it.
Integrating data and analytics into sustainability reporting is transformative for organizations seeking to communicate their sustainability efforts effectively. Leveraging advanced analytics, I derive meaningful insights from complex datasets. This not only enhances the accuracy of reporting but also empowers organizations to make strategic decisions rooted in data-driven sustainability practices. By adopting best practices for collecting, analyzing, and presenting data, organizations can strengthen their sustainability reporting, providing stakeholders with transparent and credible information.
Once you have defined your goals and scope, you need to collect and validate your data. This involves identifying the sources and methods of data collection, such as surveys, interviews, audits, sensors, or databases. You also need to ensure the quality and accuracy of your data, by checking for errors, inconsistencies, gaps, or outliers. You may need to use data cleaning, verification, or normalization techniques to improve your data quality. Additionally, you need to document your data collection and validation processes, such as the definitions, assumptions, calculations, or limitations of your data.
The possibilities provided by Data analytics and Artificial Intelligence are undeniable. They are a game changer in the collection/visualization purposes. From my previous experience, one of the companies was utilizing Machine Learning (ML) to detect peak energy consumption hours enabling Heating, Ventilating, and Air conditioning (HVAC) systems to be adjusted properly. Eventually, the company managed to reduce its energy consumption by 12-15% in a year. Thus, the utilization of data analytics should be thoroughly evaluated within a firm to reach desirable and tangible results.
Using a spec data like Specright will be a game changer for this step. You can actually see your results in real time to check your progress daily. This will save you the surprise at the end of the year.
Sustainability related data is critical to making progress in our world’s highest emitting sectors. Collecting and validating data ensures that organizations can monitor and evaluate their actions and progress towards reaching internal and external sustainability goals. Accurate data is foundational to all sustainability reporting and disclosure decisions because, as we say frequently at the Global Network for Zero: “What isn’t measured can’t be tracked.” And when data is not tracked and verified, we end up exactly where we are now – in a net zero no man’s land. Once an organization has collected and analyzed their data, we encourage clients to commit to publish their transparent data annually and share their ROI story.
I have a slightly different view compared to this sequential approach to reporting where you set your goals, get the data, visualise and disclose. Reporting standards are just frameworks to be able to compare different organisations in a meaningful way - you need to structure your raw data and reporting in a highly configurable way, so that you can seamlessly make it flow into reports in the way you want and in the way that the reporting framework demands. Reporting standards keep changing all the time, so it's essential to have the right underlying data and the capabilities to slice / dice / format them into desirable outputs. Too often reporting is treated like a standalone project that comes once a year - this leads to rework!
Gather relevant data from reliable sources and ensure its accuracy through validation processes. Accurate data is crucial for credible and effective sustainability reporting.
After you have collected and validated your data, you need to analyze and visualize your data. This involves using data analysis tools and techniques, such as descriptive, inferential, or predictive statistics, to extract insights and trends from your data. You also need to use data visualization tools and techniques, such as charts, graphs, maps, or dashboards, to present your data in a clear and engaging way. You may need to use different types of data analysis and visualization depending on your audience, purpose, and message. For example, you may use a pie chart to show the breakdown of your greenhouse gas emissions by source, or a line graph to show the progress of your energy efficiency targets over time.
- largely sustainability data are of 02 type 1. Quantitive: Majority E and some S 2. Qualitative : S and G - Quantitive data analysis add value once you able to notice anomalies and gaps when you compare with benchmark - Graphical representation should tell a story when it comes to qualitative information - Sharing a framework should include how sustainability is integrated with vision and culture of the company So data has more power, once we know how to implement!
Após a coleta e validação dos dados, a análise eficaz é o próximo passo para transformar números em insights valiosos. Técnicas de análise, como estatísticas descritivas e preditivas, ajudam a identificar tendências e padrões relevantes. A escolha da visualização correta, seja gráficos de linha para medir progresso ou gráficos de pizza para divisões de emissões, é essencial para comunicar informações de maneira clara e impactante. Adaptar a apresentação conforme o público garante que os dados sejam compreendidos e possam influenciar decisões estratégicas. Um relatório visualmente envolvente reforça a credibilidade e o impacto das suas descobertas.
Use data analytics tools to examine trends, identify patterns, and extract insights. Visualize the data through charts, graphs, and dashboards to make it understandable and actionable.
I am a big fan of using established, market leading data analytics focused tooling, such as Alteryx. There is also a real challenge when dealing with both structured and unstructured data, so whatever tooling is used needs to be able to handle both. Only by consolidating, cleaning, preparing and correctly processing the data, to a pre-defined and agreed process, will be the best results be achieved. The visualisation can then follow, Alteryx Insights, Tableau and typically PowerBI can all be useful when visualising and we use extensive graphing techniques when dealing with big data and trying to get insight into supply chains.
Isso envolve o uso de ferramentas e técnicas de análise de dados, como estatísticas descritivas, inferenciais ou preditivas, para extrair insights e tendências de seus dados. Você também precisa usar ferramentas e técnicas de visualização de dados, como tabelas, gráficos, mapas ou painéis, para apresentar seus dados de forma clara e envolvente. Talvez seja necessário usar diferentes tipos de análise e visualização de dados, dependendo do seu público, finalidade e mensagem. Por exemplo, você pode usar um gráfico de pizza para mostrar a divisão de suas emissões de gases de efeito estufa por fonte ou um gráfico de linhas para mostrar o progresso de suas metas de eficiência energética ao longo do tempo.
Finally, you need to report and disclose your data. This involves preparing and publishing your sustainability report and disclosure documents, such as annual reports, sustainability reports, ESG reports, or integrated reports. You also need to communicate your data to your stakeholders, such as investors, customers, employees, regulators, or media. You may need to use different formats and channels depending on your stakeholder preferences and expectations. For example, you may use a PDF file to share your full sustainability report, or a web page to highlight your key sustainability achievements and indicators.
By using data and analytics to support your sustainability reporting and disclosure decisions, you can enhance the credibility, transparency, and value of your sustainability performance and impact. You can also identify opportunities and risks, benchmark your performance against peers and standards, and drive continuous improvement and innovation for your sustainability goals.
Data management is crucial. To accurately disclose necessary information, it’s essential to thoroughly understand and analyse your data in accordance with relevant reports and regulations. Utilising tools like Tableau can help visualize and manage this data effectively within your organisation and teams. It's also vital to assemble a diverse team including experts in technology, accounting, sustainability, and law to ensure comprehensive compliance and accurate disclosure. Significant regulations, such as the CSRD and the forthcoming CS3D in Europe and the UK, present substantial challenges that require robust data management and interdisciplinary collaboration to address effectively, don't leave anyone behind.
Sustainability reporting is like that story, but with facts and figures to back it up. Just like any good story needs details, data helps paint a clear picture. This could be in energy use, water consumption, waste produced, employee diversity numbers, and more. Data on its own can be overwhelming. Imagine turning those ingredients into a delicious meal! Analytics can help you see trends, identify areas for improvement, and track your progress over time. Imagine setting a goal to reduce waste by 10% in a year, instead of just saying "we want to waste less.
A divulgação dos dados de sustentabilidade é a etapa crucial para garantir transparência e credibilidade. Publicar relatórios como ESG, anuais ou integrados exige precisão e uma comunicação estratégica adaptada ao público-alvo. Utilizar diferentes formatos, como PDFs detalhados ou páginas web interativas, garante que informações relevantes cheguem aos stakeholders de forma clara e acessível. Ao basear suas divulgações em dados e análises robustas, você não apenas aumenta a confiança dos investidores e reguladores, mas também identifica oportunidades para impulsionar melhorias contínuas, alinhando sua empresa às melhores práticas e inovações em sustentabilidade.
GREEN scorecard in business Functions- Management reciews. To walk the talk, its not just about reporting but also adding actionable KPIs. Beyond Financial performance its required by management to include Green KPIs (reporting and targets) in function/ department process and reviews. Eg- Scope 1- process experts reporting emission values, and reduction targets. Scope 2- electrical department/ function reporting CO2e of energy usage and improvement targets. Scope 3- procurement reporting product EPD inclusion and review process. And binding these reported KPIs to overall company performance.
Prepare your sustainability reports by presenting the analyzed data in a clear and transparent manner. Ensure compliance with reporting standards and communicate your findings to stakeholders effectively.
Scope 1 and scope 2 and scope 3 reporting will be here soon and will provide a great starting point for companies looking to improve their sustainability. It will also provide a scary time for companies who have been avoiding the move towards sustainability.
Don't forget about collaboration, materiality, and integrity. Engage stakeholders throughout the data collection process to ensure their concerns are reflected. This builds trust, relevance, and a shared vision for progress. Continuously refine your materiality assessment to align with evolving stakeholder expectations and regulatory requirements. Prioritise data quality through validation processes and transparent practices. Credible data builds stakeholder confidence and positions your organisation as a sustainability leader!
Model different scenarios to understand the potential impact of various sustainability strategies. For instance, assess the effects of adopting renewable energy sources or implementing waste reduction programs.
Data analytics empowers organizations to extract meaningful insights from vast datasets related to their environmental, social, and governance (ESG) performance. By analyzing diverse metrics such as energy consumption, carbon emissions, and stakeholder engagement, organizations can measure current performance, forecast future outcomes, and identify areas for improvement. Data analytics also enables benchmarking against industry peers and best practices, providing valuable context for assessing performance and driving continuous improvement.
Our clients are facing some real challenges with Scope 3 emissions. Sourcing and reporting the data is proving difficult. Missing data (and the process of proxying to fill in the gaps) will only be supported by regulators for so long, so expect fines and/or capital charges (in the case of the Finance industry) if you have large, material gaps in your data. When modelling and driving strategy be aware that an incomplete data set can impact results and outcomes. Sounds like common sense, but at this point in the ESG journey, understanding the data gaps and their impact can be as important as the data that has been sourced.