How can you measure the circularity of your business model with data analytics?

Utilizing the power of data systems significantly enhances the ability to assess the circularity within a business framework. Market-available platforms, like SAP, offer tools for companies to track and manage the lifecycle journey of materials and products. For instance, a company manufacturing electronic devices can use data analytics to monitor the % of recycled materials used in production, the efficiency of their take-back program for end-of-life products, and the success rate of refurbishing or recycling these products. By analyzing this data, the company can identify opportunities to increase the use of sustainable materials, enhance product design for easier recycling, and improve customer participation in return programs.

Every supply chain originates, and terminates in the earth. Being able to see this view offers a strategic view on how to provide the greatest value in the value stream and how to fend off many risks.

- Benefícios ambientais: A circularidade pode ajudar a reduzir a poluição, o consumo de recursos e as emissões de gases de efeito estufa. - Benefícios econômicos: A circularidade pode gerar novas oportunidades de negócio, criar empregos e aumentar a competitividade das empresas. - Benefícios sociais: A circularidade pode contribuir para a construção de uma sociedade mais justa e equitativa.

Measuring circularity allows assessment of business model performance, impact, and potential benefits across environmental, social, and economic aspects. By tracking data on material flows, energy use, waste generation, and value creation, businesses identify efficiency, innovation, and resilience opportunities. Communicating circular achievements to customers, investors, and regulators showcases sustainability commitment.

By quantifying the circularity of a system or process, organizations can set meaningful targets, benchmark performance against industry standards, and communicate their sustainability efforts to stakeholders. Additionally, measuring circularity can uncover inefficiencies in resource use. In the plastic industry, measuring circularity can help quantify the impact of recycling efforts. For example, by tracking the percentage of recycled plastic used in manufacturing processes, companies can assess their progress towards circularity. Metrics like the recyclability of products, the efficiency of recycling processes, and the amount of plastic waste diverted from landfills can also provide insights into the circularity of a company's operations.

Life Cycle Assessment: Using life cycle assessment (LCA) tools and methodologies, you can evaluate the environmental impact of your products and services across their entire life cycle. By collecting data on energy consumption, emissions, and resource use at each stage of the product life cycle, you can identify areas for improvement and design more sustainable products. Circular Economy Indicators: There are various circular economy indicators that can help you assess the circularity of your business model, such as resource productivity, material efficiency, and circular economy performance.

Sure. Here's how you 'could' go about it: Establish Sustainability Context -->Identify carrying capacities of various capitals (natural, social, human, manufactured, and financial) that your business relies on --> material flow data collection -->lifecycle analysis --> resource efficiency metrics -->circular design parameters --> Supply Chain Sustainability Metrics --> Stakeholder engagement --> Economic Impact Analysis. Alternatively, traditional metrics such as sheer output and short-term profitability do not account for long-term resource depletion or waste generation. So collect data that informs a transition from a linear 'take-make-dispose' model to a more circular one.

Let me be honest here: Collecting data for circularity is tedious, if it doesnt seem so then probably you are doing it wrong. The very basic example is if a product is build for repair the research is still figuring out whether that data can be reported well in LCA's or not. Considering that we have an emerging concept called double materiality. So there are ideally two ways to collect the data: Using estimates which are very close to real values or using real data where ever you think it isnt quite tedious

Most processes do not collect data about waste. This is critical to understand circularity. Simply, what is discarded from the value stream as waste?

- Taxas de reutilização, reciclagem e compostagem: Medir a porcentagem de materiais que são reutilizados, reciclados ou compostados em vez de serem descartados. - Extensão da vida útil do produto: Medir o tempo que os produtos duram antes de serem descartados. - Eficiência do uso de recursos: Medir a quantidade de recursos utilizados por unidade de produção.

To analyze circularity data, you can use a variety of tools and techniques. For quantitative analysis, spreadsheet software can be used to calculate metrics and perform statistical analysis. Data visualization tools like Tableau, Power BI, or Google Data Studio can help create visualizations to understand trends and patterns in the data. For qualitative analysis, tools like NVivo or MAXQDA can be used to analyze textual or interview data related to stakeholder engagement or regulatory compliance. Life cycle assessment software such as SimaPro or openLCA can help evaluate environmental impacts throughout a product's life cycle.

There are a lot of tools which helps us in analyzing the data and take the best possibel decision. I would recommend to perform initial LCA on MS EXCEL and analyze it there. Though most of the companies use Open LCA, PACE and much more which are entirely based on ISO 140001 - but it is always better to start from scratch

Software de análise de dados, indicadores de desempenho circular, modelos de simulação. Ellen MacArthur Foundation, Circle Economy, World Economic Forum

The quality of data has become increasingly relevant in organizations, as a result of which there is an increasing need to obtain information with reliability and integrity. Artificial intelligence is well used to help with this.

Analyzing the circularity of a business model involves using methods and tools like circularity indicators (e.g., circularity rate), frameworks (e.g., Circular Economy Monitor), and dashboards (e.g., Circulytics). These tools quantify circularity, define dimensions and criteria, and provide visual displays for analysis. By utilizing such resources, companies can evaluate their circularity and identify areas for improvement in their business models.

While interpreting the results of a circularity assessment, make it a point to include the sustainablility of operations with respect to the people involved. An organization is its people, and the actions of the one affect the actions of the many. Inculcate holistically sustainable practices in the workplace and encourage your employees to continue this trend at home and anywhere outside the workplace as well. Actions as small as discouraging littering one's desk and proper disposal of wastes can have a large ripple effect.

Analisar os dados coletados e identificar os principais indicadores de circularidade. Comparar os indicadores com benchmarks do setor e identificar áreas de melhoria. Utilizar os dados para identificar oportunidades de otimização de processos e desenvolvimento de novos produtos e serviços. s.

Interpreting data involves understanding your business model's circularity strengths and weaknesses compared to benchmarks. Consider data reliability, accuracy, representativeness, and relevance. Ask: Is the data actionable and useful? Recognize limitations and uncertainties, ensuring contextual understanding. This critical analysis informs strategic decisions for enhancing circularity.

To enhance data for circularity initiatives, prioritize quality, quantity, and frequency of collection. Rely on standardized, verified sources and advanced analysis techniques. Validate results for informed decisions. Use data to set goals, monitor progress, and engage stakeholders, fostering innovation and adaptation in your business model.

Bring the collection of the data closest to the measurement of the data, which will improve its quality. This is no small feat as it invokes all kinds of vulnerabilities about transparency.

Analisar os processos da empresa para identificar áreas onde o uso de recursos pode ser otimizado. Implementar medidas para reduzir o desperdício e aumentar a eficiência.

The title is a bit of a misnomer - it is not the circularity of the business model, but the circularity of the value stream that should be measured. The business model is part of the value stream.