The State of Sustainability: A Call for Action

Sustainability means meeting our needs without harming future generations. It covers environmental, social and economic aspects that are connected and important.

But we are not doing well on sustainability. We face many problems and risks that need urgent and collective action. Some of these problems are:

• Air pollution: Most people breathe dirty air, which kills millions every year.
• Land degradation: A third of fertile land has been lost in 40 years due to erosion, desertification and deforestation.
• Waste generation: Americans throw away a lot of organic waste that can be composted. Half a million trees are cut down every week for newspapers.
• Climate change: The world is getting hotter and hotter, which will hurt ecosystems, biodiversity, human health and livelihoods.
• Resource depletion: We use more resources than the Earth can renew by 60%. We are running out of our natural wealth.

These statistics show that we are not on track to achieve the Sustainable Development Goals (SDGs), a set of 17 global goals to end poverty, protect the planet and ensure peace and prosperity for all by 2030. No country is doing well enough to achieve them.

So we need to act now to change our course and adopt more sustainable practices in every aspect of our lives.

Sustainability is not a trade-off or a sacrifice. It is an opportunity and a necessity. It is the only way to ensure a prosperous and resilient future for ourselves and generations to come. We all have a role to play in making sustainability a reality. The time to act is now.

The Role of Data and Processing Data for Sustainability

Sustainability and Analytics are two sides of the same coin. Data is indeed essential for advancing sustainability. Data can help us measure, monitor and manage our impacts on the environment and society. Data can also help us identify opportunities, risks and solutions for sustainable development. Data can enable more informed and evidence-based decision-making and accountability.

However, data alone is not enough. We need to process data in ways that are reliable, relevant and responsible. We need to use data science techniques such as big data analytics, artificial intelligence and machine learning to extract insights and value from data. We need to use data visualization tools to communicate data effectively and engagingly. We need to use data platforms and ecosystems to share data securely and collaboratively.

Examples by sector:

• Energy: IEA uses big data to monitor and analyze global energy trends, scenarios and policies, providing authoritative data and insights to inform decision-makers and the public on energy security, sustainability and affordability.
• Transportation: Uber uses big data to match drivers and riders, reduce waiting times, and lower fares, saving 1.2 billion miles of driving in 2019.
• Agriculture: FarmBeats uses satellite data, drones, sensors and AI to monitor soil health, crop growth, weather conditions and irrigation needs, increasing crop yields by up to 30%.
• Health: HealthMap uses big data to track and visualize disease outbreaks and epidemics, alerting public health authorities and the general public in real time.

These case studies show that data and processing data can be powerful tools for sustainability. However, they also pose challenges and risks that need to be addressed. These include data quality, privacy, security, ethics, governance, bias, transparency and accountability. We need to ensure that data is used in ways that respect human rights, protect the environment and promote social justice.

Sustainability and Supply Chain Management go hand in hand

Using data can help to improve supply chains and have a positive net effect on sustainability by enabling better visibility, intelligence and adaptability across the entire network. This can improve both the economic and environmental outcomes and increase the resilience to disruptions.

Some metrics and case studies that demonstrate this are:

• According to McKinsey , supply chain management solutions based on artificial intelligence (AI) can reduce total costs by 5 to 10 percent, increase revenue by 5 to 10 percent and improve sustainability by 15 to 30 percent.
• According to Forbes , data analytics and machine learning (ML) can help to optimize material selection, packaging design, energy efficiency, waste reduction and circular economy by providing insights into the entire lifecycle of a product.
• According to another Forbes article , AI and ML can help to reduce CO2 emissions by up to 45 percent by optimizing transport routes, minimizing inventory, improving demand forecasting and increasing transparency over suppliers.

The importance of applying AI lies in that it enables processing, analyzing and leveraging large amounts of data from different sources to make better decisions and respond faster to changes. AI can also recognize patterns, detect anomalies and provide recommendations that go beyond human capability.

Lack of crucial data for Sustainability

Missing data along the supply chain can prevent companies from accurately tracking their sustainability footprints down to an article level, which can affect their reputation, compliance, and performance. To deal with this challenge, companies can do the following:

• Adopt a data supply chain management approach , which puts equal emphasis on all phases of data management, from collection to organization to consumption of data products. This can help to ensure data quality, consistency, and availability across the network.
• Implement advanced technologies such as artificial intelligence (AI), machine learning (ML), radio frequency identification (RFID), and blockchain to improve data visibility, accuracy, and security . These technologies can help to monitor and track the environmental and social impacts of products and processes throughout the supply chain.
• Collaborate with external partners such as suppliers, customers, regulators, and industry associations to share data and best practices on sustainability . This can help to create common standards, benchmarks, and metrics for measuring and reporting sustainability performance.

By addressing the issue of missing data along the supply chain, companies can not only improve their sustainability footprints, but also gain competitive advantages such as cost savings, risk reduction, customer loyalty, and innovation.

Taking action: What you can do now to improve your Sustainability Transparency

• Establishing clear and consistent metrics and standards for sustainability reporting and disclosure, such as the Greenhouse Gas Protocol or the Task Force on Climate-related Financial Disclosures . This can help to improve data quality, comparability, and transparency across the supply chain and the industry.
• Leveraging cloud-based platforms and tools to collect, store, analyze, and visualize sustainability data from various sources, such as sensors, smart meters, satellites, or third-party providers . This can help to enhance data accessibility, scalability, and security, as well as enable real-time insights and actions.
• Applying advanced analytics and artificial intelligence to sustainability data to generate insights, predictions, and recommendations for improving environmental performance and reducing emissions. This can help to optimize processes, products, and services, as well as identify new opportunities and risks. Here is a generic technical blueprint to get started.

To utilize data effectively for sustainability purposes, companies may also need to make some organizational changes, such as:

• Creating a dedicated sustainability function or team that is responsible for defining the sustainability strategy, goals, and initiatives, as well as overseeing the data collection, analysis, and reporting . This can help to ensure alignment, accountability, and coordination across the organization.
• Empowering the CIO or the chief data officer to play a leading role in driving the sustainability agenda by providing data-driven solutions, technologies, and capabilities . This can help to foster innovation, collaboration, and transformation within the organization and with external partners.
• Building a culture of sustainability awareness and data literacy among all employees by providing training, education, incentives, and feedback . This can help to increase engagement, ownership, and action on sustainability issues.

The reason for all of this is simple - at the end of the day we are talking about Change that needs to be managed .