Sustainability and Analytics: Two Sides of the Same Coin What do sustainability and analytics have in common? More than you might think. In my presentation I will explore how these two concepts are interlinked and how they can help businesses achieve better performance, innovation and resilience. I also share some examples of how companies are using sustainability and analytics to create positive impacts for themselves and the world. Whether you are a business leader, a data enthusiast or a sustainability advocate, you will find something valuable in this article.

1. The State of
Sustainability:
A Call for Action
Sustainability and Analytics: Two
Sides of the Same Coin

2. The time to act is now
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.

3. The role of Data and Processing
Data for Sustainability
Data is 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.
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.
● Education: Khan Academy uses big data to provide
personalized learning paths and feedback for students,
improving test scores by 20% on average.

4. 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.
● 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

5. Where to go
from here?

6. 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. To deal with this challenge, do as follow:
● 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.
● 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.

7. 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.

8. What you can do now to
improve your Sustainability
Transparency- ct'd
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.

9. platformeconomies.com/
sustainability
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