The Hidden Environmental Cost of Data: Minimise Your Data Footprint with Sustainable Information Management

The intersection of digital data storage and sustainability has become a growing concern for organisations as they navigate the challenges of managing increasing volumes of digital information. As the world shifts towards cloud computing, the environmental impact of data centres and their carbon footprints cannot be ignored. With data consumption and storage needs on the rise, businesses must adopt sustainable practices to mitigate their environmental impact while balancing the demands of compliance, security, and efficiency. This article explores the evolving landscape of data storage, the associated energy demands, and practical strategies organisations can implement to manage their information assets responsibly. 

Sustainable Data Storage in Focus 

I recently attended the Archives and Records Association (ARA) Conference in Birmingham in the United Kingdom. The theme of the conference this year was ‘Climate and Crisis: Tackling It Together’. This conference had a range of presentations addressing the impact of climate change in relation to recordkeeping and archives, challenges with data storage and the carbon footprint, sustainability and climate advocacy as it pertains to the management of information, records and archives.   

The topics covered at the ARA conference provided compelling insights into how organisations and information management practitioners are grappling with the ever-increasing volume of data, along with the associated costs of storage and the ongoing management of large volumes of data and information.   

For most organisations, sustainability efforts focus on strategic direction and initiatives aimed at reducing adverse environmental and social impacts. This often involves implementing energy and water conservation methods, reducing waste and increasing recycling, investing in green buildings and efficient equipment and purchasing environmentally friendly office supplies. 

Evolution of data storage 

In days gone by the focus for information managers and Information and Communication Technology (ICT) departments was to go digital and reduce the reliance on paper, automate business processes and work digitally. Many organisations have been busily digitising paper records for ease of access and for preservation reasons.   

As organisations embraced this digital world, storage of data and digital files was not perceived as a problem, storage was considered cheap so everything could be kept usually in a multitude of information repositories. These assets are utilising huge amounts of storage space, and many organisations are struggling with what to do with this data.  The value of this data is often not well understood and lacks sufficient metadata to make this data particularly useful.   

The amount of data being captured is only growing as organisations transition to online applications and cloud storage services. The impact of this is that more and more storage space is needed for an organisation’s information and data.  Technologies are evolving at a fast pace and are becoming more sophisticated. With the emergence of cloud computing, the Internet of Things (IoT) sensors, big data analytics, smart devices and software the volumes of data being retained have grown exponentially.   

Energy Demands and Carbon Footprint 

Anthropologist Steven Gonzalez Monserrate coined a wonderful phase in his article, The Staggering Ecological Impacts of Computation and the Cloud. The term used is Cloud the Carbonivore.  The cloud now has a greater carbon footprint than the airline industry.  A single data centre can consume the equivalent electricity of 50,000 homes.   

As organisations increasingly adopt cloud computing services, the amount of data stored in data centres has exploded. Data centres are now among the fastest-growing consumers of electricity. According to the International Energy Agency’s Electricity 2024 Report, data centres, along with cryptocurrencies and artificial intelligence (AI), accounted for nearly 2% of global electricity demand in 2022—surpassing the UK’s consumption and comparable to that of France. 

s data volumes continue to rise, data centres will need to expand and evolve to handle the growing demand for processing and storage. The graph below from the IEA report illustrates the projected increase in electricity usage from 2022 to 2026 across key sectors.

Goldman Sachs research in May 2024 predicts that as the AI revolution gathers steam, data centre power demand will grow by 160% by 2030. This increase in demand will drive electricity growth and as a result carbon emissions may more than double between 2022 and 2030. The following graph shows the workload demand for data centres and the power consumed. 

AI’s Carbon Footprint 

An interesting study by researchers from Hugging Face and Carnegie Mellon University offers important insights into AI’s carbon footprint. This is the first time researchers have measured the carbon emissions of AI models for different tasks, giving us a clearer idea of how much energy they use. 

The study looked at 88 different AI models across various applications and found that generating images uses the most energy, sometimes as much as charging a smartphone. It also showed that large AI models used for creating content require much more energy than smaller models designed for specific tasks. 

As generative AI becomes more popular and widely used by big tech companies, the environmental impact of AI is likely to grow as these powerful models are used more often. 

The study provides useful relative data though not absolute figures. It shows, for example, that AI models require more power to generate output than they do when classifying input.  This is a starting point as researcher Alexandra Sasha Luccioni, states, “The generative AI revolution comes with a planetary cost that is completely unknown to us and the spread is particularly indicative.” 

The Green AI Revolution in Data Centres 

While AI, particularly generative AI, is contributing to increased energy consumption due to the immense computational power required, it is also proving to be a key player in improving the sustainability of data centres. A significant shift is underway as data centres aim to meet both the rising demand for data processing and sustainability goals. To reduce their carbon footprints, data centres are being re-engineered with energy efficiency at the forefront—utilising AI to optimise operations. 

AI is playing a critical role in predicting workloads more accurately and managing energy consumption dynamically. One of the most promising developments is AI’s ability to improve cooling efficiency, which is a major contributor to data centre energy use. For instance, Google’s DeepMind AI has been used to cut cooling costs by up to 40%. 

In addition to AI-driven efficiencies, cloud providers like Microsoft, Amazon Web Services, and Google Cloud are increasingly adopting renewable energy sources to power their data centres. These tech giants have set ambitious sustainability targets, aiming to become carbon neutral or even carbon negative within the next decade. Together, these advancements demonstrate that while AI may add to energy demands, it also holds the potential to significantly reduce the environmental impact of data centres. 

What can organisations do now? 

The environmental sustainability issues associated with the processing and storage of vast amounts of data cannot be underestimated and will not be solved quickly.  However, there are strategies that organisations can embrace and implement to enable better management of information and data collected, created and stored while also managing increasing storage costs as data volumes grow and meeting regulatory obligations. 

Organisations must understand what information and data is collected and created, what information assets are held across their technology eco system, the value of the information to the organisation and the legislative and regulatory requirements that impact the access, use, security and retention of the information assets.   

It is critical that organisations consider what data and information should be retained, for how long and when it could be disposed of.  The lessons learnt from recent security breaches is that the over retention of data is a considerable risk to an organisation and its customers.  Organisations need to minimise the data they are holding.   

One of the key privacy reforms ahead for Australia will place more emphasis on organisations to establish maximum and minimum retention periods in relation to personal information as outlined in Proposal 21.7 of the Privacy Act Review Report 2022.   

This will have a huge impact on organisations to develop retention policies across data holdings to ensure that personal data is managed appropriately. Organisations should consider a holistic approach and develop and implement a retention and disposal schedule that covers all the information assets of an organisation.

What is a retention and disposal schedule? 

A retention and disposal schedule describes the business undertaken by an organisation and identifies the types of information and data created, collected and used as part of the conduct of the business. Minimum retention requirements are then applied to classes of information produced as outputs of the business functions of the organisation. The retention requirements are based on legislative and regulatory requirements, privacy justifications, business need and customer, client and community expectations.   

Retention and disposal schedules are a key control tool from a records management perspective, but the application of these tools is not just restricted to what an organisation may consider to be a record. The very nature of development of these tools – understanding the legislative environment, the business and the functional responsibilities is key in understanding the information assets created, collected and used and the value of those assets to an organisation.  

Five key initiatives for getting control of your organisation’s information assets (or minimising your data)

There is much discussion around data minimisation and what organisations must do to have better oversight and management of their information assets.   

  1. Understand your information assets. How is data collected and captured? Are you keeping the right information and data? Do you know what you should be creating? What are the risks? How will the risks be managed? In what systems are your assets captured? In what formats are the assets held? Who has access to the information and how is it used? How is the information organised? Is it tracked? From this understanding of the information and data holdings of an organisation a retention and disposal schedule and an information asset register can be developed.  
  1. Develop a retention and disposal and schedule that covers all information assets and will provide the guidance on how long assets need to be retained. This is a strategic instrument that is based on an organisations business functions, identifying information assets that are created as part of business operations. This document categorises and describes the information assets and assigns suitable retention periods such as retain permanently, destroy after a particular time frame or de-identify. 
  1. Develop an information asset register (or in the data world a data inventory or catalogue).  An information asset register (IAR) covers all forms of information assets.  This tool provides an enterprise-wide view of assets and where they are stored.  The IAR links assets to a range of metadata fields that provide an understanding of how the asset will be managed.  These fields include, information sensitivity, retention requirements, risk, identification of personal information.  More information can be found on IAR’s in this recent RKI blog.  
  1. Understand accountabilities. Determine where accountabilities lie for information assets.  Assigning responsibility to information owners, custodians and stewards for example, have important roles in ensuring data and information are collected, created and managed according to data management and records management practices and processes.   
  1. Metadata and disposal.  Metadata is key to understanding your information assets.  Metadata schemas define the creation, management and longevity of information assets and structures.  Defining metadata for retention and disposal is critical in ensuring that disposal can be implemented.  There are tools available to work with the metadata and automate the identification of assets due for disposal.   

How Recordkeeping Innovation Can Help You Achieve Data Minimisation 

At Recordkeeping Innovation (RKI), we can help you implement sustainable data and information management practices that ensure compliance, improve efficiency, and minimise data-related risks. Our tailored Retention and Disposal Schedules and Information Governance services are designed to support your organisation in reducing unnecessary data while maintaining information security and integrity. 

Whether you’re looking to develop effective data management strategies or need assistance with retention requirements, our team is here to guide you toward a more sustainable approach to information management. Contact us today to discuss how we can support your goals.

About The Author

Adelle Ford, Director of Recordkeeping Innovation Consulting, is an experienced industry expert, information management consultant delivering quality strategic advice, consultancy and services for companies operating in legislatively complex business environments. Adelle Ford has worked in the information and records management sector since 1979, having been employed in various capacities by both public and private sector organisations. Adelle has a Graduate Diploma in Data Management.

Further Reading

For more insights on sustainable data storage, explore the following articles:

Exploring the sustainability challenges facing digitalization and internet data centers

The Staggering Ecological Impacts of Computation and the Cloud | The MIT Press Reader 

The Environmental and Climate Impacts of Storing Too Much Data | AvePoint 

The Obscene Energy Demands of A.I. | The New Yorker 

How much electricity do AI generators consume? – The Verge 

Foundry (an IDG, Inc. company) • Technology Marketing Intent data (foundryco.com) 

Privacy Act Review Report | Attorney-General’s Department (ag.gov.au) 

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