The Environmental and Climate Impacts of Storing Too Much Data

When I was at university (let’s not discuss how long ago that was), I worked in an organization that was trying to go paperless. Spoiler: It didn’t work. Part of the business driver for this initiative was the desire to reduce the environmental impact of storing all the paper. However, in the push to move to a digital environment, almost no consideration was given to the environmental impact of this change.

In today’s digital age, we don’t hear much about organizations trying to go paperless (although many continue to live in a hybrid environment). What we do hear about is the exponential growth of data and information and how this has become a double-edged sword. While data and information drive innovation and efficiency and help us make good decisions, the environmental and climate impacts of storing vast amounts of data are often overlooked. Let’s explore these impacts and look at some suggestions for reducing the carbon footprint of data storage. Another spoiler: Information Lifecycle Management (ILM) can help organizations sustainably manage their data.

Environmental and Climate Impacts of Data Storage

The environmental footprint of data storage is significant. Data centers, which house servers and storage systems, consume vast amounts of electricity. In 2020, data centers accounted for approximately 1% of global electricity demand, a figure comparable to the entire aviation industry. This energy consumption translates into substantial greenhouse gas emissions, which are generally accepted as a significant contributor to climate change.

One of the primary reasons for this high energy consumption is the need to keep servers cool. Data centers require extensive cooling systems to prevent overheating, which further increases their energy usage. For instance, a study by Stanford University found that storing 100 gigabytes of data in the cloud for a year emits about 0.2 tons of carbon dioxide.

Moreover, the concept of “dark data” exacerbates the problem. Dark data refers to data that is collected, processed, and stored but never used. It is estimated that more than half of the digital data generated by organizations fall into this category. This unused data still consumes energy and resources, contributing to the overall carbon footprint of data storage.

Examples of Environmental Impact of Data Storage

A notable example of the environmental impact of data storage is the massive data centers operated by tech giants like Google, Amazon, and Microsoft. These facilities, often spanning hundreds of thousands of square feet, require enormous amounts of electricity to operate.

In 2019, Google’s data centers consumed 12.4 terawatt-hours of electricity, equivalent to the annual energy consumption of nearly 1.2 million U.S. homes.

Clearly, if studies show that over half of the digital data being stored is “dark” and not required for business reasons, organizations have an opportunity to make a significant environmental impact by not storing data and information that is simply not required.

Reducing the Carbon Footprint of Data Storage

Organizations can take steps to reduce their carbon footprint by storing less data through minimization policies and practices. Implementing data minimization strategies involves regularly auditing and deleting unnecessary data.

By keeping only essential data, organizations can reduce the amount of storage required and, consequently, the energy consumed by data centers.

Data minimization is best achieved through the application of information lifecycle policies and programs. That is to retain the essential information required for regulatory or business reasons and defensibly destroying the rest. There are also impacts here for cost, user efficiency, and use of AI tools, but the significance of carbon reduction needs to be a key consideration when looking at the benefits of data minimization.

Explore the impact of information management strategies on AI success in this free report:

The Role of Information Lifecycle Management in Reducing the Environmental Impact of Data Storage

ILM is a strategic approach to managing data throughout its lifecycle, from creation to disposal. It helps organizations optimize their data storage and reduce environmental impact by implementing policies and technologies that ensure data is stored efficiently and securely.

ILM involves several key phases:

1. Data Creation and Capture: Establishing guidelines for what data should be collected and how it should be stored.

2. Data Storage and Maintenance: Implementing tiered storage solutions that prioritize energy-efficient options for less frequently accessed data.

3. Data Usage and Sharing: Ensuring data is easily accessible and usable while minimizing duplication and redundancy.

4. Data Archival and Disposal: Regularly archiving outdated data and securely disposing of data that is no longer needed.

By adopting ILM practices, organizations can reduce the volume of stored data, lower energy consumption, and minimize their carbon footprint. For example, a company that implements ILM can ensure that only current, active data consumes valuable computing resources while older, less critical data is moved to more energy-efficient storage solutions.

The environmental and climate impacts of storing too much data are significant, but organizations can take proactive steps to mitigate these effects. By adopting data minimization, efficient data management, and ILM practices, businesses can reduce their carbon footprint and contribute to a more sustainable future. 

With so many reasons to implement information lifecycle, organizations cannot afford to ignore this vital program any longer.

Explore how organizations can sustainably manage their data with information lifecycle management: