The Digital Dilemma: Balancing data growth with the carbon costs

In today’s digital age, the vast amounts of data generated by businesses often go unnoticed. Yet, beneath the surface lies a hidden environmental cost that many are unaware of – dark data. This article will delve into this often-overlooked aspect of digital operations and explore how businesses can play a crucial role in reducing their digital carbon footprint.

What is dark data?

When we talk about ‘dark data’, we are referring to data that is collected but rarely reused – representing most digital information. This data is collected, processed, and stored, often unnecessarily or for single-use purposes. If it was visible, like plastic, we would be horrified! 

Why is it a problem?

The energy consumption required to maintain dark data, housed in vast servers and increasingly gigantic warehouses, represents a significant environmental cost. With data storage requirements only set to increase, this growth is outpacing sustainability efforts in the sector. Despite this, guidance on reducing carbon footprints often neglects the digital sector’s substantial contribution to greenhouse gas emissions, with digital data processing already rivalling traditional sectors like automotive and aviation.

Digital carbon footprint

In 2019, digitisation accounted for 4% of global greenhouse gas emissions and the production of digital data is rapidly increasing, projected to increase by 9% each year. Despite these alarming figures, little attention has been directed towards reducing the digital carbon footprint of organisations. 

The cause of dark data:

The cause of the growth in dark data can be attributed primarily to two interconnected factors: fear of deletion and inadequate data management practices. 

Fear of deletion

Organisations often harbour a fear of deleting data due to concerns about losing important information that might be needed in the future. This reluctance stems from several reasons:

  • Regulatory compliance: Companies are required to retain certain data for compliance with legal, tax, or regulatory mandates. The ambiguity about what needs to be kept, for how long, and in what format, can lead to a “save everything” approach.
    • Future utility: There’s a belief that data, no matter how trivial it seems today, might hold value in the future, especially with advancements in data analytics and AI technologies.
    • Liability and documentation: Data serves as a record of decisions, transactions, and interactions. There’s a fear that deleting data could remove evidence of due diligence or decision-making processes, potentially exposing the organisation to legal or reputational risks.

Inadequate Data Management Practices

The exponential growth of data volume, velocity, and variety has outpaced the development of effective data management strategies in many organisations. This inadequacy manifests in several ways:

  • Lack of policies and procedures: Without clear data retention policies, categorisation standards, and deletion protocols, organisations find themselves amassing large volumes of data without a clear strategy for managing it.
    • Poor data hygiene: Regular data cleaning and archiving are often overlooked in the face of more immediate business priorities. Over time, this leads to the accumulation of ROT data that clutters systems and makes data management even more challenging.
    • Inefficient storage and organisation: Data is often stored in siloed, unconnected systems without a unified management or governance framework. This fragmentation makes it difficult to understand what data exists, where it is stored, and whether it is still relevant or necessary.

What are the solutions?

The starting point for all organisations needs to be raising awareness of the environmental impacts of data storage, and the particular issue of dark data. 

Organisations also need robust data governance frameworks. We provide our clients with a template data retention policy to help foster a culture which prioritises data hygiene and lifecycle management to mitigate the environmental impact of excessive data storage.