Data Minimisation Principle: What Is It & How Can It Help GDPR Compliance?

Alex Franch
March 20, 2023

Table of Contents

Data minimisation means maintaining only data that is strictly necessary to fulfil a specific purpose. Data minimisation is a direct way to limit privacy leakage. Intuitively, the less data there is to collect, store, and share by businesses, the easier it is for them to protect the personal information of users.  

Concept of data minimisation

Since the first decade of the 21st century, businesses and governments were under the impression that data is the new oil and the companies and organisations with access to the most data and the best ways of making sense of it would inevitably rise to the top and succeed. On the contrary, data has become a liability rather than an asset and its management is slowly becoming a privacy and information security nightmare. That’s where data minimisation comes in: it removes the data liabilities your firm has, letting you focus your energies on maximising the value of your data assets.

The principle of data minimisation means that data controllers must only collect and process personal data that is relevant, necessary and adequate to accomplish the purposes for which it is processed. It encourages the companies to adopt the organisational practice of minimising the overall amount of personal data collected. In practice, it obliges the companies to collect personal data that is adequate, relevant and what is limited to their specific purpose.

Example A recruitment agency places workers in a variety of jobs. It sends applicants a general questionnaire, which includes specific questions about health conditions that are only relevant to particular manual occupations. It would be irrelevant and excessive to obtain such information from an individual who applied for an office job.

Let's understand the essential elements of the minimisation principle:-

Although not explicitly defined within GDPR, organizations can use the following general definitions when determining the adequacy, relevance and limitation for personal data collection.

Adequate: only data that is sufficient to adequately fulfil specified purposes stated within the ‘purpose limitation principle.

Relevant: only data that is reasonably related to the purposes stated within the ‘purpose limitation principle.

Limited: only data that is necessary to perform stated purposes, ensuring the organisation does not collect data that is not relevant to those purposes.

Why does data minimisation matter?

The benefits of the principle of data minimisation not only helps an organisation in data management but also from a data protection perspective.

  • **The essential principle of data protection-**This is required by data regulations and includes lawfulness, fairness, transparency, purpose limitation, data minimization, accuracy, storage limitation, security and accountability.
  • **Reduced ecological footprint-**Less data means less computing power and a physical hard trail of paperwork.
  • **Adherence to EU GDPR compliance-**This is now a very universal approach to many major privacy regulatory bodies across the globe.
  • **Reduction of data storage cost-**Although data storage is getting cheaper, it still adds to the computing cost of enterprises.

Best practices to ensure data minimisation

The application or adoption of the principle of data minimisation requires the creation of a comprehensive plan that includes the following principles:-

  • Define the Purpose Define the purpose of the data as explicitly as possible. Everyone involved, including data subjects and members of the enterprise, should be able to easily understand the purpose and use of the data.
  • Narrow data collection Determining what data is absolutely necessary is the first step in a successful data minimisation strategy. Businesses must narrow their data-gathering techniques to the point where only the most valuable information, however, a given business defines that, is collected for analysis.
  • Specify the Usage Specify and define the processing of the data, which is specific to how data will be used. Any clarification from the enterprise should be properly acknowledged and discussed in a timely manner.
  • User verification and screening Many bulk data collection workflows function on the assumption that the vast majority of users submit usable, relevant information that they own. In reality, this is not the case. Many businesses, from start-ups to multinationals, unintentionally collect large amounts of dangerous data. It could be fraudulent or unconditioned, and thus generate risk for everyone involved simply by sitting in company servers. Strong data minimisation plans create user verification and screening processes to weed out such data.
  • Data Collection procedure Evaluate methodologies of data collection minimisation by designing and implementing processes that require the least personal data or that only require anonymised data.
  • Progressive data management User data eventually goes stale, yet many organisations do not take this into account, which results in databases stuffed with unusable or incorrect information. This is a burden for not only the IT infrastructure but also the greater business as it could negatively affect the analysis. Data minimisation plans with progressive evaluation protocols avoid these issues by working with users to update their data and cultivate databases optimised for actionability. It is cost-effective and mitigates risk.
  • Strategic deletion Strategic data erasure is a core component of the data minimisation methodology. User information has a lifespan, and this has never been more true than in today's fast-moving digital marketplace. Businesses must consistently purge stale data from servers to ensure the information they access is truly valuable and does not pose a security threat. As a result, all data minimisation plans should include deletion protocols.


Collecting data is easy but becoming the rightful custodian of that data is challenging. It is important to put in place and adopt an effective mechanism to use the data for the rightful purpose and discard it properly to showcase your commitment and respect for the core principle of GDPR.


This article does not constitute legal advice in any form and only seeks to break down some of the main points set out by publicly available sources such as the ICO.

Alex Franch is the co-founder and CEO of Privasee. With a background in computer science and cybersecurity, it is no surprise that he is a highly analytical problem solver; now putting these skills to use within the data privacy space. Alex is passionate about GDPR, and productivity and spends a lot of time doing sports as he values the importance of having a work-life balance. He is excited to help businesses generate documentation, and become and maintain GDPR compliance through the Privasee platform.

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