Data Minimisation Under KVKK: Common Implementation Problems

⏱️ Reading time: 13 min · 📁 Category: KVKK, Data Security & Compliance

Data minimisation under KVKK: Where organisations struggle most at the end of 2025

Although data minimisation is a fundamental KVKK principle,
it remains one of the greatest practical challenges for organisations at the end of 2025.
The recent audits and decisions of the KVKK Board clearly indicate that;
the most frequent violation is exceeding what is necessary for the processing activity.

Although many institutions have established the legal basis correctly when initiating data processing activity,
they exceed what is necessary in the quantity and variety of data collected
and inadvertently collect excessive data.

Summary of the 2025 audit approach:
"Being able to process doesn't mean you can collect every data." What is Data Minimization? 2025 Perspective

Under KVKK, data minimisation means processing
personal data for specific, explicit and legitimate purposes,
in a way that is relevant, limited and proportionate to those purposes.

As of 2025, the Board does not consider data minimization to be limited to only the "first collection moment";
It evaluates the entire life cycle in which data continues to be processed under this principle.

1. Where does the processing-related necessity begin, and where does it end?

The question organisations struggle with most is:

“Do we really need to process these data, or are they merely useful to us?” According to the Board's 2025 comment:

• The fact that a data is "beneficial" is not enough to process
• If data is being held without the purpose of processing it is a surplus.
• If there is an alternative method, the method with less data should be preferred

Example:

• A full address is needed to deliver an order → reasonable
• Requesting a date of birth for the same process -> data excess

2. Most Commonly Detected Data Excess Areas in 2025 Promotional campaigns and prize draws

• Identification number request
• Date of birth (day/month/year)
• Profile data such as gender, profession

The board approach is clear:
None of this data is mandatory except to determine a winner for the draw.

CRM and Marketing Systems

• Past data stored outside of campaign purpose
• Keeping passive customer records indefinitely
• Excessive datasets used for profiling

Employee Data

• Camera recordings held indefinitely
• Wide-ranging location tracking
• Behavioral monitoring data unrelated to performance

The most frequently used expression for employee data in 2025 audits is:
“The principles of purpose relevance and proportionality have been breached.” 3. Where do excessive data most often hide?

Excess data often build up through habit rather than deliberately:

• Formerly remaining form fields
• Automatic log and analytics records
• Derivative data generated by AI and automation systems
• Data pools with no deletion calendar

As of 2025, the Board has begun assessing AI-generated derived data
specifically under the data-minimisation principle.

4. Why is “we may need it later” no longer a valid approach?

The defense that institutions often use:

"We don't use this data right now, but it could be useful in the future."

The Board's 2025 approach explicitly rejects this defense:

• Hypothetical need is not a legal justification
• Storing data for future use is the risk of a breach
• New purpose -> requires new assessment

5. Guide to Implementing Data Minimization for the End of 2025 Step 1: For each data field, the question "why?"

• For what purpose is this data processed?
• Is it really necessary for that purpose?

Step 2: Alternative method analysis

• Can the same result be achieved with less data?
• Is anonymisation or masking possible?

Step 3: Review retention periods

• Are retention periods unspecified or unlimited?
• Does the automatic deletion mechanism work?

Step 4: Review of AI and analytical processes

• Is unnecessary data being used for model training?
• Are derivative data included in inventory?

By the end of 2025, data minimisation
has become a matter of operational efficiency as well as compliance. 6. Data Minimization - Data Inventory - privacy notice Relationship

Data minimization cannot be assessed alone.
Full consistency is required between the following three:

• Data processed
• Data contained in the data inventory
• Data reported in the privacy notice

If one of these three is incompatible,
Data minimization violation occurs in a chained way.

Conclusion

By the end of 2025, KVKK data minimisation
has moved beyond the slogan “as little data as possible” to become
a proportionality test tied to the processing purpose.

Organisations’ biggest mistake
is believing that a legal basis allows them to keep collecting data.
Whereas the Board's approach is clear:
Any unnecessary data is a risk of a breach in itself.

Data Minimization Compliance Analysis