Everything You Need To Know About Data Minimization

Improve privacy and data quality with lower breaches, cost, and operation time through data minimization!

Data Minimization, the definition lies in the term itself, that is, minimizing the data by collecting, storing, and processing only the required information for business operations.

Just knowing what to keep and what to trash in your data is the key here. But why would you want to minimize your data?

As the earth grows older, data continues to grow. For years and decades, we now have tons of data, and it’s not so easy to deal with all of it. Just factor in how much personal data you yourself must have! Aren’t pictures a storage hassle enough?

That’s why we use techniques like data minimization to make the most out of minimal data. Plus, data minimization helps protect consumers privacy by limiting and making businesses more accountable for the data they collect.

So, where you are a business storing and working on customer data, or an individual whose curious about how your personal data is being used by a business, read on to know more of data minimization, its benefits, techniques, regulations, and a whole host more!

Benefits of Data Minimization

Previously, data was considered to be a gold mine, but now with the increasingly versatile avenues of data collection, quality is being chosen over quantity and rightly so! Here are some benefits of not flooding yourself with data:

#1. Enhanced Privacy: Data Minimization limits data collection. Because collecting only important information keeps personal and confidential data of your user safer, resulting in strong privacy. Furthermore, respecting the customer’s privacy by collecting only necessary data eventually builds trust. With proper customer data integration, duplication of data collection too can be avoided.

Let’s face it, how many of us are comfortable enabling cookies or seeing persistent pop-up ads of a product we had searched for but aren’t intending to buy anytime soon? Yup, sometimes less is more.

#1. Reduced Data Breaches: The less data you have, the fewer risks you face.

Having large data might give you more info, but it also brings the risk of data loss or data breach. So, having limited data is not only easy to handle, but also reduces the risk.

This will save your business from losing money, as I hear ‘data = success’ these days in many industries. However, without security practices like data masking, data is synonymous to danger as well!

#1. Lower Costs: Data storage and maintenance are not cheap. They come at a cost. So, you can’t just pick all the data and pocket it because this will unnecessarily raise your expenses.

However, data minimization is a technique that lets you store only necessary data so that you can leverage the data within budget.

#1. Improved Data Quality: Collecting necessary data and working only on relevant data complements improved data quality. Also in case of fewer data, you can easily trash🗑️ the outdated information and update it with current data, enhancing the quality and accuracy of your data.

#1. Reduced Operation Time: With less data, business operations like querying, filtering, exporting, or updating will be lightning-fast. Moreover, data request, and response time is also faster, improving the overall efficiency of the business.

Thus, a more selective take on data might be a wiser option now as when dealing with customer data, there are now so many avenues for collection. From eye tracking software to heat mapping, data collection sources abound!

Data Protection Regulations that Prioritize Data Minimization

#1. GDPR – General Data Protection Regulation

Data minimization principle GDPR talks about efficiently collecting, processing, and storing only required data. It suggests collecting less data, and it is illegal to collect irrelevant data.

This is a comprehensive data protection regulation that’s valid among all the countries using the EU individuals’ data.

#2. EDPS – European Data Protection Supervisor

EDPS is an independent authority specially built to ensure European institutions comply with data protection rules.

It guides the institutions, businesses, and other major data collecting and storage sources in Europe to only gather the necessary data for specific purposes. Plus, they don’t encourage you to keep the data once the purpose is fulfilled.

#3. CCPA Data Minimization – California Consumer Privacy Act

California data privacy regulations allow individuals to question the data collected about them. They can know what data is collected and ask to delete the data if they feel it is inadequate.

This way businesses become more accountable and responsible while handling the consumer’s data and incorporate data minimization techniques in their workflow.

#4. VCDPA – Virginia’s Consumer Data Protection Act

Like the other data protection regulations, VCDPA also states to collect the data only if it is adequate, relevant, and reasonably necessary. Virginia also demands you to use the data you have gathered only for the actual and intended purposes.

After all, all the data minimization principles convey collecting only the necessary and relevant data is legal. Plus, they demand you to delete the data once the intended purpose is done.

Also read: How Much is Your Personal Information Worth on the Dark Web? 

How do you Implement Data Minimization?

Follow the below principles to ensure data minimization is implemented in your systems.

#1. Define the Purpose

You should define the precise objectives and exact goals of why you should collect specific data. Understanding the clear purpose helps you only collect the data you need.

#2. Narrow down the Data Collection

To respect your customer’s privacy and align with data protection regulations, it’s crucial to keep your data collection as lean as possible. So, make sure you only collect the data that is required.

In essence, you should be able to justify why you collected specific data, how long you stored it, and where you used it.

#3. Data Management

The data you collect gets outdated over time, compromising on data quality. So, a data minimization principle recommends you perform timely audits to update the data with current info and delete outdated information.

Preferably, perform yearly audits to ensure that you adhere to data minimization policies.

#4. Data Deletion

Include strategic deletion protocols in your data minimization approach.

Data minimization is not just about collecting minimal and required data, but alsovmoving to trash or deleting it once the intended purpose is fulfilled. This ensures that businesses keep the data only for as long as needed.

#5. Security

You are responsible for the security of the data you collect. So, implement robust security measures like authorization, encryption, role-based access, etc., to prevent data breaches and losses.

Here are a few challenges you might face while implementing data minimization:

• Data Minimization doesn’t just end at minimal data collection, it also demands you to – use the data for specified purposes only, limit actions that can be performed on data, and delete the data after usage. Ensuring all these policies throughout the data lifecycle is complex.
• Balancing between collecting enough data and less data can be challenging. That is, you should collect enough data for your purpose while limiting the collection of irrelevant and unnecessary data.
• In large organizations, data is usually scattered among various departments. Sometimes, you may delete the data in one place, and it will be left over in the other department, violating data minimization. So, it is difficult to manage scattered data.

Furthermore, adhering to the same data retention policies across the organization can be challenging because different types of data may have varying lifecycles.

Use Cases of Data Minimization

#1. Mobile Apps

When you have a mobile app on your smartphone, it might need access to your location, contacts, microphone, etc to function as intended. But have you ever wondered how some apps only ask for the permissions they truly need?

When the developer makes an app keeping data minimization in mind, it only requests the specific and necessary accesses.

This will improve privacy and build trust of customers in the long run, boosting the success of your app.

#2. Financial Institutions

Financial organizations should incorporate strict data minimization rules as they deal with a lot of customers’ sensitive data. Accessing and storing only required data helps reduce data exposure, preventing the risk of data loss.

#3. Health Care

Health check-up machines and fitness apps often require patients’ or users’ data to show accurate results. Implementing data minimization in the health care industry accesses and stores only relevant information to diagnose and treat any diseases.

#4. IoT

IoT devices usually collect a lot of data from sensors, and sometimes end up boarding more data than they really need. So, applying data minimization techniques here limits the data collection, reducing the risk of data breaches.

Conclusion

Data is a big part of today’s world and many businesses use it to boost their profits, sales, marketing, and user experiences. However, it is equally important to limit the data usage for intended purposes to avoid the risk of data loss and keep privacy intact.

That’s why techniques like data minimization should be implemented.

I hope this article helped you understand what exactly data minimization is, why you require techniques like this, and how to implement data minimization in your systems.

You may also check out the best data security solutions to secure your businesses.