Lawsuits and press releases are published daily about how businesses are misusing consumer data or illegally selling it to third parties. These fiascos led governing bodies to set rules for how corporations can use the collected information ethically.
Companies need copious amounts of data, especially with the advent of AI and machine learning, but how can they be responsible while obtaining the information they need to operate successfully? Data minimization is a framework that provides a happy medium between collection and privacy to reinforce cybersecurity and customer satisfaction.
What is data minimization?
Data minimization is the practice of intentional data gathering. A company would only collect information that is essential for performing necessary operations. As an easy example, businesses that don’t need Social Security numbers to sell products shouldn’t request them from customers. Data minimization holds organizations accountable and provides peace of mind to consumers who have potentially become complacent about distributing personally identifying information (PII) to every online account they register for.
The strategy is more than limiting data collection — it’s also about access, oversight and management. One of the reasons minimization is a hot topic right now is because of overstocking and illegal distribution, which increases as more people have access.
Additionally, administrators should curb permissions and update them frequently to ensure accuracy. This allows analysts and IT teams to perform database management, storage and deletion as required by law. The goal is to keep only necessary and up-to-date data pivotal to company success.
What are the benefits of data minimization?
Enterprises may feel wary of data minimization because of a “more is better” mindset. While understandable, this approach is dangerous because it increases the surface area for cyberattacks. Collecting more PII about customers than required places more severe liability on companies when protecting customer bases.
Having too much information bogs down servers and hardware. Data centers may reach their limit, using countless resources like energy, money and time from staff. Data minimization curbs expenditure in these areas, reducing stress on employees, utilities and technology for a more efficient and sustainable outfit. IT won’t have to troubleshoot as frequently, and backup times will shrink, making recovery strategies more effective. Companies are less likely to lose or misplace information if meaningless data points don’t obscure more prominent items.
From a public relations standpoint, data minimization is a protective blanket over a company’s reputation. Customers will have more faith in an organization with quality compliance and awareness of information use.
Plus, it gives companies a competitive edge when facing upcoming compliance updates and legislation — which will only hone on privacy and management in more detail. Executing intelligent data minimization will eliminate bad publicity and the need for public apologies over information abuse.
How do you create a data minimization strategy?
Creating a data minimization strategy is a nonnegotiable aspect for every company department. Following these steps will ensure a robust and secure installation.
1. Define what’s essential
Look at your data and notice what you do and don’t use. An audit will reveal company operations, forcing you to outline your priorities. Plus, it makes businesses reflect on what to do with data before collecting it instead of finding as many ways to use it as possible.
Do companies use phone numbers to obtain feedback, and are you only getting legally obligational information from employees? Companies should delete all data collecting digital dust before moving on to other parts of the strategy installation.
2. Delegate responsibilities
Data minimization involves more departments than IT. Here are some responsibilities that will need to be assigned before this framework becomes effective:
- Checking and updating data management compliance according to laws
- Giving and removing information access permissions
- Managing storage and executing data wrangling for intentional deletion
- Enforcements validating the effectiveness of data minimization strategies
- Ensuring systems are in place to allow customers to provide consent for information release and use
- Protecting the data from cyberthreats
3. Outline sustainability
A data minimization plan won’t be effective if the strategy doesn’t consider how the program will stay sustainable and efficient. How frequently will necessary parties evaluate its effectiveness? What is the data retention schedule, and how will companies ensure it’s an ideal setup? Though data minimization immediately changes a company’s digital structure, long-term implementation is equally critical for success.
Companies must define how each data byte serves the company’s mission, how they receive permission to use it, how long they’ll keep it and the justification for holding onto it. Transparency is the key to clarity in data minimization.
Why data minimization matters
These practices are a necessary step into a more data-driven world. It encourages companies to have healthy relationships with information collection and usage, making consumers more conscious about what they’re giving to corporations. Data minimization is one piece of a puzzle that forms the foundation for safer digital environments and ethical data applications.