Do you remember going to your grandparents’ house as a kid and pulling out a kitchen drawer jam-packed with expired mayonnaise and ketchup packets from a dozen different restaurants? Or opening a closet door . . . and having hundreds of gift bags fall on your head? Tripping over stacks of newspapers with half-finished crossword puzzles?
When you tried to throw some of it away, did they stop you and say, “Put that back, I’m saving that March 1987 issue of People magazine—I want to re-read the article about Cybill Shepherd”?
Grandparents are famous for saving everything from rubber bands to expired mayonnaise to ancient paperwork. And while this habit may not technically qualify as hoarding, it definitely can result in “collections” that are unwieldy, hard to manage, and even dangerous (especially when it comes to that expired mayonnaise).
Many companies have a data collection program resembling your grandparents’ house. They collect anything and everything, store it wherever they can for as long as they can, and hope that one day they’ll find a way to use it.
But just like expired mayonnaise can yield unintended consequences, hoarding data can lead to a host of smelly issues that take a long time to clean up.
Enter the principle of data minimization.
Data minimization is key to reducing operational risk and establishing compliance with current and pending privacy legislation.
Data minimization has been cemented as a privacy best practice since the European Union passed the General Data Protection Regulation (GDPR) in 2016. Since then, governments around the world have followed suit.
While privacy regulations are unevenly distributed, it’s safe to say that even if your business isn’t currently subject to a digital privacy law, it eventually will be.
So let’s get you familiar with the practical ins and outs of data minimization.
How does data minimization work?
Data minimization is the practice of collecting and using the bare minimum amount of required data (MRD) that an organization needs to complete an operation. Moreover, organizations need to explain why they’re collecting the information before it’s actually collected.
This means that processed data should be adequate, relevant, and limited.
- Relevant: clearly connected to the stated purpose
- Limited: data collection is limited only to the stated purpose
Keeping collection practices adequate, relevant, and limited is especially important when it comes to “special category” or “sensitive personal” data (e.g., birthdate, social security number, race, medical history, political or religious affiliation, sexual orientation, union membership, and biometric data). Because special category/sensitive personal data could potentially identify an individual or cause harm if exposed, this type of information requires extra security and is granted extra protection under most privacy laws.
Need a real-world example of what data minimization looks like?
Say you want to start an email newsletter for your business, but you don’t have up-to-date email addresses for your customers. To keep your data collection adequate, relevant, and limited, you can put a digital form on your website or a paper signup by your cash register that explains your newsletter and lets customers share their names and email addresses.
Following the data minimization principle, collecting information for an email newsletter doesn’t mean you should start asking for your customers’ addresses, phone numbers, or birthdates.
But you actually have to be doing those things.
A vital data minimization takeaway is this: Just because you can ask for something, doesn’t mean you should. (A lesson your grandparents should have taken to heart about those expired mayonnaise packets!)
All data collection should be backed up by a business purpose—and that business purpose should apply to what you’re doing today, not what you hope to do a year from now.
Data minimization and data inventories
Data minimization is one of the best ways to reduce operational risk and establish compliance with privacy laws, and a data inventory (also referred to as a data map) is one of the best ways to help you achieve it.
A data inventory involves following a data record through its entire lifecycle in your system. This will show you what data is being collected and why, who it’s being shared with, how long and where it’s being stored, and where it’s at risk of being compromised.
Data maps pinpoint where your data program practices deviate from policy. They can also identify which data points are mission-critical and which are a liability, which is extremely helpful in streamlining your data collection processes.
Benefits of data minimization
If you’re like most people, data minimization probably feels like something that you’re legally obligated to spend money on but don’t receive much benefit from apart from establishing compliance.
But we want to change your mind and prove that data minimization provides you with a huge opportunity to differentiate yourself from your competitors.
Done well, data minimization can:
- Reduce the risk of a breach
- Make data processing and analysis more efficient
- Improve decision-making processes
- Future-proof marketing and privacy programs
- Increase bottom-line savings
- Help save the planet (really)
Reduce the risk of a breach
Data is always at risk of exposure, and the more data you have, the easier it is for hackers to access the system. The customer service and marketing benefits of using accurate user data justify the risk, but collecting and storing data you don’t need is like leaving the door to your warehouse unlocked.
Make data processing and analysis more efficient
Let’s go back to your grandparents’ house.
Have you ever spent hours helping them dig through piles of junk looking for important legal documents or precious family photos? Not only does the sheer volume of stuff make the process frustrating, but it also makes every search take longer than it should.
Similarly, too much data clogs your analytic programs and slows your ability to respond to customers. Plus, data doesn’t stay fresh forever—and when you use outdated data, you risk skewing your analytics.
Improve decision-making processes
Collecting too much data increases the likelihood that you have unreliable data, and you don’t need to be a CEO to know that making strategic decisions with faulty data is a recipe for the next New Coke formula disaster.
Increase bottom-line savings
Hiring enough people to manage giant data stores is expensive. So is storing and maintaining data safely. Streamlining data collection processes can significantly reduce overhead expenses.
Future-proof marketing and privacy programs
Investing the time and resources to build an agile data privacy program now will make it easier to comply with current and future regulations without interrupting operations.
Help save the planet
Okay, so data minimization may not get the Black Rhino off the endangered species list, but producing, using, and transferring data contributes to C0₂ emissions—and more than you might expect. Minimizing data requires less energy, and that’s an important step towards a greener future.
Minimize Your Data, Maximize Everything Else
Don’t be like your grandparents, leaving your employees and customers to wander aimlessly through a maze of clutter. (But you can be like them in all the other ways because, let’s face it, grandparents are generally pretty great).
Willingly cutting back on the information you collect from your customers feels counterintuitive and can be scary. But the reality is that minimizing data collection maximizes what you can get out of the data you have.
If you need help figuring out the best way to manage your data or build a privacy program, the experts at Red Clover Advisors are here to help you. Give us a call today to schedule a free consultation.