When companies collect data, it has a lifecycle. The time comes when this data is no longer relevant or the company no longer has the right or privilege to hold onto it.

Data life cycle management is how a company regulates and controls data from the collection to the cleaning stage.

In the past, companies had more leeway in determining how to manage data.

The passing of Europe’s GDPR and California’s CCPA created legal frameworks dictating how data can be used and when it should be deleted for a large portion of the consumer market.

Companies must keep this in mind when choosing a data management cycle model.

What Are the Stages of Data Life Cycle Management?

There are five data management phases or stages. At each stage, the company’s treatment of and relationship to the data changes.

While each stage improves accuracy, it also potentially brings the data closer to its deletion phase.

1. Collection

Data privacy laws now dictate how, when and why affected companies collect data.

Consumers in jurisdictions with these laws can also determine when a company has access to their data. In fact, customers can shorten the life cycle altogether by asking to “be forgotten.”

Note that most data privacy laws also prohibit businesses from taking negative actions against customers who limit the collection and use of their personal information.

Companies still have a lot of legal tools available for collecting consumer and public data. This is especially true in jurisdictions not yet affected by data privacy laws.

Here are some common collection methods:

• Asking customers to provide personal information in exchange for a free gift, such as an eBook
• Including the submission of personal information during the sign-up process, such as when requesting construction quotes
• Requesting personal information as part of the process to participate in raffles
• Offering special services requiring or encouraging the creation of membership profiles tied to personal information
• Requesting contact information as part of the purchase process for products and services
• Using software to track user information in apps, on the company website or even on social media platforms

It is important to note that while some of the most valuable data come from consumers, it is not the only kind of data companies have and store.

Businesses also generate data in-house when tracking performance and calculating key metrics.

2. Data Storage

How companies store data depends on the data privacy laws that affect them. In Europe and California, companies are held to higher standards to protect the personal information of customers.

However, all across America, companies must comply with federal laws regarding medical and payroll information.

Because of this, at the storage stages, companies are also considering security concerns.

Data breaches can be costly in dollars and cents but can be even more costly in public distrust and brand damage.

One of the most important considerations companies make when it comes to data storage is whether to upgrade to the cloud.

3. Data Maintenance

In its primitive form, data might not be very useful. Companies must connect the dots to enrich it.

Sometimes, this is an explicit process that involves reaching out to the client or customer and asking direct questions.

Insurance, remodeling and construction companies are likely candidates for taking this approach.

For most companies, data maintenance can involve looking for duplicates or cleaning up inactive accounts.

Data integration is also important at this step. This provides access to the data for authorized parties.

Some companies follow a manual process, but technology has made digital integration so much easier.

Fluix, for instance, provides easy integration solutions for our clients. This reduces the need to purchase more apps and move between multiple apps as part of your work process.

4. Data Usage

At this point, data becomes part of key decision-making processes.

Whether it’s a doctor determining what surgery to recommend to a patient or a salesperson reviewing prior account activity to upsell a customer, the data has finally made its way into the workings of the business.

Note that data privacy laws can also affect this.

Companies that share personal information with other business partners or sell information to marketers may have additional considerations.

It is important to establish protocols, especially when customers allow data collection but decline to have their data shared or sold.

5. Data Cleaning

Modern-day businesses generate a large amount of data on a regular basis.

Storing an infinite amount of data for an indefinite period of time is expensive and will likely take up more space than it’s worth.

Because of this, companies should also invest in re-verifying data to ensure it is still valid and accurate. At this stage, data can be purged, destroyed or deleted.

With the introduction of data privacy laws, companies need to put protocols in place for how to handle requests to be forgotten.

Archiving inactive data that might become active in the future is another consideration to make allowances for.

What Are Common Mistakes Businesses Should Avoid?

The number one mistake is to fail to follow data privacy laws. Companies have been fined in the 10s of millions for violations. Here are four additional mistakes to avoid.

Treating Data Equally

All the data in your company should be safeguarded from unauthorized access. However, not all data carries the same level of risk.

No matter how strong the safeguards are to protect email addresses and names, the protections for SSNs, financial information and medical records should always be a step higher.

Ignoring the Context

Remember the context in which data was collected and respect the usage customers consented to.

Say, for instance, a customer provides personal information while purchasing a solar power system.

The customer might welcome follow-up emails and how-to information. However, he or she might not appreciate receiving weekly spam mail pushing new solar power components.

Erasing the Human Element

In the modern world, people are often the sum total of their data. While this does not determine personal self-worth, it does determine an individual’s worth to a company.

Even so, companies must take a step back and remember that human beings are on the receiving end of their decisions and communications.

Failing to Back Up

If an employee hits the wrong button and deleted an entire month’s worth of data collection, would you be able to retrieve it?

Companies need strong backup tools to account for human error, natural disasters and technology glitches.

What Are the Benefits of Managing the Data Life Cycle?

Data life cycles require active management to protect a business’s best interests. These interests include legal, financial and marketing.

Failure to put proper protocols in place can lead to costly, embarrassing and even deadly errors.

Imagine the potentially horrifying outcome of someone’s medical file containing incorrect information about health conditions or incomplete information on medications.

Even if it is accurate and complete, what if an unauthorized person gained access to that information?

What would the repercussions be for the health care provider and what are the potential risks for the patient?

Proper management of the data life cycle can also yield crucial information companies need to boost sales, better serve customers, beat out competitors and seize market opportunities.

Properly collecting, storing, verifying and cleaning up information can help ensure this.