Trying to solve a problem, determine the optimal course of action, or make a critical decision in the absence of meaningful data not only is frustrating – it can yield undesirable outcomes.

It’s like driving without a map or hiking without a compass, let alone precise GPS. Or, like trying to communicate with a friend, whose last name you don’t remember how to spell, without a phone number, email address, or Twitter handle.

Many business leaders have realized that connected devices, systems, and sensors are generating more and more data that can be invaluable to making better business decisions. Yet, they still are deciphering how best to leverage all of the data to drive better business decisions.

With impending compliance obligations under the GDPR, they may forfeit those data opportunities if they don’t implement solutions that enable ongoing authorized use of those data.

Privacy leaders can be business enablers by supporting the business in maximizing net data value in two key ways:

  • Partnering with other data leaders in the organization to establish an integrated approach to data governance that enables data benefits and risks to be evaluated in a holistic way, and
  • Driving consistent evaluation of the value and costs associated with the acquisition, storage, use, and re-use of data.

Data Protection by Default

In the white paper, Meeting Upcoming GDPR Requirements While Maximizing the Full Value of Data Analytics Mike Hintze and Gary LaFever tackle the new frontier of “data protection by default” under Article 25 of GDPR.

The concept of data protection by default permeates the regulation. It expands upon traditional notions of data minimization or the minimum necessary data to prescribe implementation of technical and organizational mechanisms for ensuring that only the specific personal data necessary for each specific processing purpose are processed.

Each specific processing purpose includes: collection, scope of use, length of storage, or accessibility.

Hintze and LaFever present a compelling case for companies to proactively implement a robust technical approach to the GDPR’s data protection by default requirements in order to both maximize data value and minimize compliance risk and liability.

Technology Saves Time and Maximizes Data Utility

As privacy professionals, we spend countless hours with business teams identifying and classifying data elements, determining the processing purposes and the legal basis for any proposed processing, and evaluating data retention periods and proposed data transfers.

We create data inventories and data flow maps in order to determine whether data minimization, proportionality, and onward transfer requirements are met.

We are startled when the hours fly by and our analyses are ongoing, and we recognize that the only way we can support goals like maximizing net data value is to rely on technology to scale our work, make it more efficient and ultimately, more effective.

With GDPR’s data protection by default requirements in just 15 months, we can no longer put off plans to implement new technology to help us comply.

How Controlled Linkability Improves Data Utility

Fortunately, Hintze and LaFever present solutions based on a concept of “controlled linkability” that refines data so that it can be used for a range of purposes while preserving privacy and protecting the data from unauthorized processing.

Controlled linkability thus facilitates extraction of the full value of data, enabling both GDPR and other regulatory compliance as well broad data utilization. In order for businesses to preserve and enhance the value of their data beyond the next 15 months, however, the time to plan for effective implementation of these technology solutions is NOW.

Since so many businesses rely on big data analytics, as increasingly artificial intelligence, to fuel innovation and growth, it has become essential to know how to ensure compliance in a way that allows your data assets to be utilized.