September 12, 2018
Data Commoditization and Transparency
Steering Data Use with Integrity
In our modern technology-driven world, “virtually every activity creates a digital trace.”1 That digital trace is data, the abundant derivative of our digital age and the world’s newest precious resource.
For the moment, this commodity is free for the taking with only a handful of fragmented regulations associated with its ownership, use and protection. And much like the forty-niners of the California Gold Rush, companies are scrambling to claim, mine, and sell as much of this new resource as they can get their hands on.
As history has shown us, misuse of unregulated resources quickly can lead to manipulation, monopolization and devastation. Fortunately, the historical outcomes and lessons-learned can serve as a helpful framework for developing a plan now that allows us to utilize data ethically and responsibly, as we discussed in part one of this three-part blog series on data.
But the parameters for responsible data use, rights, ownership, security and privacy are not yet defined, implemented and enforced consistently across industries and around the globe. In the meantime, we need to be cautious of our short-term impact on this resource and in Tristan Harris-esque2 fashion, steer its use by conscious rather than for sole economic gain.
In this second installment of our data blog series, we examine how data collection, mining and commoditization can be acceptable, appropriate and drive real value – when done with transparency.
The Drivers Behind Data Collection
Data as an industry has been around for a while. Traditional list brokers, for example, have solicited their aggregated data wares to marketers since the early days of direct marketing.
It didn’t take long, though, for other organizations to recognize that the data that they collected through the course of business – customer information, transaction history, seasonal trends and more – posed real value. Companies could use their first-party data, for instance, to connect in meaningful ways with their bases, gain competitive advantage by deriving insights into trends, and surface new revenue streams. Their information also held value for others, and companies could gain financially by selling their data to partners, list brokers and other third-party vendors.
This recognition of data’s value, the promise of Big Data and technologies including cloud storage and advances in data analytics all have encouraged the collection of consumer data – even when there’s no specific plan for its use.
Removing The Cloak
Data collection often is done under the cloak of convoluted legalese that a grandparent can’t understand. While shrouded data practices may provide companies with short-term control, “…users can’t trust you if they don’t understand what you’re up to,” and long-term benefits are jeopardized.3
But 2018 already has brought some winds of change. The General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (the “Act”) are pioneering the shift to consumer empowerment – and the longer-term preservation of the data resource in the digital age. Companies obligated under either GDPR or the Act that want to use data must disclose the types of data they collect and limit use to the context of the permission granted.
These regulations are demonstrating that it IS possible for companies – even those who are not obligated under specific regulations – to collect, mine and sell data appropriately, and to drive outcomes and innovations that benefit both users AND companies.
Transparency around data practices, though, is the key. Not only does transparency build consumer trust, it also commits companies to defining their data use and, ultimately, doing so at higher and dare we say more ethical level.
Balancing the Outcomes
There is a correlation between consumer trust and their willingness to share data. With increased transparency and outcomes that benefit both the users and the companies, data collection is an easier pill for consumers to swallow.
There are, of course, the traditional marketing-based objectives of data collection that arguably result in shared company-consumer benefits – including more relevance in marketing such as online ads prompted by searches and purchase history, and product innovations that prompt exercise and feed interests.
Other outcomes are more innovative and contribute benefits that resonate on a deeper level. Genome sequencing in healthcare, for instance, uses collected samples of DNA data and is becoming an important tool in guiding therapeutic intervention, in vitro fertilization, and preventing disease.
Not surprisingly, newer technologies are helping to enable data outcomes while ensuring critical data privacy. Homomorphic encryption enables companies to share data with companies that can perform mathematical computations and analysis on encrypted information without decrypting or compromising the source data. Differential privacy methods, for example, inject “noise” into data sets to enable similar computations while protecting the source information.
Whether enforced by law or consciousness, transparency enables a more appropriate and balanced approach to data commoditization. This translates to improved trust between data subjects and companies as well as outcomes that are balanced and innovative. Further, it sets the groundwork for a solid long-term plan for tapping into our valuable data resource without exploiting it – or the data subjects. Assurances like these will let companies stand out from the crowd and retain customers as they innovate.
About the Author
Christina Whiting is the managing director of privacy, enterprise risk and compliance at Tevora.
David Grazer is the privacy practice lead at Tevora.