How can I Maximally Monetize my Data without Exchanging & Exposing Sensitive Information?
In 2017, The Economist published a report titled “The world’s most valuable resource is no longer oil, but data.” The report explained how digitally-native organizations like Facebook, Google, and Amazon were leveraging data to achieve high-growth and market disruption.
In the two years since The Economist’s article was published, organizations of all sizes have jumped aboard the digitalization wagon, investing millions of dollars in technology and processes to gather and analyze data. The main goal of going digital is data monetization.
What is data monetization?
Data monetization is the process of extracting insights from data in order to create value for the customer and the business. In a survey by McKinsey & Company, organizations mentioned that they monetize data by adding new services, developing new business models, and joining with similar companies to create a data utility.
In a recent survey, Gartner went deeper in understanding how organizations are monetizing their data, exploring both their present and future approaches:
Data monetization is no longer a nice-to-have strategy. It is a requirement for any enterprise that wants to compete. In the same McKinsey & Company survey, respondents described how incumbents are being disrupted by new entrants who are better at monetizing their data, or by traditional competitors who use data to improve their businesses.
Unfortunately, data misuse and data breaches have made governments and customers react negatively to the way organizations are using their data. Facebook – whose unethical practices were revealed during the Cambridge Analytica scandal – are the best example of a company with enormous data power that has abused customer trust. In response, governments from all around the world are pushing privacy regulations that control how organizations use customer data. Data is no longer flowing inside and among organizations. Instead, in order to prevent risk, restrictions and siloes are being created. As a result, large digitalization investments are lagging and ROI’s are getting squished.
Data Monetization 2.0
Recent advancements in cryptography and privacy techniques offer organizations new tools for monetizing data – tools that don’t risk exposing or exchanging sensitive information. Three of the most promising new technologies are Differential Privacy, Secure Multi-Party computation, and Fully Homomorphic Encryption.
Differential privacy, as The Conversation outline, “makes it possible for tech companies to collect and share aggregate information about user habits while maintaining the privacy of individual users.”
Differential privacy is a technique that injects “noise” into a data set, with the objective of reducing the risk of re-identification of an individual. With Differential Privacy, the probability of someone being present in a data set is the same as the probability of them not being present in that same data set – thus protecting the privacy of the subjects in the data set. After applying Differential Privacy, organizations can monetize their data with a high degree of certainty that no sensitive information will be exposed or exchange.
Differential privacy has been adopted by large tech companies like Google and Apple as well as by the US Census Bureau.
Secure Multi-Party Computation (MPC)
As described by Boston University researchers, “Secure Multi-Party Computation allows us to collaboratively analyze data for the public good without revealing private information.”
MPC is a cryptographic technique that allows various parties to compute a function using everyone’s inputs without disclosing what those inputs are. Since the inputs are never disclosed, the sensitive information is always protected.
MPC gives organizations two major data monetization benefits:
- Better Insights: Organizations can now expand their internal data with data from partners in a way in which everyone’s sensitive data is never exchanged, but everyone derives more and better insights from the augmented data sets.
- Renting Data: Data assets are extremely valuable. However, the value is lost once they are sold. With MPC, organizations can allow partners to benefit from the data without having to sell it, increasing the value of the data asset.
Fully Homomorphic Encryption (FHE)
Fully Homomorphic Encryption (FHE) is a cryptographic technique that allows for computations to be performed on encrypted data. Once data is encrypted, it becomes fully anonymized, thus preventing any sensitive information from being exposed.
In theory, FHE is the best way to monetize data without exposing or sharing sensitive information. However, in reality, this technique is extremely slow and computationally expensive. This means FHE isn’t a viable option for real commercial applications.
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