Information has become a primary form of capital—to businesses that know how to monetize their data, that is. Organizations that embrace the art of the possible in data monetization stand to create new capital from data sources and ultimately transform their business models. In doing so, however, they must maintain a sharp focus on data privacy.
Capturing and monetizing data will require intelligent, connected systems and processes that help ensure that data and privacy are managed with the same rigor as traditional assets. The good news is that, as the volume of data has multiplied, the technologies for capturing, analyzing and storing information have become more powerful—and less costly.
In recent years, businesses have adopted technologies such as cloud-based data management, artificial intelligence, machine learning and predictive analytics to more efficiently run their operations. Now, many are applying these technologies to data monetization, creating specific algorithms to manage, store and analyze huge internal and external data sets.
And they are doing so affordably. Most leverage open-source software such as Apache Hadoop, Spark and Kafka to implement real-time data-management and analysis capabilities. These open-source tools, available at little or no cost, enable companies to gather and analyze data without significant investments in software.
Certain technologies, however, can be detrimental to data privacy. For instance, organizations are using AI and machine learning for surveillance to help monitor for terrorist activity. These technologies have been implemented with few regulatory provisions, and the line between surveillance and individual privacy is one that may be easily crossed.
The titans of high tech, not surprisingly, have the advantage when it comes to protecting the privacy of monetized data. For these, data is the very lifeblood of the business, and in many cases sophisticated data management and analysis capabilities have been at the core of business ecosystem from the start.
Digital-first companies were among the first to understand the alchemy of using data to transcend industries. Apple and Google, for instance, moved into the financial services sector several years ago with the launch of Apple Pay and Google Wallet.
The move toward data monetization extends beyond tech firms. We’re seeing telecommunications, financial services and automotive companies successfully turn data into new services and revenues.
Monetization is a natural fit for telecommunications providers, which typically have industry-leading data-management and privacy capabilities, as well as state-of-the-art business support systems. These technologies provide a ready-made platform for monetization of data, allowing them to enter new industries such as financial services.
Automakers, meanwhile, are racing to monetize data generated by in-vehicle telematics and communications systems. Telematics can generate a wealth of valuable information, including data on vehicle performance, location and driver behavior. Most automakers are already ingesting and analyzing this data.
In fact, almost two-thirds of respondents to PwC’s Global State of Information Security Survey 2017 said they collect telematics data on vehicle location, while 44% gather driver data. And they’re not just hoarding information: More than one-quarter said they sell telematics data and an additional 25% plan to do so over the next 24 months. They understand that this information is data catnip to insurance companies, OEM aftermarket manufacturers and retail advertisers, among others.
It’s clear that businesses will be unable to generate new revenue from data sources without leading-edge data-management and analytics capabilities—and data-privacy processes that underpin customer trust.
At PwC, we work with companies looking for the right infrastructure to monetize data while maintaining customer privacy. For many, that means that applications for ingesting and analyzing customer behavior data must be built on data privacy and secure data transfer principles.
Another challenge is the arduous task of integrating data across businesses units. Doing so requires expertise in mapping and combining disparate types and sources of data, as well as integrating data sets with analytics services. To realize the full potential of monetization, businesses often need to enrich their information with market or third-party data.
More and more businesses also want help building fee streams from new data businesses. This often requires establishing data and analytics units to map and integrate data across the business and fuse anonymized internal data and analytics capabilities with external research.
Companies that implement data-monetization capabilities will be positioned to create new service offerings and revenues while maintaining data privacy. Done right, monetization of data represents a truly transformational opportunity for companies to evolve into an entirely new type of business, one built on the capital of information. Businesses that do so can make the possible profitable.