Data Monetization Requires Balancing Data Availability and Governance
Data protection and careful access control can become part of the value equation when you monetize your data.
- By Zdenek Svoboda
- August 24, 2020
The use of data analytics is widely acknowledged as essential for making sound business decisions. Embedded data analytics technology is now being used to navigate increasingly choppy business, global, and public health waters. What's less widely acknowledged -- and used -- is the idea of data analytics as a revenue stream, a model that requires a careful balance of data availability and governance.
For providers of applications, portals, and mobile experiences, a product-first approach to data and data analytics enables them to take the vast amount of information their platforms generate, transform it into actionable insights, and make those insights available to customers in the form of customizable dashboards, reports, and other product offerings. Customers of these organizations can also use this information to improve their use of the platforms and thus the impact the platforms have on their businesses.
There are also providers' customers' customers to consider. SaaS and cloud platforms that integrate directly with customers' applications can deliver a seamless data-insights experience -- which translates to competitive value-add -- to their own clients.
The Move to Monetization
In a research study by Aberdeen, 36 percent of respondents said one of their main objectives for "embedding" analytics was to increase software revenue/market share through enhancement of product offering; 29 percent named the top objective as productizing and monetizing data.
That study was done two years ago, when many organizations viewed data analytics as a cost center. Today, more companies are recognizing that the data in their care can generate revenue and provide competitive advantage -- in other words, data analytics can be a profit center.
The operative phrase is "the data in their care." Effective and sustainable data monetization requires not just the availability -- or democratization -- of data, but also the thoughtful and purposeful governance of that data.
Providers need to understand all of the regulatory and compliance requirements governing the data to be monetized -- including auditability of all data, in motion and at rest.
Providers should offer -- and customers should demand -- robust governance protections for regulatory-sensitive industries such as healthcare, finance, and government. Many customers may require specific and scaled controls -- for example, for compliance around programs such as HIPAA, the GDPR, and CCPA.
From the provider side, all layers of the application from which data is being collected and analyzed must be protected, from physical security at the data center through the features used to authorize and provide access to users.
Other security, privacy, and governance systems that should be in place as companies move to monetize data include:
- Access restricted to only the data customers and their clients need
- Centralized authentication and authorization framework
- Role-based access control (RBAC)
- Data-based access control (DBAC)
- Use of encryption
With these and other controls in place, the protection of data itself can become part of the value equation.
For example, a governance framework can be used to assess the accuracy of the results surfaced by machine learning and artificial intelligence models, to assess usage and adoption data insights, and to ensure that updates and changes are being properly managed.
A Final Word
Data monetization enables organizations to create new revenue streams while adding "stickiness" to product offerings through actionable insights for customers. An effective strategy requires a focus on availability and customizability, as well as life cycle and change management, information quality, predictable scale, and governance.
About the Author
Zdenek Svoboda is the VP of platform at GoodData where he oversees product development given his expertise in analytics, enterprise architecture, cloud, and SaaS. You can reach the author via email, Twitter, or LinkedIn.