Data and Analytics Monetization: Data Strategy Is Business Strategy

To the uninitiated, monetization of data can sound sketchy, often conjuring up a scenario of reselling customers’ personal information. But opportunities to monetize data extend far beyond selling it to external parties, and into other goals that create new value for businesses. Organizations may one day formally account for their data as balance sheet assets –discussions about that are already underway.

Businesses are benefiting from new value they’re creating with data they already have. In this way, their business strategies — and data and analytics strategies — are inextricably linked. This post demystifies data monetization and explores how businesses can capitalize on insights they develop from their data. It promotes a pragmatic understanding of how investing in modern data and analytics capabilities — people, process, systems — ties directly to new ways of increasing revenue, reducing risk and driving operational efficiency.

Data and analytics strategy is business strategy – beyond offense and defense

Data monetization leverages data and insights for business value. It derives value by applying data to purposes other than those for which it was first collected. That value is typically realized by acting on insights that the data yields. It’s helpful to realize that there is a natural offense-versus-defense tension across driving growth and innovation, maintaining operational excellence, and effectively managing risk and compliance. A pragmatic strategy for data and analytics monetization will include leveraging data and analytics insights across all three categories previously mentioned to realize holistic business value.

For example, in recent history, businesses have been increasingly obliged to collect data – and data about data – to demonstrate compliance with new regulations. Historically, the financial services and healthcare industries in particular bore the brunt of these regulations. However, with General Data Protection Regulation (GDPR) in effect for the European Union since 2018, and various US Consumer Privacy Regulations (e.g., California Consumer Privacy Act of 2018 in effect since 2020), business leaders in all industries are discovering existing, and generating new, collections of data to meet regulatory requirements. Now, business leaders are beginning to recognize opportunities to put that data to new use.

Once, data collection was solely for the “compliance defense” essential to highly regulated industries. Now, businesses in all industries are playing defense: understanding where systems hold personally identifiable information, how it’s created and how it’s used. Leaders must not stop with mere compliance when so many other advantages can be realized from the same data collections.

Modern, digitally enabled business models and growth strategies are linked to effective use of data and analytics.

  • Consider a mid-sized bank with multiple lines of business including insurance, retail, commercial and consumer banking. The bank had an unrealized opportunity to use information they already possessed to cross-sell and upsell customers in new ways. For instance, when supporting a customer through a commercial real estate deal, they knew the customer was required to buy insurance – another product the bank sold. But inefficient use of data prevented recognizing and sharing that selling opportunity across functions within the bank. Instilling a practice of sharing data more effectively – knowing who’d benefit from knowing what – resulted in a rewarding new growth tactic.
  • Consider an online retailer who requested the same information from customers multiple times during a purchase transaction. Consumers got frustrated by these interactions because they were already having better experiences in other online stores. With too much re-keying of their information, consumers will gravitate to more efficient competitors – an action they can take in minutes. This retailer chose to use customer information they already had to pre-populate forms so buying would be easier for consumers.
  • Consider shopping for anything online; many of us have experienced searches where effective filtering of results was impossible. A consumer shopping for chairs couldn’t search effectively by seat height, a key selection criterion for her – so she took her business to another online retailer whose product data was clean and organized enough to support efficient searching. In a time when consumers can shop elsewhere in minutes, low-quality data can cost online retailers significant business.

There’s value in deeply understanding the customer, having all customer-related data in a well-defined, available form, at all times. Likewise, well-organized and complete data about products and services enables better search experiences, discoverability and personalization. Since only data and analytics of appropriate quality can be confidently monetized, investing in effective data governance is foundational to ensuring trusted, ethical, and resilient data and analytics-informed products and services.

Developing a monetization strategy

An effective data and analytics strategy recognizes that data has little inherent value. Data’s value is unlocked by putting it to work in the form of insight. The insights generated from the data convey its value. Data professionals should start their strategy development by understanding the concerns of their colleagues – from board room to back office. Business leaders must recognize the value potential data and analytics monetization represents before they’ll get motivated to invest resources and effort in a winning data and analytics strategy. Data and analytics professionals will have trouble getting business leaders interested in nuts-and-bolts matters like data governance and data science if business unit leaders don’t see data monetization’s real-world potential first. What are business leaders’ goals, challenges and aspirations? How do they want to generate new revenue, reduce risk, enhance operational processes? Follow through on business leaders’ answers to questions like these, then consider what data and analytics assets are already available – anywhere in the organization – to derive the insights the business needs.

Consumers want their data leveraged to the fullest extent possible, legally and ethically, to make their lives more efficient, easy and enjoyable. In financial services, for instance, it wouldn’t be difficult to recognize that a 529 college saving plan likely indicates there’s a baby in the household and offer a review of their life insurance holdings. In retail, it’s advantageous to personalize a home page based on a consumer’s past shopping experiences.

Consumers see the benefit in allowing businesses to use personal information and transaction histories to build relationships in which mutually advantageous opportunities can be exposed within a framework of trust. In fact, they’re expecting it. That’s a powerful impetus for leaders to invest in their data and analytics capabilities; to apply the discipline needed to make data accessible, trusted and well-defined. It calls for promoting data literacy throughout the organization, raising awareness among business leaders, thinking critically to develop creative insights — and breaking down the silos that conceal opportunities.

Building a data and analytics monetization culture

The objective that drives data monetization culture is to generate more value – legally and ethically – by finding new applications for data and analytics assets the organization already possesses. Building that culture requires leaders to invest in a data and analytics strategy that supports serving customers in a responsible way. It’s a challenge that may call for more diverse skill sets, updated processes, cultural change and new systems to achieve.

A data and analytics monetization culture is fundamentally enabled by two things: business leaders’ understanding and enthusiasm for data and analytics monetization’s potential, paired with a strategy to reach that potential. A business value-driven data and analytics strategy can enable great customer experiences, innovation and revenue, risk reduction and operational efficiency. However, it must be built solidly on a foundation of governance, privacy and security, fit-for-purpose architecture, ease of use, and data and analytics literacy.

Unlocking the insights residing in data to create value starts with raising awareness among business leaders. Leaders must first appreciate data and analytics’ potential before they can get interested in establishing a culture that is data- and insights-driven, thus driving the appropriate investment in capabilities that will achieve the potential value that data and analytics monetization represents. Leaders’ enthusiasm and clear understanding of data and analytics’ capacity to deliver value is essential to power the organization through efforts to design, build and operate the capabilities that will generate new value while sustaining customer trust.

To learn more about our data and analytics services, contact us.

Mark Carson

Managing Director
Enterprise Data and Analytics

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