Data monetization remains a hot topic in boardrooms, yet many organizations still struggle to extract significant value from their data assets. Despite the enthusiasm around data monetization and AI, why do so many companies still fail to capture meaningful value from their data?
Drawing from Barbara Wixom’s seminal work at MIT CISR, particularly her IWS (Improve, Wrap, Sell) framework for data monetization, let’s explore three proven routes to create value from data, enriched with real-world examples from my experience working with some of the world’s largest organizations.
Barbara also leads an outstanding executive course on data monetization at MIT – I had the privilege to attend it recently and would strongly recommend it to anyone interested in this space.
Improve: Using Data to Enhance Internal Operations
‘Improve’ represents the foundation of data monetization, and research shows it still accounts for roughly 50% of all value extracted from data. Think about it: how much value is trapped in your organization’s data, waiting to be unlocked through better internal decision-making?
The ‘Improve’ route includes everything from optimizing supply chains to enhancing customer service, from refining product development to streamlining operations. While less headline-grabbing than external monetization, it often provides the quickest returns.
During my time at dunnhumby, we worked with a major retailer to leverage their customer transaction data to optimize their private label portfolio. By analyzing purchase patterns across customer segments, we identified significant gaps in their offering, leading to the development of new product lines that generated significant incremental revenue and customer satisfaction.
Have you fully explored how your internal data could drive operational improvements?
Wrap: Enhancing Products and Services with Data
The ‘Wrap’ route is about augmenting existing products or services with data-driven insights. What if your core offering could deliver significantly more value through data enhancement?
Think of it as a data-powered enhancement layer that transforms a basic product into a premium, insight-driven solution. This approach leverages existing customer relationships while creating new value streams. Stop for a second and think to this twice: leverage existing customer relationships for improved product and value creation, leading to increased revenues. No new customers needed, no new products needed.
At Yahoo/Overture, we pioneered this approach in digital advertising. By wrapping our ad platform with rich audience data and performance analytics, we transformed a simple ad placement service into a sophisticated performance marketing solution. This ‘data wrap’ allowed advertisers to optimize campaigns in real-time, increasing both value delivered and revenue per customer by an order of magnitude.
In fact, today’s digital advertising industry would be unrecognizable without these data wraps. What started as simple demographic targeting has evolved into sophisticated, real-time optimization powered by rich data layers. The entire programmatic advertising ecosystem is built on wrapping inventory with data to enhance its value.
Sports broadcasting offers another compelling example. What started as simple live video feeds has evolved into rich, data-enhanced experiences. Real-time player statistics, motion tracking, win probability calculations, and augmented reality overlays have transformed significantly how we consume (and enjoy) sports. Think about it: would you watch a Premier League match today without expected goals statistics, player heat maps, or real-time performance data? These data wraps have become so integral to the viewing experience that they’re no longer just enhancements – they’re expectations. And they have contributed to a significant increase in rights value, and customer satisfaction.
When was the last time you evaluated how data could enhance your core products?
Sell: Monetizing Data as a Product
This most ambitious route involves monetizing data or data-derived products as standalone offerings. Could your organization’s data be valuable to others in your ecosystem?
This requires a fundamental shift: from seeing data as a byproduct to viewing it as a product in its own right. Success demands not just high-quality data, but also sophisticated product management and deep understanding of customer needs. And much more (check Barbara’s work for details). It’s why many organizations aspire to this model, but few execute it successfully.
Leading the development of Walmart Luminate at dunnhumby exemplified this approach. We transformed Walmart’s rich customer data into a suite of insights products for CPG manufacturers. But perhaps most importantly, Luminate became the foundation for a new way of working between retailer and CPGs. The data and insights became the common currency for negotiations, enabling more fact-based discussions and collaborative planning with significant benefits for both sides, and substantial value creation for customers.
What would it take to transform your data into a product that others would pay for?
The Path Forward
Research shows successful data monetization rarely follows just one route. However, the dominance of ‘Improve’ (50% of value creation) underscores a crucial point: before looking at external monetization, organizations should focus on extracting value from data internally. It’s the low hanging fruit, requires less capabilities, smaller investments and has lower risk.
The key is creating genuine value for users. The core of data monetization isn’t about selling data – it’s about transforming data into insights that drive better decisions and outcomes.
What’s holding your organization back from extracting more value from its data?
This post draws from Barbara Wixom’s research on data monetization at MIT CISR. Her work continues to provide valuable frameworks for understanding how organizations can create value from their data assets.
If you know some examples of successful data monetization in your industry, please share to everybody’s benefit.