Monetizing data and technology can help unlock future growth—here’s how to take advantage of the opportunity

The state of play

Many technology leaders recognize the inherent opportunity in data. In Deloitte’s 2023 Global Technology Leadership Study, data and insights ranked among the top three tech capability areas organizations plan to focus on in the next two years.

“One focus for us is data and analytics,” says Sathish Muthukrishnan, Ally Financial’s chief information, data, and digital officer. “It’s not about understanding data of external customers; it’s understanding data about internal customers—how they’re working, how we can make them better, and how we can improve their lives. By stitching data across the company, you can ultimately understand the business of technology and become that ecosystem orchestrator.”                                           

While some organizations are moving along their data journey, others may still not be ready or giving data the attention it deserves—by their own admission (figure 1).

Data management and analytics doesn’t even rank in the top five areas of where tech leaders currently spend the majority of their time, effort, and energy. It landed at no. 6 on the list behind business/digital strategy execution (no. 1); security, risk, and compliance (no. 2); business/digital strategy development (no. 3); innovation (no. 4); and operational reliability and delivery (no. 5). Why the lower ranking? It could be because the research also shows that there doesn’t seem to be clear consensus around who is responsible for data. Thirty-five percent of respondents said CIOs oversee data governance at their organizations; 34% said it’s a joint effort between business and tech leaders; 21% said their C-suite and tech leaders partner on these efforts; 8% say it’s driven by executives outside IT; and 2% said there was no clear ownership.

That’s not to say tech leaders aren’t investing in these areas. When asked which data and insights capabilities their organizations are actively investing in, the three focus areas were advanced analytics (62%), data infrastructure modernization (60%), and foundational data management (59%); data monetization was at the bottom of the list (figure 2).

In a way, this makes sense—companies likely can’t begin monetizing their data if they don’t have quality data and strong data management practices in place.

“I am passionate about innovation and when I got here, I said that it's no use talking about the future if we don't have a strong data structure,” says Robert Nunes, chief technology and digital officer at retailer Portobello Shop. “First thing we did was create a program to review our systems architecture, our integrations, and our data from the consumer's perspective. There was no recipe to follow. Different retailers need to do different things. But once we had a strategy around these elements, we could then think about cloud, digital transformation, and what’s next.”

“Our business is increasingly dependent on the insights coming from our data,” explains Pablo De la Puente Mora-Figueroa, CIO of Gestamp, a global automotive engineering company. “A key success factor in data and analytics is having a homogeneous and standardized set of systems, both transactional and informational. The more homogeneous, the faster you can get value from data.”

Even if organizations are still laying a foundational data infrastructure, tech leaders should still be thinking now about how to monetize their data in the future. Otherwise, it could be a missed opportunity.

To do so, executives should see the promise and value of data and prioritize it accordingly. Currently, less than a third (31%) say harnessing data (Internet of Things, customer, operations, and public) to deliver insights and generate revenue is a top priority for their tech function. Yet, leveraging data and insights is, in part, what could allow organizations to fulfill their top priority, which, according to Deloitte’s survey, is optimizing business processes for cost and efficiency.

“There is no digital transformation without organizational transformation,” says Elena Liria, managing director at Madrid Digital. “We need a good, solid data governance strategy to be able to know our citizens better and tailor our services.”

Four approaches to data monetization

Once companies have established strong data management and governance practices, they can consider monetizing their data. This transformation is not without its challenges, but the good news is many organizations, both tech and nontech, already have data assets that can be monetized.

Some key data domains and types of data that organizations can use to drive internal value and external revenue generation include raw data, curated data, and third-party insights (figure 3).

So how do tech leaders do it? Here’s a look at four strategies companies across industries are using today to monetize their data—and the benefits they’re seeing as a result:

1. Sell data sets: One method of providing ongoing value through data monetization is by selling raw or curated data directly to customers as a one-off transaction, which may repeat over time as a discrete batch of business intelligence.

Flatiron Health, for instance, provides aggregated and deidentified patient electronic health record data to researchers for use in oncology research, clinical trials, and personalized medicine. By deriving data from diverse patient populations (Flatiron Health has more than 3.5 million patient records from more than 800 unique sites of care²), the organization is helping enable diversity in clinical trials.³

2. Sell insights: Platform-as-a-service models comprise another suite of technologies that allow companies to store, analyze, and share data with their customers through drillable and customizable reports.

One example of this is Mastercard’s efforts to provide market-based data to help a national department store understand its high-end customers. The store used Mastercard’s Market Basket Analyzer to analyze data sets over time, thereby gaining stronger insights into shopper behavior. The tool includes signals that helped the retailer evaluate customer visits, and in the process, uncover data on basket size and composition based on different shopper segmentations.

The Mastercard solution found that the average shopper who purchased from the new product line spent more than US$400 per visit, with almost US$300 of that total on a new luxury product. The tool also evaluated shoppers’ purchasing behavior before and after the new product line launch, further helping the department store understand trends, identify opportunities, and make data-driven decisions to optimize performance.⁴

3. Embed data and insights into existing offerings: Embedding curated data and insights into existing products is another method that technology leaders can champion to help generate additional revenue.

eBay, for instance, is using recent supply, demand, and pricing data for customers to identify how products and categories sell across all eBay marketplaces. Its proprietary Terapeak product research tool includes access to years of real-world sales data, offering insights into aspects like the number of listings and items sold, average sales prices, item conditions, sell-through rates, shipping costs, and availability of free shipping. In addition, Terapeak provides information on seller and buyer locations, sales trends over time, unsold inventory, and the listing formats preferred by sellers. By combing through data from millions of transactions, eBay is helping sellers make more informed decisions about listings.⁵

4. Sell to and through ecosystem partners: Yet another way for tech leaders to explore data monetization is by selling data and insights through collaboration with a data aggregator or another similar partner that will in turn sell that data to third parties for commercial use.

One example of this would be a company that collects real-time data from electric, connected, and autonomous vehicles and combines this data with information from another company to create a robust view of road and mobility conditions, for instance. These millions of data points can then be shared with automakers, who in turn can use these insights to enhance vehicle safety and alleviate congestion on the road.

While the data monetization journey will vary by company, it’s important to note that these approaches can work in conjunction with one another—and all should prioritize data privacy and protection. The regulatory environment around data sharing continues to evolve across the globe. Organizations should keep an eye on evolving trends that may govern the data sharing landscape. If in doubt, do not share or sell.

Successful monetization may also require the democratization of data. Data should be easily accessible throughout the organization. This often calls for a coordinated interplay between data platforms, data culture, and data processes, as well as effective communication and collaboration among all data stakeholders, including tech and business leaders, data strategists, data owners, data scientists, and data stewards.

Monetizing tech to drive lasting value

Creating new products and services is the third largest organizational priority, according to the Deloitte survey. Another way tech leaders can deliver on this goal and drive value is by monetizing the very same software that is—or has—driven their business forward. Consider Lenovo for instance.

“In order to accelerate our commercialization journey, we initiated a corporate strategic program called ‘Lenovo Powers Lenovo’ where tech and business teams work together to validate, reshape, and put forward our proprietary products and solutions,” says Art Hu, senior vice president and global CIO at Lenovo. “One example of this journey is Lenovo xCloud, which is a hybrid cloud solution that helps customers build, migrate, utilize, and manage the cloud. It was originally a solution built by Lenovo’s IT team to use as an infrastructure platform internally, but it was such a success story that business teams often requested for it to be commercialized for customers. Once it became clear that xCloud could also help customers manage their complex cloud environments, product teams started working on a go-to-market and productization strategy for it.”

While xCloud has been a success for Lenovo, Hu acknowledges that commercializing tech does not come without obstacles. “One major challenge has been how to formulate a minimum viable product (MVP) that can be marketed effectively,” he explains. “When the tech team provides services to Lenovo internally, it’s generally focused on realizing business value with a whole set of functionalities. However, for a product to be marketable, there needs to be a standard product template that’s adaptable to different customer situations and flexible for configuration. For us, this was certainly a big challenge at the beginning, but by proactively reaching out to customers and understanding their requirements, we’ve gradually developed an approach that works. One of the key success factors is to get rid of company-specific features and focus on replicable functionalities.”

Commercializing their tech has led to several benefits. “The journey has contributed to a trusted and reliable partnership with our customers by bringing Lenovo’s validated solutions and experiences to help them succeed in digital transformation,” adds Hu. “It also helps internal tech teams learn about the market as well as our customers and inspires them to build more competitive offerings and services. Apart from a new business opportunity, commercializing has also been a catalyst for the tech team to transition from being more traditional back-office to a customer-oriented team. With two-way interactions around internal deployment and customer practices, it becomes a dual cycle to help both Lenovo and our customers grow capabilities in the long term.”

For Vanguard, software and data have also become true assets for the firm, ones that are driving new possibilities for strategic growth.

During a strategy meeting in Colorado, Vanguard’s leadership team uncovered that the next engine of growth for their organization was a global cloud-native platform that would allow them to roll out their low-cost financial advice both digitally and through Vanguard advisers. To build it, they created an internal startup constituting people from their wealth management, investing, marketing, product, and technology teams—and intentionally placed the group under the direction of the CIO.

“Why the CIO? Because the differentiator here was the technology,” says John Marcante, former global CIO of Vanguard and US CIO-in-residence at Deloitte. “We knew if the technology was done right, it would lead us to the goal we laid out. But more importantly, it would lead to additional areas of opportunity that we hadn’t even dreamt about yet—and that’s exactly what happened.”

Vanguard’s initial financial advice platform in the United States served as a catalyst to building additional advice capabilities, both in the United States and across the globe. As use of the global cloud-native platform grew, two things happened.

“We soon realized this platform was a source of data and insights on our investors’ preferences and behaviors,” explains Marcante. “Further, it offered value in helping us understand and maximize how advisers spend their time and add value to their clients. While we initially built these capabilities to better serve our own clients, we soon realized these same capabilities can be used by other organizations to serve theirs as well. It’s a trend I only see continuing. Software and data will increasingly drive the future of organizations and create new possibilities for growth.”

Lessons on monetizing data and technology

Unleashing a vision for monetizing data or technology can help organizations gain a competitive edge, and every leader in every industry can begin the journey. Here are a few strategies to consider as you’re getting started.

• Start with a customer need and have a compelling value proposition: This may sound rudimentary, but it is surprising to see how often monetization efforts either fail or don’t reach their full potential because they’re not led by the entire business. If these initiatives are only driven by the tech function, they can often become a systems exercise where IT merely grants access to data and adds analytics tools in the hopes that people will use them.

But monetization is like building any other product or service business. It should start with an unmet customer need in the market, have a compelling value proposition, and a viable business model.

Work to confirm that value proposition is unique. When it comes to data, for instance, organizations may talk themselves into thinking that their data is valuable simply because they have so much of it and it seems to address a customer need. But companies should spend sufficient time looking at the competitive landscape to help ensure they either don’t end up commercializing data or products/services that already exist in market (or can be easily copied by competitors) or target a need that is already well-addressed.

“Don’t underestimate the amount of time, effort, and cost it takes to define and build a customer-ready offering for the market compared to an internal IT deployment,” recommends Lenovo’s Art Hu. “It’s not an easy journey to create a marketable product from an internal solution. It’s a long process requiring continuous dedication and investment, so persistence is a must. It’s also important to make sure you get in front of customers to test the value proposition. Only with their feedback, both good and bad, will you be able to iterate and move towards product-market fit.”

• Prioritize your monetization efforts based on an accurate evaluation of options: Since many organizations have monetization opportunities, leaders should have an established framework for accurately assessing each opportunity. Otherwise, they could struggle with prioritization and capital allocation. Deloitte Germany’s Artificial Intelligence and Data Valuation (AIVA) Framework⁶ is one possible tool to kickstart the data valuation journey. It is designed to not only accurately assess the value of an organization’s data assets, but it also includes an operating and governance model as well as a repository of industry-specific use cases to accelerate value delivery.

“As a company, it can help to take a portfolio view of the various ideas you have for commercialization,” explains Hu. “Due to the inherent uncertainty, not all ideas and features will convert into commercially viable ideas, but it’s important not to get discouraged.”

• Pick a monetization leader with technical chops: When asked who in their organization is primarily responsible for the commercialization of tech-enabled assets, respondents in Deloitte’s Global Technology Leadership Study primarily said the CIO (46%); the same response was noted for data monetization (38%).

Tech leaders often lead or colead these monetization initiatives because it’s ultimately technology underpinning the success of these efforts. But it’s not just CIOs who can lead the charge. It could be the chief data officer (CDO), a business executive with data and insights experience, or a commercial leader who is tech-savvy. What matters is that this leader has a deep understanding of tech and doesn’t see these efforts in terms of how much they cost but rather how much value they can bring.

“The technology org at Ally is no longer a cost center, and I don’t think of it that way,” says Ally Financial’s Sathish Muthukrishnan. “I think of technology either as a value generator or a revenue generator and how what we do connects to that is more critical than anything else.”

• Build a cross-functional team that can think big and align on a cohesive strategy: While monetization efforts need a key leader, they’re ultimately a team sport. Driving direct or indirect revenue through data and tech is shared—and so is the responsibility for seeing it done well. For monetization efforts to be successful, the whole organization should define and align to a common understanding and cohesive strategy.

That can mean a joint effort of the board, chief data officer, CIO, chief financial officer, and business- function leader—people who understand where data and tech capabilities are mature and ready for prime-time, and who are sensitive not only to the business opportunity but also to feasibility and potential obstacles.

“The advice I have for other tech leaders is to break out of the 1970s data processing mindset. Mainframes and green screens are long gone, but 50-year-old organizational structures that relegated technology and those building-sized mainframes to the basement live on,” says Diogo Rau, executive vice president and chief information and digital officer at Eli Lilly and Company. “Spend your time with the rest of the C-suite and board on the big ideas that will change not just your company, but the industry as a whole. Data will always be a shared responsibility. Even though we have a chief analytics officer, that doesn't mean that everything that's data-related all has to roll up to one person.”

This cross-functional team should be able to think big. It can be very easy to use data, analytics, and technology for tactical or operational purposes. But the real value of monetization is envisioning and driving bold ideas. This requires courage and a willingness to explore unchartered territory.

“The things that are really going to propel an organization forward require courage,” says Brian Lucotch, president of enGen, a subsidiary of Highmark Health. “Being courageous—that’s what’s really going to propel change at the end of the day.”

• Think of your organization as the first customer, not the only customer: Your data or technology may have applications beyond what your team has even envisioned. To see those possibilities, leaders may need to shift their mindset around who their customers are or could be.

“We think of Ally as the first customer, not the only customer,” says the organization’s chief information, data, and digital officer Sathish Muthukrishnan. “After we [leverage our tech] to drive efficiencies internally, we white-label our software services to other businesses to generate revenue—balancing these two creates immense value from technology.”

• Don’t confine yourself to the industry you’re in: Just because you’re a financial services company, for instance, doesn’t mean your technology (and/or data) can’t serve beyond that sector.

One financial services company we interviewed, for example, no longer views itself as just a provider of retail financing; it considers itself to be a platform business, one that can (and does) provide services to other brands. The company has architected its business and technology so that anyone within its ecosystem can incorporate the capabilities it has built into their own systems. Whether it be payment or insurance capabilities, this company is helping improve other organizations—and benefitting as a result.

• Create robust oversight and feedback loops: Other reasons monetization efforts could fail is because they take too long, are costly, and sometimes feel like science experiments. One way to overcome these roadblocks is to have a robust decision structure that defines success measures and allows for quick decision-making.

One large manufacturing company we interviewed for the research held a weekly stand-up meeting while developing software that would commercialize their services. These sessions included both business and technology stakeholders and the single purpose of these meetings was to remove obstacles for the execution team. It paid off. The company was able to reduce the development time from an average of three years to nine months, ultimately giving them significant competitive advantage.

• Consider the many facets of monetization: Successful monetization brings in new revenue, yes, but there are many other facets to monetization to consider. It’s not just about the hard numbers and the bottom line. Successful monetization can also mean increased resilience and even an eye into the future.

Consider that one organization, for instance, leveraged data to predict future disruption. “When the pandemic struck, my data science team got to work on creating predictive models with our data,” says a former executive at a large multinational food industry company. “We were able to foretell the closure of a certain factory almost to the exact day in early April 2020.” Having such detailed insights into the operational resilience of your organization—and being able to mitigate disruption ahead of time—can help prevent losses.

Unlocking the untapped value of data and technology is an urgent need for many organizations to stay competitive. But monetization shouldn’t be viewed as a one-time project. It’s a journey that requires ongoing investment, regular maintenance, and continuous improvement. These efforts require a bold vision and a long-term commitment.

When done right, it can pay off. By monetizing data and technology, businesses can position themselves at the forefront of their industries, create new revenue opportunities and catalyze growth. The path to realizing the true value of data and tech lies ahead, waiting for those bold enough to embark on this transformative journey.

The opportunity is clear. The question is, will you embrace it?