Thirty years ago, consultants Stan Davis and Bill Davidson wrote a book called 2020 Vision in which, not surprisingly, they laid out their vision what would happen by 2020. I am not quite ambitious enough to review all their predictions, but one is of particular interest to me. In fact, in a Wall Street Journal column 7 years ago, I wrote this about one prescient Davis and Davidson prediction:
a company’s “information exhaust” (information byproducts gathered in the course of its normal business) could be used to “informationalize” a business (develop products and services based on information).
I wrote then that big data companies were beginning to make use of data (fewer syllables than information, roughly the same thing) exhaust, but it’s been a slow trend to go mainstream. Many companies lacked the rich data, the technical skills, and the business insight to create new products from data exhaust. Just as we didn’t figure out how to use engine exhaust to power cars until turbochargers became widely adopted, most companies haven’t had the turbocharging mechanism in place to make data-driven products and services feasible.
Data & Services at Mastercard
One company that clearly does have turbocharging capabilities for data exhaust is Mastercard. Specifically, its “Data & Services” business unit, led by Raj Seshadri, seems to have all the necessary components. I knew that this organization existed, having co-authored an article recently about Mastercard’s Chief Data Officer, JoAnn Stonier. But I didn’t realize what a great example it is of developing an organization that can turbocharge performance with data exhaust.
It may be possible to find someone better than Seshadri to play the role of President, Data & Services, but it’s difficult to imagine. Initially trained as a Ph.D. in Physics, I told her—and she agreed—that she might have become a data scientist if she’d gotten that degree (from Harvard) a few years later. After a short postdoc at Bell Labs, she got an MBA from Stanford, ventured into consulting at McKinsey for a decade, and became a partner there. She then worked at several large financial institutions, including US Trust/Bank of America, Citi, and BlackRock in roles ranging from sales to marketing to strategy. Then she came to Mastercard to lead its work with banks and credit unions in the U.S., before taking on her current role in early 2020. A leader of Data & Services would need to know something about data as well as the business contexts in which it is used, and both are undeniably present in her background.
Mastercard doesn’t report financial results separately for the Data & Services unit, so it’s difficult to assess its size and performance. But then-CEO Ajay Banga said at an investor conference in 2019 that the company’s services lines (which include data & services, as well as cyber & intelligence solutions and processing) represented about a quarter of its roughly $15 billion in 2018 revenue. In a more recent Fortune interview, he implied that those businesses comprised a third of the company’s revenues. In short, Data & Services is a significant business in itself.
There are multiple components to the Data & Services business, including:
- Analytical services
- Marketing services
- Innovation services
- Software platforms such as Test & Learn
- Loyalty services
Seshadri notes that for any given client project, “All the ingredients are already in the pantry—it’s just a question of how to cook up the right meals.” The overarching principle of the business, she said, is simply to use data and analysis to make smarter decisions with better outcomes for customers.
But how does Mastercard Data & Services do that? There seem to be several different components that make the business work. I’ll describe four here: the data, the software, the methods employed, and the people.
The Data and the Ethics Behind It
Mastercard’s payments data is clearly the core asset of the Data & Services business. As the unit’s website notes upfront, “Mastercard’s real-time, anonymized and aggregated transaction data is the world’s best resource for consumer-facing businesses to develop a holistic view of the behavior of different consumer segments.” Mastercard now has about 3 billion cardholders who make about 90 billion transactions at about 70 million merchants through about 40,000 banks and financial institutions in about 210 countries and territories. That adds up, of course, to a massive amount of information on the purchasing trends of humans. Seshadri confirmed that most of Data & Services’ engagements with clients make use of the insights.
Data & Services has a variety of “data products” based on this data asset. SpendingPulse, for example, which measures overall retail spending including estimates of check and cash spending (extrapolated to the government definition of Total Retail Sales) and issues monthly reports across various countries, industry sectors and channels, began in 2002. Its clients include governments, merchants, banks, and many other types of businesses. Business Locator is another data product that is particularly valuable in this pandemic, as it provides information on what businesses are open based on whether they are doing Mastercard transactions.
I learned when interviewing JoAnn Stonier, Mastercard’s Chief Data Officer, that the company has a strong focus on data privacy and ethics. It makes perfect sense that the company wouldn’t destroy the value of its data assets by not safeguarding the data or abusing consumer privacy. It has a well-articulated set of “Principles of Data Responsibility” that it released in 2019.
The Software Tools
The data turbocharger at Mastercard wouldn’t be complete without a set of software tools to analyze the data. Mastercard has made a number of acquisitions in recent years of technology firms. Some are fintechs that enable new or more efficient financial transactions, but several are primarily oriented to data analysis and are part of the Data & Services portfolio. I’m most familiar with an offering called Test and Learn, which is based on an acquisition of Applied Predictive Technologies (APT) in 2015. I wrote in a 2009 article before APT was acquired that its software “leads users through the test-and-learn process, keeps track of test and control groups, and provides a repository for findings to be usefully accessed in the future.” Presumably it still does that, but now it has plenty of purchasing data to use as a dependent variable in a wide range of business experiments.
Some of the other analytics-oriented software businesses within Data & Services include Cytegic, a cutting-edge cyber risk assessment and management platform; and Session M, a customer data and loyalty platform based in Boston.
Seshadri said that although there are a diverse set of services and offerings within the business unit, there is a common methodology that is used on client engagements. It is centered on the key opportunity or challenge a customer is facing, and has the following steps:
- Discover—Look at all available data that’s relevant to the client and business issue, and responsible to use
- Recommend—Apply analytics and consulting to tease out meaningful insights
- Act—Executing the proposed solution—at this step Data & Services typically gives the customer a choice about whether Mastercard will implement the solution, help with implementation, or make recommendations for it;
- Improve—Measure the impact, and determine how to make the results better over time.
This is a straightforward set of activities that might be found in any data-oriented services business, but it’s probably useful to have a common framework for working with clients and attempting to improve their businesses.
In any services business, a key success factor is having great people. Data & Services doesn’t reveal how many people work in the unit, but there are clearly a good number of them. One account of SpendingPulse said that the company overall has 2000 data scientists, many of whom probably work in Data & Services. There are also a number of economists, at least some of whom work in the Mastercard Economics Institute, a part of Data & Services. The Institute was launched in 2020, and provides both customized insights for clients and a series of public reports. One series is called Recovery Insights, and was intended to help businesses and governments recover economically from COVID-19. Its reports address topics like “The Shift to Digital,” “Travel Check-In,” and “2020 Holiday Shopper.”
Data & Services also has a large number of consultants, and they are located around the world. This isn’t new; the Mastercard Advisors consulting business was created in 2001. It has a focus at the intersection of payments and management consulting; a job description for a “Senior Managing Consultant—Advisors” in San Francisco describes the role:
“We combine traditional management consulting with our rich data assets and in-house technology to provide our clients with powerful strategic insights and recommendations.”
Lessons for Other Data-Rich Firms
So if your company has a lot of data and you think it may be valuable as the basis for products and services, the Mastercard Data & Services business unit will certainly be instructive. The key lesson is that you need a variety of capabilities to surround the data with value. You need to be fully committed to the data-driven business idea in order to assemble these resources, and you need to be sure that your data is sufficiently valuable to be worth the trouble. Mastercard’s clearly is, and it has been proving that assertion for at least twenty years by now.