In the largest announced corporate transaction of the year, S&P Global entered into a $44 billion agreement to acquire IHS Markit, thereby forming a data solutions and services behemoth intended to rival Bloomberg, Intercontinental Exchange, and Refinitiv Holdings.
Despite a pandemic-impeded global economy, 2020 has been a year of big deals about big data. This announcement follows other multi-billion dollar corporate transactions involving data-centric and digital businesses such as Morgan Stanley’s acquisition of E*TRADE for $13 billion, Just Eat Takeaway’s acquisition of Grubhub for $7.3 billion, Intuit’s acquisition of Credit Karma for $7.1 billion, and Visa’s acquisition of Plaid for $5.3 billion.
Data Deal Implications
Moreover, the S&P Global-IHS Markit deal exemplifies the data land-grab that has been underway for the past decade, featuring Microsoft acquiring LinkedIn, IBM acquiring the Weather Channel, NASDAQ acquiring Quandl, and even the acquisition of IHS by Markit just four years ago. Certainly, one-stop-shopping for data has its attraction, but data product buyers are a bit more cautionary. “This marriage is not one I appreciate,” commented Claus Thorball, head of data procurement at DanskeBank. “By applying the S&P business mindset to the IHS Markit portfolio of services we are looking at a billion-dollar wedding, and customers will get stuck with the bill.” Other data procurement managers have voiced similar concerns over the monopolization of financial data products and services driving up prices, and therefore expect regulatory scrutiny of the deal.
Duncan Chapple, head of analyst relations at CCgroup, posited that while S&P will be “too busy digesting to work out what it has,” he also noted that the introduction of IHS Markit’s deep vertical expertise and data results in a strong set of vertical offerings that, similar to Gartner’s and Forrester’s horizontal research and advisory services, could see rapid adoption by enterprises.
Investors Love Data Businesses as Much as They Love Data
Indeed, markets in recent years have favored data-oriented business models. With market-to-book values nearly three-times higher than the market average, investors have come to reap, if not explicitly understand, the unique economic qualities of data.
Compared with financial and physical assets, data can be re-used and re-sold without it being used-up, the same data can be repackaged and licensed in nearly unlimited forms and formats, and using data typically generates evermore valuable data. Data is what economists refer to as a non-rivalrous, non-depleting, regenerative asset. Moreover, data’s inventory carrying costs and distribution costs compare favorably to most other kinds of assets, making it an attractive commodity to purveyors and investors alike.
Alternatives for Alternative Data
Data product company consolidation, however, are not the only data business play. Much like how Amazon, Ebay and Etsy offer online sales and distribution platforms for millions of manufacturers, independent data aggregators and marketplaces have sprung up over the past several years. Companies like DAWEX, Demyst Data, Eagle Alpha, and Datarade offer one-stop shopping for financial, demographic, corporate, legal, weather, consumer, scientific, geographic and other data compiled or generated by thousands of data providers big and small.
Not only do these nascent data marketplaces aggregate commercial data sources, but unlike the mega information services companies or data brokers, they provide match-making services for companies that want to find buyers for their own data.
Innovating with Information
Who is purchasing all these data products? Trading firms endlessly seeking new sources of alpha have modern-day data science sweatshops continually plugging new “alternative data” feeds into new and adapted analytical models. Retailers soak up social media, consumer and price elasticity data to better target customers with “next best offers”. Manufacturers integrate ratings and reviews to improve customer service and product designs. Construction companies and home-builders track population shifts, climate change and public utility plans. Logistics companies use realtime and long-range traffic and weather data to optimize routes and distribution channels.
And clever app developers around the world take advantage of all sorts of obscure data sources. For example, Iceland’s popular Íslendingabók mobile app integrates the country’s genealogy database to determine how closely related two people are so they can “bump their phones before they bump in bed,” per the app’s tagline.
The opportunities to leverage external data in high-value and innovative ways in every sector are limited only by the imagination of business leaders or the consultants they hire.
Data as the 21st-Century Factor of Production
Jeffrey Maron, global head of product at Compagnie Financière Tradition, commenting on the acquisition, says, “Data is the lifeblood of finance and this deal acknowledges the value of high quality data.”
Not just in the world of finance, data has become a fifth factor of production, creeping up upon or in some instances even supplanting the importance of land, labor, capital or entrepreneurship. IDC estimates that the market for external data approached $200 billion last year. This is likely to accelerate rapidly as businesses realize the pandemic broke their traditional trend-based models that analyzed only the company’s own historical data rather than incorporating external leading indicators.
Over three decades ago FedEx’s founder and CEO, Fred Smith, proclaimed that “The information about the package is just as important as the package itself.” Since then, this realization and mindset have swept across every corner of commerce spawning a sprawling marketplace for data, and endless opportunities for businesses to capitalize upon it.
A version of this article originally appeared in Forbes.
Doug Laney is the Data & Analytics Strategy Innovation Fellow at West Monroe Partners, where he helps clients generate greater value from their information assets. Doug originated the concept of Infonomics and is the best-selling author of "Infonomics: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage."
Doug is a former Gartner Distinguished Analyst and three-time Gartner Thought Leadership Award recipient, co-founder of the Deloitte Analytics Institute, adjunct professor at the University of Illinois Gies School of Business, and frequent speaker at industry conferences.