How much is big data really worth? That's the question analysts have been tackling. Some suggest big data is becoming more dominant in determining the valuation of a company. There's been a shift in the way organizations are valued, from those that own tangible assets to those that were built on big data, like Facebook and Uber. Those in the business of valuing corporate investments will increasingly be forced to "consider a company's wealth of information in properly valuing the company itself," says industry analyst Douglas Laney.
By 2021, Gartner predicts that equity analysts will eventually adopt formal internal information valuation and auditing practices to accurately determine the value of an organization. To illustrate the importance of this, Facebook's market capitalization is around $385 billion; whereas, United Airlines, a company that actually owns large assets such as airplanes and licenses to airport facilities and transoceanic routes, among other things, has a market capitalization of $24 billion.
To analyze the perception of how influential big data is in determining a company's value, technology consulting firm Capgemini surveyed 1,000 senior decision-makers in nine regions and nine industries to assess where the market is heading. The results show that 64 percent of companies believe that big data is changing traditional business boundaries, while 58 percent expect to face increased competition from startups enabled by big data.
Big data is all about business disruption, the report indicates. The real battle in business is for data that delivers the "most relevant and pertinent insights - the combination of data sets that enable effective and more rapid monetization of data," the report reads. "Your data could ultimately become more valuable than your traditional product or services. Big data technologies are the enabler for developing new business models to make that happen."
If big data is such an important aspect of success in business, then it needs to be measured effectively. In another report containing a series of predictions about the rising importance of data and analytics, Gartner analysts suggest that although information arguably meets the formal criteria of a business asset, present-day accounting practices disallow organizations from capitalizing it. That is, the value of an organization's information generally cannot be found anywhere on the balance sheet.
"Even as we are in the midst of the information age, information simply is not valued by those in the valuation business," says Douglas Laney, vice president and analyst at Gartner. "However, we believe that over the next several years, those in the business of valuing corporate investments, including equity analysts, will be compelled to consider a company's wealth of information in properly valuing the company itself."
Gartner conducted a study which showed how companies demonstrating "information-savvy" behavior - such as hiring a chief data officer (CDO), forming data science teams and engaging in enterprise information governance - command market-to-book ratios well above the market average. Mr. Laney says: "Anyone properly valuing a business in today's increasingly digital world must make note of its data and analytics capabilities, including the volume, variety and quality of its information assets."
Equity analysts and institutional investors will consider only a company's technical data and analytics capabilities and how its business model provides a platform for capturing and leveraging information, not the actual value of its information assets, says Gartner. It also predicts that by 2019, 250,000 patent applications will be filed that include claims for algorithms, a tenfold increase from five years ago.
According to a worldwide search on Aulive, nearly 17,000 patents applied for in 2015 mentioned "algorithm" in the title or description, versus 570 in 2000. Including those mentioning "algorithm" anywhere in the document, there were more than 100,000 applications last year versus 28,000 five years ago. At this pace, and considering the rising interest in protecting algorithmic IP, by 2020 there could be nearly half a million patent applications mentioning "algorithm," and more than 25,000 patent applications for algorithms themselves.
According to the European Patent Office, there is no legal or conclusive definition for a software patent. The FFII goes so far as to say software patents should not exist under European law. However, algorithm patents can be granted in the US, the EU and many other countries. Most of them place limits on the patenting of inventions involving software, but there is no one legal definition of a software patent. For example, US patent law excludes "abstract ideas", and this has been used to refuse some patents involving software.
While not all algorithms can be patented, many can, even if the rules of application are not always straightforward, according to Gartner. Of the top 40 organizations patenting the most software algorithms the past five years, 33 are Chinese businesses and universities. The only western company in the top 10 is IBM at No. 10.
Whose data is it anyway?
Now that organizations are realizing the full potential of their information assets, some analysts warn that their customers might resent them and backlash, according to Capgemini. Some people might feel peeved off that someone else is profiting from ‘owning' their information. It really comes down to the question: whose data is it anyway?
It's a sensitive issue that is difficult to predict since the profitability of big data in the business world is still relatively in its infancy. Speaking on the matter, Jeff Hunter, vice president of Capgemini, says it really "depends on how the data is being used, repurposed, or resold. Companies aren't out to resell the data en masse. They want to drive toward derived results that better serve customers and themselves."
Mr. Hunter notes that customers are probably less concerned about aggregated data, but said there's a generational disconnect on the question of who owns data. He illustrates an interesting example of this: "Your perception of data is based on your comfort level. My wife would see it as disconcerting, while my teenage daughter would see it as convenient."
The most successful data companies, according to a report by Oracle and the MIT Technology Review, include Amazon, Google and Uber, who each treat data as an asset, able to be sold and monetized. The fact that these companies are able to profit on user data, drew Microsoft Research scientist Jaron Lanier to argue that users should receive "nanopayments" for data accumulated from them. Dutch technology pundit Jathan Sadowski has even suggested that big data collection is a "form of theft".
However, many of the products and services provided by large companies that rely on big data from users - such as Uber's surge pricing feature and Google's traffic predictions - depend largely on information from millions of users. Ultimately, one individual's contribution isn't worth all that much. In fact, if Facebook divided up all of its profits among its users, each user would only receive about $5 for 2016, according to analysts.