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Information overload?

Data is a valuable commodity, but also comes with major risks
Information overload?
  • Smart data analysis can help lead innovation
  • But monetising personal data is difficult terrain to navigate 

Your smartphone is a tiny, starving monster that feeds off the data that you pour into it, and sucks at your soul until you turn into a brainless zombie. Or so goes the argument of The Social Dilemma, one of Netflix’s (US:NFLX) hits of 2020. The documentary, which attracted 38m viewers within four weeks of its release, shone a deeply unflattering spotlight on the ways that the gods of Silicon Valley harvest and commodify our personal information. 

While the film is an entertaining watch, and makes salient points about the impact of social media on mental health, the documentary does not reveal anything new about the nature of advertisers. The likes of Facebook (US:FB) and Google parent Alphabet (US:GOOGL) are pioneers in cutting-edge technology – but they both make most of their revenues from ad sales. And like advertisers before them, they work to make sure that they engage their audiences. The industry has always tried to collate the most relevant information they have about their viewer or readership and try to use it to sell products en masse. 

Thanks to the rapid adoption of smart devices (which long precedes the so-called “digital transformation” of 2020), there is simply more available information about us. In fact, we regularly and willingly give it up to hundreds of advertisers every time we ‘Accept cookies’ when we visit a website for the first time.

These stack up into enormous banks: data sets that are so big that a regular computer would struggle to process them. They are also brimming with opportunity. Data science lies at the heart of modern product innovation, market research and personalisation. Investors who approach company analysis with an eye on its capacity to collect and mobilise information will be able to spot the long-term winners. Getting to grips with Big Data and all its related sciences is no mean feat, but this tour of its sprawling landscape explains why companies with a data-driven strategy often outperform their competitors. 

 

Big Data: the digital Wild West

In the early 2000s, commercial laptops came with around 40GB of data. Now, even the most basic smartphone has around 30GB of storage, while the newest iPhone can have more than 500GB. 

In 2018, the International Data Corporation predicted the world’s data would grow to 175 zettabytes in 2025. That is a dizzyingly difficult number to comprehend º but if you were to store 175 zettabytes on DVDs, the stack of discs would be long enough to circle Earth 222 times. If someone attempted to download 175 zettabytes at the average current internet connection speed in the US, it would take around 1.8bn years. 

 

But it is not just volumes of personal data that have exploded. Industry data too continues to grow. This is in part a natural historical process, as more companies digitise and log customer, product and research data. And data services is an attractive market to operate in: S&P Global (US:SPGI), which resides over indices, as well as financial markets and Platts energy data, boasts a gross margin that has averaged 67.9 per cent over the past five years. Its all-stock acquisition of IHS Markit, itself the result of the IHS and Markit combination in 2016, will further strengthen its dominance in the information services sector, where subscription revenues are sticky and switching costs are typically astronomical. 

Any company worth its salt will know the sector that it operates in back to front. While a few decades ago this would have meant a few regular market research surveys, this now means accessing a whole universe of information that is constantly growing. 

But just because it exists, does not mean that it is valuable. Its worth lies in actionable analysis. This is evidenced time and again by the fact that companies with a data-first strategy consistently outperform their less well-informed peers. 

 

The opportunities and pitfalls in personal data 

Unsurprisingly, big tech companies in California together preside over some of the most extensive banks of personal information in the world. Your government may record your date of birth, your address and your income. But the state, unlike Google, would not be able to draw up an accurate picture of your spending habits, your interests and your political beliefs according to your search history. It is the analysis of this colossal store of information that makes Google the leader in developing artificial intelligence technology. 

Apple (US:AAPL) insists that it prioritises its customer privacy above all else: in fact, last year it announced that it planned to give its users the ability to opt-out of their personal data being shared for targeted, personalised advertising. This spurred a very public spat with Facebook, which said that the move would slash its ad network revenues by half. Apple told the BBC that it was “standing up” for its users. Facebook said that it was “speaking up for small businesses”. 

But Facebook’s huge treasure trove of personal data is the not-so secret sauce to its unmatched advertising product. The company’s ability to reach a specific set of individuals gives its customers high quality leads, builds brand awareness and ultimately helps to close sales, while slimming down wasted ads on viewers who would be unlikely customers. This data-driven approach to advertising has meant that Facebook has left traditional players like IPG (US:IPG) and WPP (WPP) in the dust. 

This commodification of personal data, in what Professor Shoshana Zuboff coins as ‘surveillance capitalism’, has started to ring alarm bells. While the American big tech companies do not share the data that they collect with state powers, it appears that it is not without precedent elsewhere. The Wall Street Journal reported this month that Chinese regulators are pushing Jack Ma, the owner of Alibaba (HK:9988), to cave on something that he has previously resisted: share customer credit data that has been collected by his financial technology giant, Ant Group.

Mr Ma, who has not made a public appearance since October, does not have much wiggle room given that his fintech business is at the mercy of the Chinese government, which called off what would have been the biggest IPO ever just a few days before. Ant Group’s app, Alipay, is used by more than a billion people and has information about consumers’ spending habits, borrowing behaviours and loan payment histories. 

This has enabled it to reportedly originate loans to half a billion people, with around 100 commercial banks to supply the majority of the funding. True, in China looser privacy laws mean that consumer data can be mined more effectively. But there are players in the Western world that sit on similar sizes of data banks: take Visa (US:V) or Mastercard (US:MA). Their dominance in the payments infrastructure sector, combined with their near unparalleled comprehensive data-set of consumer behaviour, opens up a wealth of opportunity for innovation in the likes of credit, banking and other consumer services in fintech. It is perhaps not surprising then that Paypal (US:PYPL) is listed on Glassdoor’s top 10 companies hiring data scientists. 

The ‘privacy-first’ option at Apple does not come cheap; its iPhones and services are more pricey than their counterparts at Google and Amazon (US:AMZN). But this seems to be the future that data economies are headed towards: “premium players will wrap themselves in the blue flag of privacy and collect a nice margin for the courtesy of not exploiting their customers’ data,” theorises Professor Scott Galloway in his book Post Corona. 

Data analytics is not an American specialism. It was no coincidence that market researcher YouGov (YOU) correctly predicted a Tory majority in the last general election, as well as publishing several surveys that pointed towards the Leave vote in the Brexit referendum almost five years ago - an outcome that came as a shock to both the media and the markets. Its data-first approach to polling has more than tripled its market value in the past three years alone. Here too the likes of Gartner (US:IT) , Forrester Research (US:FORR) and Nielsen have thrived on their data analytics services. 

Ripe for data disruption

The healthcare industry is infamous for its vast oceans of unstructured, sensitive data. This varies from electronic medical records to billing and care management. But with the rise of health wearable devices by Garmin (US:GRMN) and Apple, some of these areas have enormous scope for growth. Analysis of heartbeat, sleep and movement data could help to identify health risks and recommend prevention plans, as well as deliver more precise prescriptions. 

But the world of industry data is much safer territory, where there are fewer privacy pitfalls. And here too companies which are data-savvy enjoy an edge over their less digitally-literate peers. Take for example the oil and gas sector, which arguably has a reputation for being inflexible to change. But the industry is riddled with inefficiencies: an average offshore oil and gas company experiences around 27 days of unplanned downtime a year, which can lead to annual losses of $38m to upwards of $88m, according to research from IBM (US:IBM). 

Predictive analytics are now commonplace: but the use of AI can monitor and predict equipment failures, as well as highlight the financial impact of unprepared loss of production capacity. ExxonMobil (US:XON) for example cut its production planning time from nine months to seven, and dropped its data prep time by 40 per cent.  

 

 

 

The data monopolies 

Data monopolies formed a cornerstone of the US antitrust investigations into big tech companies last year. A Congressional hearing in the summer prodded at Jeff Bezos, questioning him on reports that Amazon used third-party retailer data to identify which products were popular on its platform, and then launched its own competing offers. His response: “What I can tell you is we have a policy against using seller-specific data to aid our private-label business...But I can’t guarantee you that policy has never been violated.”

But while the sizes of big tech’s huge troves of information are unparalleled, it is wrong to assume that they are the only ones collecting banks of consumer data. Today, individuals can no more easily avoid leaving a data trail than they can the carbon dioxide they breathe out.

In this sense, data is an infinite resource that can fuel growth for companies. Not all of it is interesting - companies must be able to analyse the information that they harvest in an actionable way if they want to get an edge over their competitors. But when they do, the results are in a different league: and the market knows it. Templeton Emerging Markets Investment Trust (TEM), which holds Baidu (US:BIDU), Alibaba and Tencent (HK:0700), (the data-savvy Chinese tech giants otherwise known as the BAT group), achieved a net asset value return of 31.2 per cent in the six months ended in September last year. A portfolio with data-driven strategies at its core makes for a smarter one. 

Personal data is a tricky business to be in, and privacy laws are rushing to keep up with the sector - as well as regulators. In a market where growth can be difficult to envision, companies that mobilise their data assets will be the ones that will innovate the smartest.