How to invest in the companies turning Big Data into big profits

Nike: a Big Data refinery

(Image credit: © Nike Inc)

published 11 December 2020

As a species, human beings have been producing data for millennia. Yet if you add up all of the data created over that period – from the age of papyrus scrolls to today’s social-media age – almost all of it has been generated in just the last few years. This recent, explosive growth in information reflects the rapid expansion of internet access. Some 60% of the world’s population is now online and every click, search, swipe and stream on computers, mobile phones or other devices is noted somewhere. And the ability to nose around in all this data is incredibly valuable.

Businesses from retailers and advertisers to banks and insurers all stand to profit significantly if they can refine this real-time knowledge of what billions of people are up to or interested in, to fuel growth. It’s not for nothing that they call this “Big Data” the new oil – and right now the wells are gushing. Only last week, S&P Global, an $80bn US financial data provider, offered $44bn for IHS Markit, another New York-headquartered global business data group, which started life in 2003 in an outbuilding in a garden at a house in St Albans in Hertfordshire. These are large numbers, and even those who might once have dismissed seemingly arcane data as boring or worthless are being forced to take notice: we are now in the age of Big Data.

The oil analogy is generally credited to Clive Humby, a British mathematician who spent his career analysing consumer behaviour and was the brains behind the Tesco Clubcard customer loyalty programme launched in the mid-1990s. The Clubcards record all customer spending data – millions of shoppers, buying many more millions of items daily and weekly – with all of this information coming through in real time. That gives Tesco’s head office a very detailed insight into how individual customers shop, their price sensitivities, their likes and dislikes, which promotions they’re drawn to – the data can be analysed any which way imaginable. In turn, Tesco can use it to win commercial advantage: cutting prices here or dropping products there, say. As Tesco’s chairman and former chief executive Ian MacLaurin said when the Clubcard was launched, according to The Independent, “What scares me about this is that you know more about my customers after three months than I know after 30 years”.

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For Humby, who now has an OBE for services to data and UK business, data for any business – not just Tesco – is a raw material. Its economic worth is what can be derived from it, just as oil is changed into “gas, plastic, chemicals, etc., to create a valuable entity that drives profitable activity”. The data mined at Tesco was said to have broken many long-standing assumptions and beliefs about how its customers shopped, prompting new thinking that transformed its fortunes. It wasn’t the only one – air-miles programmes and other shopping loyalty schemes such as Nectar have all influenced sales and marketing.

Since then, with the advent of the internet, significantly more data reserves have been discovered and greater computer-processing power means analysts can drill more deeply. Go back 25 years and with Clubcard data you could analyse a superstore or a group of them. But now that analysis can stretch to entire populations, engaging in a huge and ever-growing range of activities far beyond the weekly shop.

Just take a typical 60 seconds online in 2020. In the time it takes to read a few paragraphs here, internet consumers spend $1m; Amazon ships 6,659 packages; users of the WhatsApp messenger service send 41.7 million texts; members of the Linkedin networking site apply for 69,444 jobs; and Netflix subscribers stream a total of 404,444 hours of video. Activity produces data and there are no signs that this exponential growth in volume is slowing. If anything, data generation will accelerate even further. The “Internet of Things (IoT)” promises breakthroughs in hyperconnectivity as devices including cars, household appliances, health-monitoring equipment and security and tracking sensors are digitally hooked-up and communicate with one another, helped by the advent of the faster 5G mobile cellular network with its greater capacity.

So how will this data be used? We’re already familiar with our online data being used by Amazon to offer relevant buying suggestions, or by Google to display advertisements based on past browser searches. But the web is widening. Perhaps in future, your mobile phone will be warned by your kitchen that you’re out of dog food when you’re within 200 yards of a shop that stocks your pet’s favoured brand. Or private hospitals will remotely diagnose and prescribe treatments for health problems. And road safety could improve hugely if cars forewarned each other directly of every manoeuvre. The possibilities are endless and many of the ways in which we will rely on data have yet to occur to us. Growing data use should bring great social and economic benefits as companies get better at reading the marketplace around them, meaning cheaper, quicker, more-tailored products and services for consumers.

However, any business aiming to profit from this needs not only to have access to big data, but also the computing power to store and analyse it. This is where the “cloud” comes in. In effect, the cloud stores all that data across the internet’s huge capacity, where it can be processed by many computers simultaneously. The cloud forms the third component, alongside Big Data and the IoT, of the trinity that underpins today’s investment gains in technology and related stocks. Investors see the deep structural changes at play across entire industries. The INDXX Artificial Intelligence & Big Data index has nearly trebled over the last five years, with annualised returns of almost 25% since 2018.

Investment bank Morgan Stanley calls this a “data-era productivity boom”. We’re at the early stages of a technology-driven, decade-long investment cycle fuelled by data and digitisation. We may have become familiar with chief technology or chief brand officers, but the one that every company now needs leading from the front is the chief data officer. So it makes sense for investors to focus not only on the data miners but also on more established firms that can successfully embrace these trends. And those business managers who haven’t yet begun to get a grip on the data revolution should be looking to companies such as Nike. Why has the share price of a trainers-to-sportswear group enjoyed gains of more than 17% a year since 2014? And why are those shares currently up nearly 40% in a year that opened with a US-China trade war and saw a global pandemic shut down most sport?

The answer is that Nike has been selling far more of its products online, cutting out the middlemen. And data is the goal. By getting closer to its customers, it can pick up, then analyse vast amounts of information about who they are, what they want, and when best to sell it to them. Through Nike’s apps it can offer exactly the right products while rationing their supply to ensure the maximum number of full-price sales based on past shopping patterns. The days of shipping stock to third-party high-street retailers, in the hope that it won’t sit around unsold for years or be sold off in brand-damaging sales, are already ending. “Fingers crossed” doesn’t cut it as a sales strategy anymore.

Those who can’t see these changes and have Nike marked down as nothing more than an overvalued sportswear group have missed out on strong share-price gains. But those who were early to identify Nike as a data technology company have been strongly rewarded (we featured it in MoneyWeek at nearly half the current share price in September 2018). Nike’s CEO Eric Sprunk captured the Big Data theme well when he said: “We must be insight-driven, data-optimised and hyper-focused on consumer behaviour.”

Nike isn’t unique. Drinks groups such as Diageo tell retailers which products to take based on databases showing what works in other outlets. Coffee chain Starbucks works its customer data hard, while cosmetics groups from Estée Lauder to Ulta Beauty analyse repeat orders, geographic location and cross-selling patterns. Fund management groups are buying in Big Data to analyse consumer and economic trends to find winning stocks. Even Warren Buffett has bought into the trend: Berkshire Hathaway recently bought a stake in Snowflake, a recently listed data storage and analysis group. To buy into Big Data is to back big innovation. Refined data will flow across industries, transforming businesses and rewarding shareholders. It is a global mega-trend you can’t ignore – for thoughts on how to buy in, see the box below.

Above, we’ve mentioned some established businesses that can profit from Big Data and are worth buying. Consumer data providers such as Experian (LSE: EXPN), for example, used for decisions on credit cards and mortgages, could benefit from the consolidation in the financial data industry. It’s also worth looking at the big cloud players (who have the key role of storing all this data) such as Microsoft (Nasdaq: MSFT) and Amazon (Nasdaq: AMZN).

Of the data miners themselves, Splunk (Nasdaq: SPLK) is a front-runner. It is growing rapidly, offers a diverse range of services, and is expected to turn a profit in 2022. Another is Palantir Technologies (NYSE: PLTR). It listed in September but is no newbie – it was established 17 years ago and is expected to grow fast. It has been working with the US government on military projects as well as some Covid-19 tracking. Finally, there’s Snowflake (NYSE: SNOW), the stock held by Buffett (mentioned above). It’s another cloud-based operator working with data and recently enjoyed a strong market debut. It has a strongly scalable platform, which gives it the capacity to meet ever more complex data needs, putting it in a positive position.

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Stephen Connolly is the managing director of consultancy Plain Money. He has worked in investment banking and asset management for over 30 years and writes on business and finance topics.