A staggering 2.9 billion by a billion bytes of data are created every day, enough to fill 5.8 billion average-sized PC hard drives.1
This phenomenon has given rise to a new term – big data. Typically complex and unstructured, big data presents a major technological challenge for companies that capture, analyse and exploit the information. Big data offers a potentially rewarding field for investors who can predict which companies will benefit from it.
Big data has arisen because digitalisation has accelerated the growth in data across every organisation, industry and economy. Each day, posts are made on Facebook, tweets sent on Twitter and videos uploaded to YouTube. Networked sensors collect huge amounts of data from mobile phones, gas and electrical meters, aircraft engines, drilling platforms and atmospheric equipment. Satellites gather weather and geographical data and military intelligence. Data is created as by-products from everyday activities such as the transaction data collected by supermarket tills.
According to IDC, the world’s digital output soared from 180 exabytes in 2006 to about 1,800 exabytes in 2011. (One exabyte equals one billion gigabytes.) Data volume is expected to reach 35,000 exabytes by 2020, representing a 20-fold increase in the next 10 years. To understand how big data affects companies, it helps to look at three key characteristics.
Variety describes the number of data types. Interpreting and analysing different data types in conjunction with each other can create tremendous value. Facebook, for instance, stores vast information about its users: their sex, age, location, marital status, favourite books or films and even which brands they “like”. To help with marketing, companies can discover who “likes” their brand, the age group they fall under and their sex. Velocity refers to the useful time span of data because there is little point in storing data that is out of date.
Big boost to big techs
Big data is seen as a potential huge driver of returns for the next generation of multi-billion-dollar software companies. It represents the fastest-growing market for information systems globally. Analysts believe that the total addressable market is worth US$100 billion (A$102 billion).2
Companies such as General Electric, IBM, Microsoft, Oracle, SAP and Symantec have invested heavily in global data centres designed to interpret big data and they are scouting for the best talent. IBM, Microsoft, Oracle and SAP have spent more than US$15 billion acquiring software companies that specialise in business intelligence tools as they look for the best software developers, statisticians, quant analysts, econometricians and data analysts.
Large firms are in a good position to develop lucrative consultancy businesses based on their ability to analyse big data as the technological prowess these companies have is impressive. The data recorded by sensors located on aircraft engines, for instance, can be studied to improve fuel efficiency for an airline, or data analysis can benefit the oil and gas industry by helping to extend the lives of fields and the recovery of natural resources.
Big data is a boon to market-research firms. The internet has widened the ways to reach and market to an audience because every page viewed and every click made are recorded. Marketing teams are pouring through the huge amounts of data available from search and social media leaders such as Google and Facebook. But the sheer amount of data out there can pose a huge problem. The danger is that companies do not rise to the challenge, miss out on opportunities and lose their competitive edge.
Large online businesses such as Amazon.com already use the customer data to suggest other products. However, the set-up costs and necessary infrastructure are problematic for smaller companies. An alternative solution is to outsource the data analysis and targeted marketing to specialists.
Big prod to small techs
Although big companies are giants when it comes to big data, there is room for new entrants with innovative solutions. Popular open-source database tools such as Hadoop are readily accessible to start-ups.
Indeed, the threat of start-ups poses a challenge for large software companies trying to make inroads into this field – as a result, acquisitions by large technology companies have picked up and other small technology firms have seen their share price outperform even though they may not yet be acquisition targets. One example is Microgen, a small UK software company specialising in software that allows companies to run processes immediately that would have previously been done in overnight batches. Microgen software was tested recently at seven billion transactions per hour and is used by many leading banks, transport and logistics operators and digital media companies. For one media company, Microgen built a royalty-management system to track millions of songs, apps and other downloads every day.
Then there are those companies where data analysis is already the heart of their business model. Take Experian, for instance. It helps organisations manage credit risk and prevent fraud. On the consumer side, it helps people manage their credit profile and prevent identity theft. Experian uses its data and analytical tools to sell products to businesses from retailers to financial services in over 80 countries. It is now expanding in emerging markets such as Brazil; in 2006 it had no exposure to Brazil, yet now the company generates over US$1 billion in revenue there.
Retailer, manufacturing boost
Big data is useful for retailers because it can help them automate and optimise inventory levels. Large retailers such as Wal-Mart have already adopted big-data techniques to help streamline supply chains. Wal-Mart’s data warehouse is massive and includes some 2.5 petabytes (one quadrillion bytes) of information, largely from till receipts.
What has given Wal-Mart an edge is the way it pioneered the expansion of its electronic-data-interchange systems to connect suppliers. Suppliers can now view a link that shows when restocking is required rather than wait for an order from Wal-Mart. These vendor-managed-inventory techniques have been around since the 1980s. It’s just that Wal-Mart has deployed it on a massive scale.
Data mining has been embraced by supermarkets because it gives them the ability to set prices on customer preferences and buying behaviour. A recent innovation has been to leverage the data collected by loyalty card programs. UK supermarket chains such as Tesco and Sainsbury’s regularly use the histories on loyalty cards to tailor promotions to people via vouchers.
Other retailers such as those in fashion are making inroads into big data. Inditex, which owns the Spanish retail chain Zara and controls its supply chain, collects data from its till receipts to identify demand for certain garments. It means that if it identifies an emerging trend, it takes just weeks to develop a product and get it onto the shop floor, while six months is considered the industry average.
Since the start of the computer age, manufacturers have used data to help drive production quality and efficiency. Big data allows designers and manufacturers to share data quickly and cheaply and create simulations that test designs. The aerospace and car industries use big data for this purpose. Big data can help improve business management for it can help maximise cash flows.
Making big data available across an entire business has considerable benefits. It can encourage underperforming divisions, for example, to improve without management intervening. A common application is to rank sales targets by division or even individuals. Demand is growing for software that can deliver this variety of statistics and performance indicators. Big data can help the public sector too, from the military to the healthcare system.
The return potential for investors lies in identifying the beneficiaries of what seems set to become a multi-billion-dollar industry. The winners will come from today’s tech giants as well as smaller companies. Acquisitions are likely to support returns. In big data, there are big opportunities.
Financial information comes from Bloomberg unless stated otherwise.
References to specific securities should not be taken as recommendations.
1 IBM, “Bringing big data to the enterprise.” 2012. http://www-01.ibm.com/software/data/bigdata.
2 BofA Merrill Lynch. “Big Data II – New Themes, New Opportunities”. White paper. 20 March 2012.
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