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The Disruptive Strategist - The Competitive Advantage Of Big Data

Harnessing the power of data is critical for companies to maintain a competitive edge in a technological age. GAM Investments’ David Goodman looks closer at some of the companies that are leveraging its power across a diverse range of industries.

07 February 2022

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While the analogy “data is the new oil” may not be new, it still holds true; data powers entire enterprises and provides good value but in our view, like untreated oil, it is almost worthless if not handled in the right way. According to a July 2020 survey of 1,500 worldwide business leaders commissioned by Seagate Technology, about two thirds of data available to enterprises remains unlevered. “The report and the survey make clear that winning businesses must have strong mass data operations,” said Seagate CEO, Dave Mosley. “The value that a company derives from data directly affects its success.”

Companies therefore must adopt a data strategy or die. We are on the cusp of a new technological age where, regardless of a company’s industry or size, the key drivers for long-term outcomes are data and how that data is used, with the latter critical for competitive advantage. The GAM disruptive growth team refers to this as Digital 4.0.

The evolution of competitive advantages

If we look back over the last three centuries, we can broadly identify four major industry technological changes that drove clear competitive advantages for enterprise.

Mass production powered by steam was the first major technological change and brought huge production efficiencies from 1780 onwards. Big business took off during the late eighteenth century when a new source of power, namely coal-driven steam engines, enabled production under one roof – giving rise to large factories and the efficient mass production of standardised goods. Visionary manufacturers, such as steel magnate Andrew Carnegie, took production efficiencies a step further; by making a single company to oversee the entire production chain from raw supplies to distribution, they were able to undercut the competition while reaping the benefits.

It was during the nineteenth century that big businesses first realised the benefits to be gained by utilising their innate size and reach, beckoning in an era of mass production assembly lines, giving companies the advantage of economies of scale. For example, John D. Rockefeller’s Standard Oil company possessed enough market power as a result of its size, efficiency and economies of scale to obtain significant railway rebates or discounts – enabling the company to sell oil cheaper than their competitors could produce it.

Fast forwarding to the 21st century, thanks to automated production using electronics, computers and connectivity, companies from 2007 onwards benefitted from network effects. A network effect occurs when a product or service becomes more valuable as more people use it. The larger the network, the more value it has and the harder it is to replicate. According to a study by NFX1, network effects are responsible for 70% of value generation in the tech industry stating, “…companies that leverage network effects have an asymmetric upside. They punch above their weight. They are the Davids that beat the Goliaths, and then become the Goliaths.” The competitive advantages of these network effects have driven extraordinary value creation over the last two decades, as platform businesses have scaled.

2015 saw companies begin to benefit from intelligent production incorporated with Internet of Things (IoT), cloud technology and big data. The benefits of becoming a data-driven company are significant. The more data a business collects, the better the products and services become, which in turn attracts new customers and strengthens relationships with existing ones. Data is becoming the key enabler on all fronts: for developing future products and innovations; for anticipating and influencing what customers will desire and for pivoting to new business prospects.

The most effective data models are likely to be generated by companies with the best data in what is best described as a virtuous circle; customers will flock to businesses providing services or products that meet their needs, increasing the company’s data collection and ability to improve their product or service, which in turn attracts more customers, providing more data to improve the customer experience… and so it goes on. This flywheel effect, where the robustness and performance of a system improves exponentially over time, forms a competitive moat around the business that becomes more impenetrable as the organisation grows.

A diverse range of industries

Companies can leverage data across a diverse range of industries. Within the business to consumer industry, Google is a prime example. The more people search on Google, the more data it supplies, allowing Google to constantly refine and improve its fundamental performance, as well as tailor the user experience, in our view. For example, Waze the mapping app, is now a Google subsidiary and is essentially a contributing database – the more people use it in real time, the better the mapping experience, and so the more people use it, creating a data flywheel.

Data also has applications within the agricultural industry, which routinely uses sophisticated data collection technologies, eg temperature and moisture sensors, aerial images and GPS technology – all of which provides a precision that is making the sector more beneficial, efficient, safer and environmentally friendly. For example, leading agricultural machinery manufacturer John Deer is leveraging more than 10 years’ worth of data collection to enable their latest machines to sense and act in real time to fight weeds and improve crop yield.

Within construction, agriculture and transportation, leading the digital transformation is Trimble, whose hardware and software solutions generate large amounts of data – either through the millions of sensors installed on trucks, tractors and construction machinery, or the tens of millions of users of its Building Information Modelling software.

Trimble’s growth will be driven by moving to online platforms: ‘Trimble Connect’, its construction management platform, enables project data to be shared across various stakeholders, unlocking the real value of data throughout the construction lifecycle, while its ‘Farmer Core’ platform uses data to integrate and connects all aspects of a farming operation, making it easier to generate and share insights.

For financial exchanges, when more people go to exchanges to trade, the exchanges can gather more data and sell it to traders. Indeed, exchanges can monetise this trading data directly by repackaging and selling them to investors and distributors. This flywheel creates a strong moat for the largest exchanges.

Data is used within smart cities and communities, for example Johnson Controls International (JCI), a global technology and industrial business, creates intelligent buildings, efficient energy solutions and integrated infrastructure that delivers smart cities and communities. Its OpenBlue digital platform is an all-in-one system that allows building operators to analyse sustainability, health, water and wellness indicators, while lowering energy, and carbon emissions. Over four million customers are being leveraged as a key data source and as they collect data, JCI are using digital mapping, data tagging and AI engines to help model and optimise building performance.

Finally, data has the potential to vastly improve the healthcare industry. Intuitive Surgical has pioneered the use of robotics to assist in minimally invasive surgical procedures with its DaVinci machine. Over time, doctors have experimented with novel ways to use the machine to enhance outcomes, providing Intuitive Surgical with real-world data to improve its machine. This performance will attract more surgeons, who in turn collect more data, further improving operations and widening the competitive moat.

Important legal information
The information in this document is given for information purposes only and does not qualify as investment advice. Opinions and assessments contained in this document may change and reflect the point of view of GAM in the current economic environment. No liability shall be accepted for the accuracy and completeness of the information. Past performance is not a reliable indicator of future results or current or future trends. The mentioned financial instruments are provided for illustrative purposes only and shall not be considered as a direct offering, investment recommendation or investment advice. The securities listed were selected from the universe of securities covered by the portfolio managers to assist the reader in better understanding the themes presented and are not necessarily held by any portfolio or represent any recommendations by the portfolio managers. There is no guarantee that forecasts will be realised.

David Goodman

Investment Manager
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