Doug Logan

Every Brand Is Now A Data Company: The Implications of a Data-Driven Market

Business trends come and go, but one recent concept seems to have real staying power: the idea that every company is a data company. It's the natural follow-up to the previous (and still relevant) notion that every company is, to some extent, a tech company.

The new take on this familiar concept reflects the huge influence big data now has on every corner of the business world. No sector is immune, even when it doesn't seem as if it should be closely aligned with advanced tech. Across businesses of all sizes and from all industries, data is vital to engaging with and appealing to the modern consumer.

Already in 2011, experts at the McKinsey Global Institute anticipated that big data would drive the economy in years to come. In an influential report on big data as the "new frontier," researchers explained, "The use of big data will become a key basis of competition and growth for individual firms. From the standpoint of competitiveness and the potential capture of value, all companies need to take big data seriously."

This prediction has clearly come to fruition. In recent years, businesses in all sectors have adopted a data-driven mentality. We've outlined several examples of this phenomenon below:


As one of the earliest adopters of the tech-forward approach, Tesla made waves years ago with its emphasis on big data. The luxury automaker now relies on every human-vehicle interaction to produce data points. Every time Tesla drivers move their steering wheels or put on the brakes, they provide insights for the company's artificial intelligence and machine learning initiatives.

Already, Tesla has harnessed its driver-generated data to form an insurance company, which draws on individual vehicle data to deliver a personalized pricing model. The holy grail of Tesla's big data initiative will be the eventual release of an autonomous vehicle — a huge undertaking that, as IEEE Spectrum points out, depends on a "deluge of data."


Representing another side of the transportation industry, Uber has demonstrated what happens when a data-driven model is applied to what might otherwise function as a taxi service. The company has long relied on a wealth of data to connect drivers and passengers — and to set appropriate fares based on supply and demand. Data also plays into Uber's luxury offerings, such as UberPremium and UberBlack, which bring high-end vehicles, professional drivers, and upgraded service to the mix.

Across this spectrum of offerings, data is strategically gathered, stored, and analyzed to reveal where bottlenecks exist and which services should or should not be offered. Data has also proven hugely influential in Uber's popular food delivery service Uber Eats, which actually generated more revenue than the original ride-hailing service as of 2021

Data visualization rests at the heart of Uber's success. The company formed a targeted data visualization team early on, relying on visual exploratory tools to make the most of its datasets. Meanwhile, an internal ML (machine learning) as-a-service platform allows Uber to build and deploy machine learning systems to scale, ensuring that the company can continue to effectively manage its data flood.


In the fashion world, few businesses capture the modern data-driven mentality better than Nike. This iconic brand has long been at the forefront of all things marketing, and this is once again about to play out as it expands its footprint in the realm of big data.

Nike's emphasis on data is perhaps most clearly evident in the background of the current CEO John Donahoe. While Donahoe has ample experience in the business world, his tech acumen is undeniable. Notorious for his technological expertise, Donohue represents a new era in the sportswear industry.

Business analyst Darren Rovell captures the emerging philosophy at Nike by referring to the brand as "a technology company that happens to sell shoes and apparel." The company increasingly relies on direct-to-consumer (DTC) sales, which have grown exponentially with help from its Consumer Direct Acceleration strategy.

Even before Donahoe took the helm, it was clear that Nike intended to use big data to shift to a DTC model. This intention was signaled, in part, with the acquisition of the data analytics company Zodiac in 2018, followed by the predictive analytics company Celect in 2019. Later, data integration platform Datalogue joined the fray.

The goal of all these acquisitions? To more effectively gather and manage data, which can then be used to create a personalized experience. As a result, direct consumers can expect not only rapid delivery, but also, customization that goes beyond aesthetics alone. Nike's DTC approach closely echoes that of luxury designers and may signal Nike's intention to position itself as an upscale brand moving forward.


These days, Disney's trademark magic is largely driven by data analytics. In recent years, big data has prompted some of the most impactful decisions for the company's streaming service, its beloved theme parks, and even its larger-than-life Broadway shows. The transformative nature of big data was already clear a full decade ago, when Disney used dynamic pricing models to produce record profits for its stage version of The Lion King.

At Disney's parks, big data has been a driving force behind some of the most exciting and immersive new attractions. Disney's Director of Engineering Technology Michael Tschanz tells HPE that the ultimate goal is to help guests "step into the films and be immersed with the characters and storylines, just like if we were part of the film itself—none of which could happen without so much of the technology" that's available today.

Edge computing will be a core part of Disney's strategy moving forward. As devices are able to process data near networks' "edges," it's possible to connect high volumes to a data stream and maintain a level of agility that once seemed impossible. Tschanz explains that edge computing promotes "data aggregation and management directly from our attractions systems. Keeping this data at the edge reduces the cycle time...which means faster results and a more efficiently managed attraction."

What’s Next in the Data-Driven Market?

Big data has come a long way in a few short years, but the data revolution is just beginning. McKinsey — again, a forward-thinking source of big data optimism — anticipates that data-driven problem-solving methods still in their infancy will become far more sophisticated in the next few years.

In the report The Data-Driven Enterprise of 2025, experts at McKinsey remind us that, while predictive systems drive many business functions, they're still often used sporadically. Problems identified through AI are still frequently solved via traditional business methods. Soon, however, employees at all levels will feel empowered to integrate data into their everyday tasks, replacing time-consuming road maps with innovative techniques that are more accurate and efficient.

Data as a Product
One of the most influential changes to expect in the next few years? The upcoming treatment of data as a product. Currently, there is no clearly defined ownership of data, which may be situated across sprawling environments that are prone to silos. Forbes Council Member Sanjeev Mohan5 anticipates that business leaders will soon regard data "as a product that must be managed with users and their desired outcomes in mind."

According to Mohan, the concept of the data product is akin to a self-contained "container," which can be monetized or used to solve specific business problems. This shift may seem subtle, but it helps to address data's full life cycle. Experts at Thoughtworks add that data as a product will form one of the "foundational pillars to move toward growing an innovation culture where data is readily and safely available for experimentation."

A World Without Cookies
For years, digital marketing initiatives depended on cookies to collect consumer data. The cookie era is coming to an end, however. These small files simply don't abide by today's expectations regarding consumer privacy. In an effort to promote a "privacy-first web," Google intends to replace cookies with "privacy-preserving APIs which prevent individual tracking while still delivering results for advertisers and publishers."

As cookies disappear, data-driven businesses will need to adopt more nuanced solutions to continue gaining key insights and ultimately, producing personalized consumer experiences. While the removal of cookies will spark some initial difficulties, the long-term result could be a shift towards developing stronger relationships with clients and customers.

Invoca CEO Gregg Johnson refers to the imminent end of cookies as a "wake-up call for marketers to break their third-party data addictions and instead turn to review the data strategies within their organizations." Many of the companies we highlighted above are already doing this and have reaped the rewards.

The takeover of big data is just beginning and the implications will be huge for businesses and consumers alike. A nuanced approach can provide the best of both worlds: a personalized, enjoyable experience for the customer and stronger profits for the data-driven businesses of tomorrow.

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