Key to Digital Innovator Success: Disrupting with Data

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Digital engagement, fueled by an agile approach to data, enables fearless experimentation and rapid, iterative software development.

The FAANGs were the first generation of digital disruptors. Today, most of us rely heavily on Facebook, Amazon, Netflix, and Google for information, entertainment, connection, shopping, and more. How did these companies become so successful and an indispensable part of our everyday lives? And what can the next generation of digital-native businesses learn from them?

The answer is digital engagement, fueled by an agile approach to data that enabled fearless experimentation and rapid, iterative software development.

Amazon CEO Jeff Bezos concurs. He stated that the company’s success “is a function of how many experiments we do per year, per month, per week, per day.” Bezos has also been quoted as saying, “If you decide that you’re going to do only the things you know are going to work, you’re going to leave a lot of opportunity on the table.” In short, companies need the ability to quickly conduct a large number of data-driven experiments in order to succeed in today’s market.

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Take Facebook’s famous “like button,” for example. In order to uncover what would truly engage users and keep them coming back, the engineer behind the feature conducted thousands of experiments before landing on this idea and continued to iterate to make it better. Today, the website’s like button and expanded emoji “reactions” have a powerful influence on what people read, click on, purchase, and pay attention to—all at a single glance.

Without the ability to experiment and iterate quickly, iconic features like this wouldn’t be possible. It’s these processes that give Amazon the power to influence people’s purchasing decisions, Netflix the ability to keep users watching, and so forth.

Although rapid iteration and experimentation are essential for digital innovation and disruption today, it is interesting to see how agile data stacks are making their way from software teams to IT teams and now to data teams. In the past, the most significant bottleneck to software development was IT; but with cloud and DevOps, that bottleneck has largely been addressed in modern companies, only to hit a new bottleneck in the data layer. Batch data systems and processes are stuck in a waterfall approach.

These systems are inflexible and rigid, making it hard to iterate throughout the cycle as the mountains of data grow. Just like IT went from waterfall to agile, with cloud stacks being the big enabler, the same is now happening in data, with modern real-time data stacks being the big enabler. Agile acknowledges that change is constant, and each step of the software development process should be informed by input from the people who will actually be using the product. This quick feedback loop allows development teams to be iterative and flexible so they can better meet customer needs. Unlike the rigid, step-by-step waterfall approach, modern software development’s rapid, iterative loop lets multiple teams work together and alongside customers to release software incrementally to ensure its efficacy.

FAANG giants were the first digital disruptors because they had the ability to build their own data infrastructure designed around developer flexibility. They accomplished this by employing massive data teams consisting of hundreds (or even thousands) of people. Needless to say, not all companies have the resources to hire an army of data engineers. As the new wave of digital disruptors emerges, their main challenge will be determining how to move to a modern real-time data stack. Agile data practices with modern real-time data stacks are giving new generation digital natives the ability to disrupt industries that, until recently, had long remained stagnant.

And it’s already happening. For example, vitamin company Ritual has used data to turn the health and vitamin industry upside down with its custom-formulated supplements designed to help fill common nutrient gaps in diets at different life stages. Combine this with its subscription-based delivery model, and it’s clear that the way people think about and purchase vitamins has changed for good. Similarly, Command Alkon is taking one of the most well-established industries—construction and heavy building materials—and using real-time analytics to respond to changing conditions across the chain, ensuring the timely delivery of materials to their destination.

Customer expectations have always been high, but with major companies setting an exceptional precedent for customer experience (CX), we can only anticipate expectations will grow further. Digital disruptors are keeping up with this by following companies like Amazon and Facebook’s lead: conducting experiments, prioritizing rapid iteration, and using real-time data and analytics to get customers what they need, faster.

Shruti Bhat

About Shruti Bhat

Shruti Bhat is Chief Product Officer and Senior Vice President of Marketing at Rockset. Prior to Rockset, she led Product Management for Oracle Cloud, where she had a focus on AI, IoT, and Blockchain, and was VP Marketing at Ravello Systems, where she drove the start-up's rapid growth from pre-launch to hundreds of customers and a successful acquisition. Prior to that, she was responsible for launching VMware's vSAN and has led engineering teams at HP and IBM.

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