By Shalini Raghavan and Josh Prismon
Consider the following:
- Over 12 years ago, Gartner coins the expression “Big Data.”
- Over 2 months, ago a notable venture blog declares that “Big data is dead.” – Venture Beat
- Also 2 months ago, the NY Times tries to uncover the etymology of “Big Data.” Some good sleuthing by the Times reveals the author of this expression to be John Mashey, Chief Scientist at SGI in the 1990s. In Mashey’s words, “I was using one label for a range of issues, and I wanted the simplest, shortest phrase to convey that the boundaries of computing keep advancing.”
So why has Big Data turned into big disappointment for so many people? Looking back, we see some systematic reasons that make it obvious that this disappointment is self-inflicted!
- All efforts on Big Data focused on data and infrastructure. Merely storing your data was not going to advance the boundaries. In fact, John Mashey warned about this. In 1998, he delivered a presentation titled “Big Data and the Next Wave of InfraStress Problems, Solutions and Opportunities.” He cautioned that, “Big Data is NOT technology for technology’s sake; IT’S WHAT YOU DO WITH IT, but if you don’t understand the trends, IT’S WHAT IT WILL DO TO YOU.”
- Often there is not a strategic view to data collection and management of the myriad sources that are available and important to organizations. A 2012 survey by the Economist Intelligence Unit, across different verticals and organizations, revealed a strong appetite for a data-driven approach in both strategy and day-to-day decision making. However, most organizations surveyed admitted to barriers that kept them from achieving the promise of Big Data. The reasons are numerous – aging or obsolete paradigms of data management, the continuance of siloes (human, data and machine), a lack of attention to data quality. Probably the worst barrier is the lack of a “data-driven culture.” This alone has led to significant dilution of the value proposition of Big Data – since there is neither recognition nor reward for driving change.
- Many organizations have not used analytics on Big Data to improve decisioning at scale. There appears to be a fallacious notion that decisioning solutions cannot perform analytics at this scale. Setting the expectation bar low has helped bring forth a bevy of analytic solutions that simplistically aggregate, slice and dice the data. Let’s use a food analogy to talk about the downsides. Being restricted to slicing and dicing only works when you have a few ingredients, and you know that you’re making, for instance, a salad where you can stop with slicing and dicing – when what you have chopped is ready to consume. How might this apply to data? Well, data challenges come in all shapes and forms – from the simple to the complex – and might have wide-ranging impacts on the results of your organization. Analytic solutions must be able to encompass and serve all these needs by reducing the burden for the organization. Active operational projects at NASA have already shown that it is possible to use petabytes of data to improve decisioning. Big Data technologies and analytics still seem rather esoteric because they are subject to too much hype, have not been implemented at a large scale and are still poorly understood.
One might argue that NASAs projects are carefully orchestrated, measured and controlled, and that there are in fact no learnings for us. Customers, you might say, act of their own free will. But this is the kind of thinking that is misleading and, worse still, is what keeps organizations from tapping into their data. There are many parallels and much that can be operationalized with an effective data and analytics strategy that is centered on specific goals.
So why is this worth thinking about? Customers are the greatest asset of your company. Everyday millions of your customers interact with your business in a variety of ways and in a manner of their choosing. Engaged and loyal customers are a vital part of the organizations’ success. Improving the customer experience is key to creating and maintaining loyalty. Customer experience powered by Big Data and analytics will lead to true differentiation.
If you care about this topic and would like to learn more, including approaches to support interactive dialogs with customers, develop and support strategies, and overcome operational barriers, please join us for our FICO World session titled “Big Data & Analytics: Keys to a Stronger Customer Experience.”