The following is adapted from Wikibon’s forthcoming Data Economy Manifesto.
As we at Wikibon have documented, the Big Data market is growing at a considerable pace. Vendors selling Big Data technology products and services realized over $11.5 billion in revenue in 2012, a 59% increase from 2011. By 2017, Big Data vendor revenue will hit close to $50 billion, according to our models.
But that’s only part of the Big Data story. While $50 billion is nothing to sneeze at, we fundamentally believe that Big Data practitioners will create significantly more value than the vendor community over the long-term. Enterprises across vertical markets, from oil & gas and financial services to healthcare and consumer products, now have the tools at their disposal to make innovative use of data to drive high-value business outcomes.
The innovative use of data is already underway, the result of which we are calling the Data Economy. This innovation is and will continue to manifest itself in a number of ways. In some cases, enterprises are leveraging the flexibility made possible by new data processing and analysis technologies to improve existing business processes, resulting in higher worker productivity and more efficient operations. In other cases, enterprises are fundamentally reinventing themselves and entire markets by creating new data-driven business models in which the analysis and dissemination of data is itself the product.
There are many other ways innovative enterprises are using data to disrupt long-established markets, and countless new methods will be developed in the coming years. The technologies that support this innovation and disruption are obviously critical to the Data Economy. But the majority of net-new value created by the Data Economy will come from practitioners. who create value for themselves, for their customers, and for society at large.
A great example of the type of innovation that will drive the Data Economy is already happening at L2C. L2C is an Atlanta-based company that is disrupting the financial services business by taking a new approach to an old problem: assessing credit risk. The company’s platform calculates credit risk based on analysis of a number of non-traditional data sources, allowing individuals with little or no credit history to potentially qualify for mortgages and other types of loans. This could drive significant net-new economic activity, including new home sales, new home construction and other related services, that wouldn’t otherwise occur.
A note of caution is warranted, however. Innovation and disruption is never an easy or linear process. There will be many starts and stops, and more than a handful of enterprises will fail. We are already witnessing struggles by early adopters, nearly half of who have not achieved the level of value they anticipated at the start of Big Data projects. Those who succeed in the Data Economy will be the enterprises that learn from the struggles of these early adopters to overcome challenges, both technological and not.
The Data Economy is in the early stages, but progress is likely to be rapid if choppy. Within a decade, virtually all enterprises will be in the data business in one form or another. The companies that emerge at the top of the value food chain in 2020 will be those that invest in the people, processes and technology to enable data-driven innovation today. Wikibon, SiliconANGLE and theCUBE will be here documenting the Data Economy each step of the way.