Big Data and Business Innovation
Originally published March 25, 2013
Innovation has always been the spirit of our country and has been the key to success for a number of decades. If we were to turn through the pages of history, we would see there have been tipping points across time leading to innovations in every field that touches the human life, making the world a better place. A closer examination of any innovation reveals that there has been a lot of research and development using a large volume of data, based on which we have arrived at the solution. Many of the innovations – beginning with electricity, radio and wireless, automobiles and, more recently, the Internet and mobile devices – have been transformative both professionally and in our personal lives, and provided significant business benefits.
Long Tail – The long tail is a term coined by Chris Anderson, where he explains how businesses started experiencing a longer and sustained tail of revenue and growth when they were able to market to a larger list of customers or prospects with niche products and services at competitive price points, providing better revenue. Another great example of long-tail involves fund-raising efforts and the use of social media in presidential elections in the U.S. in both in 2008 and 2012 by President Obama’s campaign.While these trends and their associated models of engaging in business are becoming clear, we have two significant problems that need to be understood:
To understand this, let us look at the history of innovation. We have been delivering innovations since the beginning of time; however, until we discovered electronics and deployed the first generation of computers, the innovations were happening at a relatively slow pace. The ability to compute started speeding the innovation across industry verticals at a startling pace. However, the volume of data required for innovating constantly challenged us, as most of the data was not inside the computing environment in a structured format.
This problem was expensive to solve until recently. There are now technologies to process large volumes of data on commodity platforms for a fraction of the cost compared to the original costs. Platforms designed and built for handling scalability problems for search engines and social media platforms now provide the computing and storage platform for creating the enterprise compute and processing platform for large and multi-format, multi-structured datasets. The extensibility of this platform into the enterprise data repository is the “game changer” for many enterprises. Now you can access all the data needed for making informed business decisions, and this creates fertile ground for innovation of new business models and identification of “blue ocean” opportunities within the enterprise.
The availability of data provides the empowerment to start creating business scenarios and replay the outcomes using the data and the underlying infrastructure. Multiple scenarios called as experiments will provide outcomes; and by creating the near perfect experiment, you can predict the closest outcome to what your business expects. This experiment will allow you to create the right segmentation strategy for your customer, the right market for your product or the right cross-sell strategy for your call center. The biggest transformation that can be brought to bear is the overall approach of the business to its prospects or customers. Instead of asking the “lifetime value of the customer” or “the profitability segment of the prospect,” the question has shifted to “What is the value of me (the business) to the customer or prospect.” This type of introspection has provided the business with opportunities to adapt to different types of customers, offer personalized levels of marketing, and services and has directly increased the revenue from such an engagement.
There is a lot of complexity in this process that definitely is not trivial. However, if the business wants to increase its profitability and remain in business, they are forced to transform their thinking and behavior. This can be implemented in the most effective manner with the right set of insights and metrics, which can be provided by using big data platforms, all the data needed for such purposes, a collaboration platform and a robust set of analytical models.
As you can see from this article, we are just scratching the surface when it comes to implementing and monetizing big data. This is just the beginning, and the possibilities are infinite. Big data definitely empowers innovation and provides a scalable platform to create multiple successful strategies from one statistical model or one experiment. At the end of the day, the biggest risk is not doing anything.
Remember the bottom-line: For innovation to occur and thrive in a business, people are the biggest success factors, both from an executive and business user perspective. As you read this article and start thinking in this direction, remember the actions and outcomes need to be small, incremental steps. If not planned appropriately, it is easy to go overboard and attempt – unsuccessfully – to boil the ocean.
SOURCE: Big Data and Business Innovation
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