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The Future of the Company with Big Data: Insight or Execution, Evolution or Revolution?

Sogeti Labs
October 02, 2012

Innovation happens when good ideas are met with good execution. With a little bit of focus, it’s easy to find good ideas, through crowd-sourcing, an open management style and social tools. In fact, there are usually more ideas than that there is budget or organizational capacity to implement. While originally we may have thought that ‘all we need is a great idea’, in reality execution has become the bottle neck in innovation, especially in larger organizations. What happens when Big Data enters the picture? Today we are hunting for new revelations, great insights, new understanding of the world, our clients and our market. We want to tap into the knowledge that is hidden in the enormous data-streams. But what does that insight consist of, really? Will it be revolutionary? Or will it simply mean that insights will become a commodity? Where anyone can do a quick market analyses from behind any device, using publicly available services? Where everyone has the same insights? There are probably a few ways to remain competitive in the Big Data era, but like all competitive advantages they are bound to erode over time. I could imagine that initially access to unique data sources, a special tool for finding the hidden patterns or simply asking better questions will lead to some (or a lot of?) advantage. But then, over time as insights start to pile up, it’s probably the same as with innovation: it’s not the insights themselves, it’s how you execute: what you do with the insights and how quickly you can make a change. Or is there a second way to competitive advantage, a much more radical way where Big Data leads to radical new business models that open up unexplored markets? Sure, there will be data brokers and data refiners and data enhancers and the like, but those merely exist to help optimizing the Big Data supply chain (which admittedly may in fact be very profitable). But what about revolutionary ways to do banking, healthcare, manufacturing, mining, etc? Quite a few Big Data examples of today are incremental and often marketing or market-insight oriented, but there are some glimpses of a revolution. Is fighting criminals before they’ve committed the crime the start of a true revolution? IBM Watson is looking very promising (or threatening, depending on your perspective) for healthcare and finance. Will Big Data lead to revolutions or is this simply the hype speaking?

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SogetiLabs gathers distinguished technology leaders from around the Sogeti world. It is an initiative explaining not how IT works, but what IT means for business.

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    1. More succinctly, yes this is the hype speaking. The storage issues and extraction/processing time it takes to get meaningful results is still subpar. What is needed is new ways to understand the “viz”es we have before us – visualizations that excite us or turn us off but quite often are telling us something else all together.

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