More and more organizations leverage tools and services that bundle different types of data. Very pragmatically, big data is about the profitable analysis of information sources that an organization wasn't previously tracking.

DATA first: Doing All Things Analytically                  

Never dabble in big data and analytics just because it feels fashionable to do so. Big data analytics definitely is an amazing discipline, however the techniques are instrumental. Your data science office should always focus on DATA first: on “Doing All Things Analytically.” The science part just isn’t the big science or rocket science that business executives might fear it is.

Anything Science just means Smart                  

In 1911, Frederick Winslow Taylor published his historic Principles of Scientific Management. Originally, Taylor used some profane terms like “shop management” and “process management.” This serves to show the sloppy use of “science” as a catch phrase. Today, we speak of “Smart” instead, and indeed, “Smart Data Office” would be a more appropriate name. Always bear in mind that businesswise, anything so-called scientific just means smart: Clever, new perhaps, but in any case completely common-sense.

Beware of Big Science   

Of course big science is an ancestor to big data -- but big data is not its heir! That’s what I tell executives all the time while stressing to beware of intriguing but false analogies. For instance in a December 2012 wrapup of top articles, presented the following shining big data examples:

  • the U.S. National Weather Service;
  • DNA Sequence Analysis;
  • the U.S. National Archive and Records Administration;
  • Optimal Wind Energy Turbine Placement and Maintenance;
  • the U.S. IRS Compliance Data Warehouse;
  • Project Artemis Medical Monitoring by IBM and the University of Ontario;
  • Perimeter Intrusion Detection by TerraEchos e.g. for the U.S. Department of Energy; and
  • NASA’s Human Spaceflight Imagery Collection, Archival and Hosting.

Certainly, those qualify as what calls “eight real-world big data deployments in a variety of industries” but all are expensive big science-related innovations and shouldn’t be mistaken for practical business role models. In a business environment, as a rule of thumb one should always be able to reduce expensive to efficient and innovative to effective, in accordance with the laws of business economics.

Your Practical Yoke         

That’s what I tell customers: DATA first, meaning “Doing All Things Analytically,” plus sure, by all means go leverage new data sources. Subsequently, big data may come soon enough. Or perhaps it never will – lucky you! And yes, you may need new tools, skills, vizualizations, extra cloud functionality, etc. Just let your Smart Data Office and IT department figure that out together, while you, as a responsible business executive, should do your utmost to grasp the relevance. With such an approach you’ll be able to explain to anyone why data-driven analytics serves as your practical yoke: a simple tool – perhaps a little heavy at first – but certainly worth the burden.

Improve your odds with Big Data & Analytics solutions  

No surprise that many organizations have not yet properly embedded big data in their operations. Only 13% have achieved full-scale production and a mere 27% and 8% told us their initiatives were “successful” or “very successful.”

How can you explore avenues for potential success? Go prepare yourself for the next DATA step and download our free report: Cracking the Data Conundrum. How Successful Companies Make Big Data Operational (Capgemini Consulting, January 2015).

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