Speaking of Big (and little) Data and using it Advantageously
We are not going to bore you by re-creating a bunch of statistics showing that data creation, data processing, and data understanding requirements are increasing at increasing rates. Just consider the widely cited fact that AT&T mobile traffic increased 8,000% between the years 2007-2010 or Eric Schmidt's often repeated comment that, "Every 2 days we create as much information as we did up to 2003." It is sufficient to say that the number of things that can produce data is rapidly growing. For example, 1 billion smart phones in use in 2012 and should take only three more years to double to 2 billion (Brown 2012). Increasingly, individuals make use of the thing's data producing capabilities to perform services for them. It all adds up to a number of challenges that are currently referred to as "big data."
While it has so far proven impossible to define data as "big," it is possible to objectively categorize Big Data Techniques, which are what have really been responsible for the so-called big data successes.
When considering Big Data Techniques or even traditional sized data, the truth of the matter is that a minority of individuals making decisions about or leading data initiatives possess the required KSAs/background. Poor understanding of how to successfully leverage data prevents organization from obtaining a data advantage. Seventy percent have a negative return on their data investments and virtually none measure these numbers internally (Aiken, Gillenson et al. 2011).
Here we have crystalized the reasons that have prevented most organizations from obtaining a data advantage. We advocate a single individual responsible for organizational data assets. Only through this individual's perspective will the organization be able to understand what size and shape challenge it is facing. Only then will it be able to make decisions about data assets using the appropriate context and understanding.
Figure 2 is a word cloud of this text describing it from a text visualization perspective. The next section describes the CIO Chief Information Officers (CIO) function as having a broad technology management focus and not enough resources to devote to data issues. The 3rd details, "exploiting a data advantage" and how broadly focused CIOs are ill prepared to devote requisite time and attention – they are data-unknowledgeable. Section 4 presents measurements showing how
organizations are not ready to leverage their data assets. The 5th examines the causes for this poor DM practice maturity. Section 6 argues the remedy – the TDJ, it describes the TDJ role as a business capability reporting outside of IT. Section 7 provides some motivational conclusions and some thought on implementing the TDJ.