All over the Web there are a lot of infographics that convey data points but I would argue that data without analytics to help us understand why, how and where are pretty much meaningless. In fact I would suggest that big data is over-hyped and that the real gold for marketers is the use of analytics that help us better understand consumers and customers.
According to Harvard Business Review “managers will see all these things in the coming months and years. The ones who respond most effectively will be those who have connected the dots and recognized that competing on analytics is being rethought on a large scale. Indeed, the first companies to perceive the general direction of change—those with a sneak peek at Analytics 3.0—will be best positioned to drive that change.” Amen !
The big data model was a huge step forward, but it will not provide advantage for much longer. Companies must once again fundamentally rethink how the analysis of data can create value for them and their customers.
The author of the boob entitled Big Data@work says “I eventually concluded, as a result of this research, that there are real differences between conventional analytics and big data, though you wouldn’t always know that from reading other books and articles about the topic, where the distinctions are often very fuzzy.”
In a 2013 survey of almost one thousand Harvard Business Review readers, for example, many respondents said they were familiar with the concept of big data, but only 28 percent said that their organizations were “currently using big data to make better business decisions or create new business oppor- tunities.” Only 23 percent said their organizations had a strategy for big data. Only a small percentage, 6 percent, strongly agreed that “My organization has considered the impact of big data on key functions within the business,” and an even smaller percentage, 3.5 percent, strongly agreed that, “My organization knows how to apply big data to our business.”
For those uses of big data that do involve internal decisions, new management approaches are still necessary, but not yet fully resolved in practice. This is because big data just keeps on flowing. In traditional decision support situations, an analyst takes a pool of data, sets it aside for analysis, comes up with a model, and advises the decision maker on the results. However, with big data, the data resembles not so much a pool as an ongoing, fast-flowing stream. Therefore, a more continuous approach to sampling, analyzing, and acting on data is necessary.
Of course, if big data is to make substantial inroads into businesses, it must provide some new opportunities. Going on about how much data there is in Facebook or Twitter, or the number of gigabytes in a single human genome, doesn’t help executives determine how much value they will achieve from exploiting big data. There are three classes of value: cost reductions, decision improvements, and improvements in products and services.
On the decision side, the primary value from big data derives from adding new sources of data to explanatory and predictive models.
What is common to all 3 uses of big data is that the data itself means little without insights and managers who can implement findings from big data into actionable and measurable business strategies. Use data for insights not just support to justify marketing initiatives.
