Big Data and the Measurement Paradox

I sketched out the above picture to help articulate a response to a LinkedIn discussion on big data vendors and their claims in helping improve the buyer’s journey:

Some thoughts…

  • Big data does not imply the right data. And even if you have the right data, it does not mean one has sufficient domain knowledge to contextualize it properly. For example, you may have tons of marketing data from your social media programs but you also need a performance measurement framework that helps you get actionable insight in way that helps “move the needle”…
  • …and most Big Data vendors’ core competence is in the technology – and often rely on the business user to provide the application context. And if the business user is also struggling to frame the context, then its a bit like the blind leading the blind.
  • Let’s say you do succeed in framing the context properly… and realize that you don’t have the right data, then how do you acquire the data? This gets to a very different challenge, that is often outside the scope of the Big Data vendors – in fact, its more and more sensory technologies like RFID (data from non-human assets) and social media (from human assets.)
  • The good news here is that the cost of data acquisition has been steadily declining. The bad news is that we often find ourselves in a chicken-vs-egg situation when management wants to do an ROI before they invest …and that goes to the “we don’t know what we don’t know” point in the measurement paradox.

[Thanks to my colleagues at LVSI for the source content on the above picture.]