Where is the Next Breakthrough in Analytics?

Upfront, it amazes me how little Las Vegas and the whole “Vegas thing” – a very small amount of gambling, too many late nights in Casino rooms bars, 3 hours a sleep a night (regardless of how much time you give yourself to try) – appeals to me any longer.  I don’t like this think of this as “getting older” – I think it is “getting wiser.”  Likely semantics.

Anyway, back on point.  For this blog post I want to talk a little bit about “analytics.”

Clearly, being at IBM IOD, analytics are going to be a hot topic. but in any context, they really should be.  Why?  Well, there is so much data available now that very few decisions should fall into the category of “made without supporting information.”  Where do analytics apply?  Not to cop out, but pretty much anywhere.

As an example of a “new” analytics offering, IBM showed off a new project in the labs – a dynamic analytics tool which incorporates a really good, and easy to navigate, visualization capability along with embedded predictive analytics.  The best part is that it did not (seem to) require any data modelling ahead of time.  We saw a demo where the demoer (yeah, I made that word up) was trying to determine if it made sense for him to go back to school.  The data exploration – on education level linked to various other factors – illustrated findings like:

– would he make more money

– would he have to work longer hours

– would it take away from time with family

– what would it do to his leisure time

… and more.  It really was impressive relative to how hard – and how long it takes – to do that analysis today.

It did get me thinking though … if the software already knew about the user, if it knew what was important to him (which clearly isn’t hard anymore with what we put out in social networks), why not let him know what the impact would be without him having to do any level of navigation at all?  If he wasn’t married or didn’t have kids, the answer to that question would not matter.  He told the audience that he loved to golf, well then, shouldn’t free time mean a lot without him having to navigate to that answer?

This is not to say that an algorithm is going to nail the answers every single time, but why not start there and then “drill” into the answers and explore further after the initial presentation that the analytics algorithm matched to your – or your company’s objectives – in the first place?

Hey, this might just apply to booking travel … need to think about that 😉

’til next time, Kirk out.

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