How To (Not) Get Smart About Big Data

And because Big Data is so BIG there’s a clear call for BIG companies to join efforts to explore and undoubtedly monetize it through building a ‘smarter’ planet (pun intended). And whilst, with the right mindset, a lot of good can come from it, I don’t think we have too good of a track record that all stakeholders (and yes, that includes you!) will benefit from it sufficiently. (I suggest you also read J.P. Rangaswami post on the theme. He makes some excellent points!)

 

But what can you do? How can you find your way through the clutter? How can you, not so big company or smaller business unit in a big company, understand if you need to fear or embrace Big Data? Esteban Kolsky says it exactly like it is:

I’d say that organizations get bombarded by Big Noise, not Big Data — data is what is filtered out of that noise.  The resulting data is not  something you need to fret about how to handle; [..]

Good time to shift strategies from panic, knee-jerking mode to calculated, strategic mode – don’t you think?

I could not agree more. It’s no time to panic, and it’s not the time to go out and buy all the technological solutions you may be led to think you need. What does it mean to go into calculated, strategic mode?

5 Questions to enter strategic mode
A good way to start being calculated and strategic about this is asking yourself 5 important questions. Here the are:

1. Start with asking (business) questions you need or want answers to. This could be any question, related to your processes, your customer needs, habits, your points of sale.. etcetera etcetera. Because, if you do not ask the right questions, you will never find the right answers in any data, let alone Big Data.
2. Re-think what you need the answers to your questions for: what is the proposed value coming out of knowing the answer? Will knowing the answer eventually result in creating more value for the company and the Customer? Is it actionable? If not, skip the question and focus on the ones that do provide actionable insights. There’s little time and little money, so you need to be effective with both resources.
3. Ask yourself: how can I obtain the answers to the questions fastest and cheapest? Can I get closer to the answer(s) by first asking my Customers? Can I get closer by first using data I already own? More data does not always mean better data. Relevancy is not always easy to establish, but 9 out of 10 times, the not so so sexy, not so far away, not so expensive is good enough. You don’t need to be exact all the times. You need to be closer than before.
4. If you still think you need to tap into Big Data, or need surrounding solutions, make sure you start any project with experiments and prototyping. Evaluate and iterate in short cycles, until you get it right. And don’t waste too much of your time getting it right. People will loose interest, and even if you get it right, chances of success decrease exponentially if people hopped on the next train.
5. Last, but not least, ask you self the question if you need all this “in (near) real time” like ‘they say’. Or that running your analysis once works just as well, because the patterns do not change that much.

 

To conclude: I do think though that you need to start answering these questions and jump into strategic mode. There is a lot of noise, but there’s a good chance some of the data in there is very useful to you. But you will never find it if you’re not looking for it strategically. And it will certainly not find you as fast as someone else can find it before it does.

So, what do you think?

Original Post: http://wimrampen.com/2012/01/02/how_to_not_get_smart_about_big_data/