Small problems with big data!

Conversations on Twitter have a unique ability to set off reflection and propel further conversation and thought. This invariably builds and shapes our collective ecosystem of sorts.  Especially so, when the conversation is between people who you watched from a distance, making a difference! 🙂

This post is a thought assortment, after spotting a conversation thread on Twitter.

It went like this.

Now, the power of analytics is large.

Yet, analytics has remained an enigma to a majority of enterprises. Bristling with potential and spoken at every conference with vigour. Yet on the ground, experiencing the true power of Big Data and People Analytics has remained a distant dream. And also, a tad too remote to comprehend.

Here are some thoughts on why!

a. ‘Big Data’ and good analytics is dependent on Good Data being there in the first place! Living with inadequate data is bad. But wrong data masquerading as ‘the truth’ is worse! No sophisticated tool can set this right.

While the gleaming benefits of Big Data and Analytics hold infinite allure, it needs a ton of clean up to begin with. Anybody who has worked with data and ‘clean up’ work during migrations will tell you that infinite allure pales into insignificance at the altar of ‘Data Clean’ up. It also means sitting down to rethink the way in which data is captured and processes to ensure there is sanctity maintained!

b. Skills to leverage and interpret data.

While tools and algorithms can chew the data and spew out reports and pointers, reports and pointers by themselves have very little meaning if insights and interpretations dont happen. In the drill of ‘getting things done’ the basic skillsets, ranging from formulating a set of hypotheses to putting interpretations to further tests with different cuts of data, have faded.

Interpreting and making meaning of the analytics in a context, unfortunately cannot be outsourced to an algorithm! That requires some relearning. Or even, building skills from the ground up.

c. That leads me to the big question : “What is the problem?”. Every organisation operates in a context. Problems, pain points and opportunities are rather unique to it. To buy an analytics engine or make some investment in Big Data capabilities before clearly identifying problems that beseech solutions is to put a big heavy cart before a sleepy horse, and wonder why the cart isnt moving!

For the few people that are convinced about the power of analytics and Big Data in organisations ( or the band of people that are marketing these tools), the first of steps is to help identify the problem. Getting people closest to the problem state it well and exploring if the tools indeed can provide the right solution!

To identify a problem that is at the sweet-spot between the what can be solved, where input data is present (or can be organised), the effort involved and payoff that will be got. That perhaps is the first problem.

To find that sweet-spot and to pull off a few good executions, and narrating the successes well, is good fodder for the future. In my mind, there is no doubt in what analytics can do. There is some real need though for experiencing it. What is needed is for people who are convinced about the power of analytics to look for a good problem to solve.

At the end of it, if the story is a good one to tell and more problems are solved, the money would be found and priority would get established. That of course, is a sign of maturity. 🙂

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