Moving Data Science towards BOP

“Big Data” was the most over used terminology of the gone year, and the forecast does not predict any bend in the trend this year too. We are connected everywhere and it now does not take any effort for the fortune tellers(analysts) to predict your next move .The challenge is not the accuracy of the prediction but its relevance as you are one of the millions intertwined in this ever growing network.

The only way we can puzzle the magician is to steal him off his tricks, the trick in this case is the wide spread data. This is the challenge we face today in our country where most of our population is e-illiterate. Does that sound secure and safe for the 70% of the population?

Well, it isn’t exactly.

Whatever qualms we have with our over exposure to the big firms, the people at the bottom of the pyramid suffer the most of the insulation from the network.

Data is indeed important and there is data available for this section of the population, so what is the big ruckus?

Statistically speaking, it is the frequency of data collection that predicts a trend with a high relevance but what we have in our country are yearlong inconsistent surveys that become irrelevant because of the time spent to accomplish it and no follow up analysis. Cannot be cruder than this, right?

Shifting the data science down to the bottom of the pyramid has far more return on both, effort and investment. Imagine if we can predict what healthcare facility we have to set up in a village following the month of March due to the shortage of water. We need not go into the causality to forecast the requirement anymore.

The same holds true for a consumer goods company who find the granularity of the information untrustworthy for designing products to 70% of our population. To close on this gap they require substantial investment in collecting data and marketing the products. But, a product with immediate use would require substantially low proportion of this expenditure. So, how do we sole this puzzle?, …..well,you know the answer by now.

There might be only one answer for many problems, but we have to be prudent to know which question to answer first. There is no better time but now to focus on moving the data science towards the bottom of the pyramid and innovate the way we capture the data.