Embedding big data analytics into company's DNA

Embedding big data analytics into company’s DNA

Embedding big data analytics into company’s DNA

Organizations are awash with petabytes of data and this can help companies create a customer DNA from this treasure trove. Don’t create a Chief Data Officer (CDO), rather let your Chief Marketing Officer (CMO) own this massive data franchise.
The Burgeoning C-suite

In the last couple of years, a number of fancy terminologies have been inducted in the C-suite. In an attempt to be a future-proof organization, the emphasis has been on innovating operations and powering it with big data and predictive analytics. Consequently, roles, such as Chief Information Officer and Marketing Officer, have gained acceptance and traction in boardrooms.

It is estimated that poor data quality costs an average organization $13.5 million per year, and yet data governance problems – which all organizations suffer from – are worsening. India too is fast inching towards a similar situation, especially considering the fact that almost 90 percent of the data was created in last two years.
“It’s flummoxing that companies have better accounting for their office furniture than their information assets,” said Douglas Laney, an analyst at technology research and consulting firm Gartner Inc. “You can’t manage what you don’t measure.”

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Understanding the Close Relationship Between the IoT and Big Data

The exponential growth of data in last few years is a conspicuous fact that can’t be ignored. The digital data generated by India in one year is humongous. The country’s share of digital information is expected to grow 23-fold between 2012 and 2020, driven by continued growth of Internet usage, social networks and smartphones among consumers, falling cost of technology, digitization among others.
Despite the fact that companies are gathering more data than ever, studies claim that 85 percent of CMOs say they struggle to effectively access and use this data in a meaningful way.

While  India is a late adopter of multi-channel customer engagement, the biggest hurdle faced by organizations infusing predictive analytics is data silos.

It was the credit crises of 2008 that first coerced major financial companies to look at their data assets with increased attention. This led to the creation of a niche function within organization focusing on the existing customer data for risk management as well as predictive customer analytics and reporting. It is quite evident that the India Inc. is yet to make major headway in this direction barring a few.

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