Is Big Data still a Challenge?

Today, big data is getting a lot of attention. Companies are spending good amount of money in the name of big data. Despite this, there are apprehensions that big data is not begetting its full strategic potential.

A recent report by TCS on big data revealed that the toughest challenge for businesses using big data initiatives is getting different business units to share information across organizational silos.

“The toughest challenges for businesses implementing big data initiatives is getting different business units to share information across organizational silos and determining what data to use for different business decisions,” TCS said in a release. The report also indicates technological challenge of being able to handle the large volume, velocity and variety of big data.

“Regardless of whether they are leaders or laggards, nearly half (44%) of big data investments are going to business functions on the revenue side: sales, marketing and R&D/new product development. Much less (24%) is going to back-office functions: IT, finance and HR,” it said.

The report further revealed that leaders in big data are doing analysis outside business units with 79% of them using the IT function or a separate big data team and only 21% doing the analysis in business units. The laggards, on the other hand, are doing only 68% of their analysis outside the business units, it added.

Utilization Gap

 So the question which arises – Where does this utilization gap come from? The CMO Survey highlighted some of the points for this gap:

1. Producers of marketing analytics produce data but not insights.
2. Marketing analytics arrive outside the decision making window.
3. Potential users of marketing analytics may not have a strategic planning process or marketing decision making process that builds in a step to use available analytics.
4. Marketing analytics systems are not sufficiently customized to the company’s marketing decisions.
5. Producers and users of marketing analytics do not have a strong relationship that allows the analyst to understand or anticipate users’ needs.
6. Users do not have sufficient training to understand marketing analytics. A crash course in regression and other simple analytic tools may be necessary.
7. Marketing analytics is often viewed as a silver bullet and companies fail to collect deep, non-quantitative, insights about customers that provide the bigger picture into which analytics needs to be placed.
8. Companies need to figure out how to use marketing analytics to create new growth for their companies, not just penetrate existing markets.  Many companies have not figured out how to use analytics to enter new markets or to compete in wholly new ways.
9. Accuracy is essential and yet there are areas in which marketing analytics fails to inspire confidence.  Mining text is a good example of this gap.  Investing in tools to understand what customers are saying about your company on the web and the valence of these statements is important.

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