Can Big Data Pay Off Big?

Perhaps one College Essay of the most exciting advances in this decade is the emergence of big data, a collection of data sets so large they cannot be processed with standard database management programs. The analytics that companies glean from this data yield quantitative insight into business strategy that was previously unavailable. The world’s technological per-capita capacity to store information has roughly doubled every 40 months since the 1980s.

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Watch Service”>Eric Schmidt, Google’s past chief executive officer, the world creates five exabytes of data every two days. That is roughly the same amount created between the dawn of civilization and 2003. Despite this, we are still in the first frontier as technology companies solve ongoing challenges that include capture, curation, storage, search, sharing, analysis and visualization.

Now that companies have the infrastructure in place to capture and aggregate the data, many are in the process of figuring out how best to use the information. Smart companies have created data strategies based on business priorities and defined their objectives before the technologists implement. The skill set and the context needed for analyzing and interpreting the data must expand beyond the IT department – computer programming, statistics, socio-economics, competitive intelligence and consumer insights are all needed to seize key indicators.

Marketing departments show early success harnessing the power of big data; utilizing granular customer data from loyalty programs, unstructured social media data and Web analytics. Companies in retail and entertainment industries are using data to better personalize services, increase customer acquisition and gain an advantage over competitors.

However, the total value of the data is greatly minimized if it is analyzed in silos. Most of the data-driven wins in the marketing realm are incremental and not blockbuster innovations. As well, too much emphasis on one type of data or analytics can be dangerously myopic. Much has been written about the current and projected shortage of talent in the analytics arena needed to monetize the insights the data holds. Companies are hard pressed to find the employees with advanced training in statistical and machine learning they seek. While this skill set is invaluable, straight statistical analysis of the data in a vacuum is not the most fruitful path to true innovation.

We contend that cross-functional teams need to share and cross analyze the key findings from their respective data sets when charged with looking for new large growth opportunities. They need to assess what the data is telling them in the context of their market, adjacent markets, culture and world economics. Consider that the immense amount of data that any one company has captured and is analyzing is but a fraction of the relevant data that exists. It is easy to mire down in to data recover and take the short view,but you can try a carbonite offer code. We encourage teams to take a broader perspective- consider all of the very complex factors at work in our world today.

There is no doubt that sophisticated analytics can substantially improve decision making, minimize risks, and uncover emerging trends. But the practice of analytics alone does not have all of the answers nor is it an oracle that will reveal the next big thing. We still live in a human-centered world. It is important not to lose sight of the fact that human psychology and behavior ultimately drive each data point. Human genius is needed to decipher its own complicated web and drive innovation.