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So What Do You Do Now with All Your Big Data?
Big data has given companies new ways of selling products to people. It has also given scientists new ways to understand complex phenomena and given journalists new ways to tell important stories. With big data, pharmacies and airlines can have a fairly accurate idea of why consumers call with questions before the call is even answered.
The costs of collecting and analyzing big data are high, and naturally, companies want to squeeze the most value from their big data. How can they do that? And how do companies know how much their big data is worth as a company asset? Answers are still developing, but some trends are becoming evident.
Pinning a Dollar Value to Big Data Is Difficult
Generally accepted accounting principles forbid companies from declaring data as an asset and forbid them from counting the money spent collecting and analyzing data as an investment rather than a cost. To use today’s accounting practices on big data, companies would have to assign a “shelf life” to their data, estimate its future value, and track changes in its value, and nobody really knows how to do that yet. Some types of data (like consumer data) lose value over time because people’s tastes and preferences change, and this makes some data a perishable commodity. The way financial experts get around these problems is generally by assuming that a company’s stock price reflects an appraisal of all its assets, including data.
Why Deriving Value from Big Data Is Difficult
Further complicating matters is that companies don’t always get the most value from their data. One reason is that a lot of that data is siloed and businesses haven’t centralized business data so it can be shared. With one department examining machine-generated data, another looking at social media data, and still another looking at marketing and sales data, any insights that might be gained from connecting these seemingly disparate data collections are lost. Another reason companies fail to gain the maximum insight from big data is that developing insights from big data is hard. Hadoop deployment can crunch the numbers, but it takes time, and people still have to look at the processed data to derive actionable insight from it.
Analytics and the Value of Your Data
Bain Capital says that analytics are the big differentiator between companies that derive the most value from their big data and companies that don’t. In a 2013 paper they found that only 4% of companies were highly competent at analytics, and that these were the companies that were able to change how they operate and put big data insights into practice. The reward for their efforts? Bain found that these companies were twice as likely as competitors to be in the top quartile of performance in their industries, three times more likely to execute decisions based on their insights, and five times more likely to make decisions faster than competitors.
Intelligent Archiving to Preserve Data’s Earning Power
The ultimate value of big data depends on how companies use it to make money and how long it is expected to be relevant. How long data remains relevant depends at least in part on maintaining it even after it has been analyzed. And many companies aren’t very good at maintaining data, according to Norbert Piette of Capgemini, who tells EMC, “Companies don’t know their data’s lifecycle, why the data is needed or even where it is. It’s not unusual for data to be scattered about, hidden in unknown nooks and crannies, put there by workers who want to protect their individual projects.”
Intelligent archiving should be part of a company’s big data strategy. Otherwise, companies spend money storing data while losing revenue that could come from being able to really use the data. Big data can be repurposed, and in ways it may not be easy to realize right now. But that’s the great thing about big data: sometimes you have no idea how much actionable, insightful information is contained in it until it is used in new and innovative ways.
The competitive edge that big data can confer isn’t just for tech companies or companies in data-driven industries (like healthcare and finance). Whatever your company’s industry, making the most of data is one key to outperforming competitors. Bigstep not only provides the convenience of processing big data without on-site infrastructure, it gives clients the convenience of the cloud and the speed of bare metal computing, plus the fastest connectivity and storage available. What that means is clients are able to analyze big data faster, derive insights sooner, and make use of these insights to increase their competitive advantage.