Although information has always had an important role in the business world, the Big Data movement has placed a larger emphasis on the aggregation and management of digital resources. Companies around the world are now seeking programs that help employees collect and store increasingly larger volumes of information because most decision-makers believe the chances of striking gold will increase if they have more data to analyze.
Ironically, organizations that believe in collecting massive amounts of information often find themselves inundated by the sheer size of the resources under their control and, as a result, encounter new performance obstacles that lead to substantial issues. This conundrum is forcing executives to ask, “Is bigger always better?”
The answer is no, especially in today’s Big Data world. Rather than focusing on the quantity of information they collect, organizations should focus on the quality. Because there’s no finite definition for “Big Data,” each company is forced to develop its own innovative strategy that aligns with the way employees work on a daily basis. In many cases, speed will outweigh a number of other metrics associated with the information being collected. If an organization has the power to quickly convert unstructured data into useful insight for its marketing and sales teams, for example, it will likely be able to reduce client churn and improve its ability to attract, engage, and retain customers.
Still, many experts believe that the data with the largest business impact is the most difficult to measure. The need to do so will pressure executives to build robust warehousing environments that can make sense of various information sets as quickly as possible, allowing firms of all sizes to use a broad range of information for numerous practices, improving their ability to compete and prosper in the long run.
Quality over quantity
Of course it will become increasingly difficult to find a needle if the haystack continues to grow in size. This prospect should encourage executives to build programs that regularly maintain the haystack, trimming the unnecessary heaps of hay to make sifting through the pile less complex. In terms of data management, this means that organizations need to understand the complications and opportunity costs associated with the inability to keep information storage environments in check.