But now, big data or extreme data is pouring into organizations in higher volumes, faster, from a wider variety of data sources, and in more formats than ever before.
Big data dangles a large expanse of promise, but it requires business analytics as the foundation of an extreme information makeover for organizations to exploit the potential it offers.
For example, companies that use predictive analytics achieve higher returns by tapping into big data, according to Nucleus Research. With an average ROI of 1,209%, companies achieve higher returns with projects such as web-based customer sentiment tracking and demand forecasting.
As the name implies, big data means a vast volume of structured and unstructured data that companies must decipher to bolster management decision making.
In a separate research report, Nucleus notes that expanding the volume of data that can be examined with analytics allows employees to detect conditions that impact a large number of transactions, but can’t be observed without automated analytics. For instance, an auto manufacturer could examine parts purchases in its servicing industry to detect flaws or quality problems before they escalate to a public relations or safety crisis, Nucleus notes.
In addition to volume, extreme data is characterized by velocity; it streams in as fast as a customer can Tweet a product complaint. By using analytics to quickly analyze large data sets, a company can uncover problems and get actionable insight while its employees can still do something to fix the problem.
“Many consumers are likely to Tweet or blog about a product long before they share their opinions with a call center representative,” Nucleus notes. “Customer churn prevention also requires timely reactions based on the accurate view of leading metrics.”
Research firm Gartner Inc. has described “extreme information management” as the concept that a company’s current information infrastructure needs to be managed, primarily because of the fast growth of data and the types of data that must be analyzed to fuel revenue and market share growth. By 2015, organizations that build modern information management systems will outperform their peers financially by 20%, Gartner predicts.
Gartner also notes that advanced analytics will automate many management decision-making processes, allowing managers to focus more on setting strategy to steer the business.
But the immense volume and ever-increasing pace of data gushing into organizations today means that analysis of that data must be made available to a larger breadth of users to glean and exploit the actionable insight often hidden in extreme data.
Gartner recommends that companies expand their information management strategies to include a wider number of business users, not just a small group of executives. Instead, companies need to embrace collaborative decision making where analytics and social collaboration tools are combined so that employees in a wide variety of areas like sales, marketing and manufacturing can be involved in making decisions.
And research indicates businesses are starting to do just that.
Top performing companies are expanding the number of users who have access to analytics, according to recent research from Aberdeen Group. In addition, these companies are creating self-service business intelligence environments where users can quickly scour big data on a daily basis with minimal or no intervention from IT.
The best performing companies are almost twice as likely than others to enable business users to create and customize their own reports and views of business data without burdening the IT department, according to Aberdeen.
These companies have equipped a larger percentage of their organizations with analytical capabilities, and they’ve seen a larger portion of these users become engaged with analytics on a weekly or more frequent basis.
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