Skip to main content

Analysts must emphasize speed when drawing insights from data

Richard Jones Archive

Companies have always emphasized accuracy when working with data, and rightfully so. By using software tools to meticulously verify every fact and ensure data quality, IT officials can proceed with confidence that their insights will be fair and actionable.

Quality isn't the only concern, though. According to Information Management, there's another equally important value for companies to consider when working with large volumes of information - data velocity.

While ensuring quality is important, it's also vital that companies work as quickly as possible to turn their accurate information into real insights that can affect business decisions. In a competitive corporate climate, there's no substitute for speed, which gives firms the ability to outperform their rivals and ultimately earn more profits.

Narendra Mulani, managing director of Accenture Analytics, recently wrote about the importance of velocity. Given the proliferation of technology in the world today, he argued, it's never been more essential to generate quick insights than it is now.

"The need to ask for and act on data more quickly is due in part to heightened customer and business expectations," Mulani wrote. "With ubiquitous access to data via smartphones and tablets, businesses no longer have an excuse not to make informed decisions in real time. Mobile technology also enables workers to track insights about customers, products, work orders and more from anywhere."

How to ensure velocity?
According to Forbes, there are several things companies can do to ensure better data velocity in their operations.

One is faster collection. It depends on the company's specifics - for a retailer, for example, collection might mean culling financial information gleaned from sales, either in brick-and-mortar stores or online. For a social media site, it might mean picking data out of users' profiles and finding noticeable trends. One way or another, companies must work to generate data quickly.

The second element of data velocity is storage. Firms must have a way to curate all the data they collect, whether it's on large servers or through the use of a cloud computing service.

Thirdly, businesses must have dedicated teams of analysts who work quickly but effectively to find trends in their information and devise plans for action. Big data is useless if companies aren't able to analyze it effectively and execute their business blueprints.

Data quality is an important value, but so too is acting on that data in a timely fashion. Companies must do what they can to stay ahead.