How to Unlock the Value From Big Data

As organizations wade deeper into the digital economy, there’s a growing realization that data is the fuel that propels the enterprise forward. Yet, coping with massive amounts of structured and unstructured data—along with the growing velocity of data—is a daunting challenge for organizations of all sizes.

Increasingly, those that deploy analytics to obtain deep insights boost the odds for success, while those that stumble may find their organization reeling or even failing. “It’s a critical time for many organizations,” states Goutham Belliappa, principal for insights and data at consulting firm Capgemini.

Over the last few years, mapping out a strategy and embarking on the journey has evolved from important to mission-critical. The ability to put big data to work and make lightening fast and insightful decisions can prove transformative.

Today, 63 percent of organizations rely on data for day-to-day operations, 60 percent use it to better understand customers, and 59 percent rely on data to measure business objectives, according to industry association CompTIA. Moreover, business leaders are looking for deeper and broader insights and perspectives.

“Organizations are looking to expand big data initiatives and incorporate advanced analytics capabilities.” says Scott Schlesinger, principal in the IT Advisory group at consulting firm EY. Nevertheless, “more and more of today’s data-driven organizations are drowning in data, yet starving for insights. Many still do not fully understand what it takes to turn existing and new data sources into innovative business-based insights.”

Breaking through the big data barrier requires the right tools—everything from platforms like Apache Hadoop to powerful analytics software—as well as an understanding of the framework required to transform raw data into insight and, ultimately, value.

Taking the Path to Value

A critical starting point for organizations looking to increase the value of data is to think beyond simply combining and recombining huge data sets in the quest for answers. “Volume and variety are fairly easy to deal with because it’s fairly simple, using today’s technology, to dump a lot of raw data into an analytics program,” explains Capgemini’s Belliappa.

“But creating value and moving the organization forward are far more difficult because many business leaders aren’t even clear about the business problem they’re trying to solve or what they want to do with all the data.” Equally vexing: Some executives think up challenges that aren’t feasible or possible.

Oberweis Data Analytics

One organization that has learned how to use big data to unlock value is Oberweis Dairy. The century-old company operates a dairy, 42 company-owned stores and a grocery store distribution business in three Midwest U.S. states: Illinois, Michigan and Missouri.

The business relies on several SAS Institute analytics tools, including DataFlux, Studio and ETS/Time Series, to take marketing to a new level. For example, Oberweis now plugs in National Oceanic and Atmospheric Administration (NOAA) data about weather and dew points and then compares it to point-of-sale (POS) data to better understand which marketing campaigns are successful and which are less effective.

“The effect of weather on sales is significant, so we’re looking at results independent of weather to understand whether marketing messages succeed,” says Bruch Bedford, vice president of consumer insight and marketing analytics. “If we don’t account for weather conditions, we receive skewed results that are artificially good or bad.”

The system uses daily sales reports that include prior day’s sales, month-to-date results and year-to-date totals. Altogether, the company relies on 18 different data elements.

“The capability is especially valuable when we launch a new ice cream product,” Bedford adds. “We are able to adjust our marketing focus very quickly and home in on what works.”