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Big Data’s Big Benefits to Big Industries

Big Data

Big Data isn’t just for big banks anymore.  In fact, if cultivated properly almost any industry can apply big data methods and analytics to more effectively target and serve customers.

True, the financial and telecom industries have set the standards in using big data.  Twenty-five percent of big data use comes from the financial industry, and each of the four largest universal banks is spending $7-10 billion annually on enhanced network monitoring and data aggregation technology to inform sentiment and predictive analytics.

But other industries such as retail, real estate, and even sports are finding ways to use big data to maximize investments, allocate resources, and generate larger profits, as demonstrated in this interactive infographic.

These industries are using big data to:

Increase operational efficiency.

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Hospitals and insurance companies are using patient data to generate better patient outcomes and to maximize health resources.  Research has shown that a 20 perent decrease in patient mortality can be achieved by analyzing patient data, and Kaiser Permanente was able to reduce doctors’ office visits by 26.2 percent by ensuring patient information exchange across medical facilities.

Delivery companies can use big data to cut down on operating costs.  By installing sensors in delivery vehicles, UPS was able to cut 85 million miles from its routes and reduce fuel consumption by 8.4 million gallons.

Even cities are using big data to efficiently allocate services and resources.  Portland, OR used technology to optimize the timing of traffic signals, eliminating 157,000 metric tons of CO2 emissions, and NYC leveraged big data to speed up the removal of trees destroyed by Hurricane Sandy.

Predict demand and trends.  

Utilizing point of sale data, retailers are able to reduce out-of-stock situations, predict the next top-selling items, time mark-downs, and ensure accurate product selections in each store.  McKinsey & Company estimates that retailers would be able to increase operating margins by more than 60 percent if they optimize big data analytics.

By analyzing data, baseball teams are able to price tickets based on demand, schedule games to maximize attendance, and determine which TV and digital media deals will be most lucrative.

Online housing searches have skyrocketed.  Zillow now has 46 million unique users, and Trulia 31.4 million.  By analyzing trends in housing searches, developers can determine what kinds of projects would work best in a given area, and industry analysts can more accurately predict home sales in the next quarter.

Troubleshoot problems.

Fifty-three percent of the 200 cyber incidents reported to ICS-CERT from October 2012 to May 2013 were reported by energy companies.  By monitoring the grid and analyzing data from sensors and databases, utility companies can combat blackouts and outages in real time.

Today’s cars are fully computerized, providing ongoing data on such things as tire wear, oil viscosity, and fuel efficiency.  By analyzing this data and tracking and mining social media comments, auto companies can predict equipment failures, accelerate product design, and improve vehicle performance.

One percent of Zynga’s online gaming users account for 25-50 percent of the company’s revenue, so player retention is of utmost importance.  Player analytics allow social game studios to understand in real time why users abandon games, and which other players may be at risk.

Big Data is here to stay, and those who master how it can be analyzed and applied to business goals will reap the benefits of their investments.

Comments on this Article: 1

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  1. DataH says:

    Paul, we are seeing an increase in businesses seeking specialized skills to help address challenges that arose with the era of big data. The HPCC Systems platform from LexisNexis helps to fill this gap by allowing data analysts themselves to own the complete data lifecycle. Designed by data scientists, ECL is a declarative programming language used to express data algorithms across the entire HPCC platform. Their built-in analytics libraries for Machine Learning and BI integration provide a complete integrated solution from data ingestion and data processing to data delivery. More at http://hpccsystems.com

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