Data, both the usage and production, has become increasingly vital to companies over the past few decades.

The number of data collection methods continue to grow and similarly, options for data aggregation. Many big companies, including Under Armour, have established departments centered around technology.

Kevin Plank, CEO of Under Armour Inc., spoke in early March during a SXSW Interactive presentation about how businesses benefit from digital endeavors.

Under Armour hopes to bring some of its manufacturing jobs back to the United States with the Lighthouse Initiative – centered around a space in South Baltimore for the company to produce footwear and apparel locally.

Since 1996, when Under Armour was founded, the company has expanded with the acquisition of three technology companies – which are now combined into a Connected Fitness Division. While discussing this, Plank touched on the importance of data.

“Data is the new oil,” Plank said. “The companies that do well are the companies that use math.”

Utilizing concrete data is not a novel concept. For decades, many businesses have been using math and collected data to modify working strategy and understand marketplace trends.

Companies use social-media software to understand consumer behavior. Technology referred to as “sentiment analysis” uses math algorithms, or “natural language processing,” to filter through millions of messages and identify the most important. Starbucks and the American Cancer Society are among the large number of businesses using sentiment analysis to satisfy consumer needs.

Mathematical models and algorithms offer the most efficient, proven method for digesting thousands of data points. The demand for mathematicians, related to companies performing data analysis, continues to grow. Data from the National Center for Education Statistics and the Bureau of Labor Statistics ranked mathematicians as #8 – in a list of 50 college majors that offer the largest ROI.

Businesses that can determine strategy and make tactical decisions based on data are stronger than businesses that rely on gut feeling and intuition. No matter the method of collection, mathematics are absolutely vital to comprehend and digest dynamic data.

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