When asked to name a big data company, most people would think of an Internet giant like Amazon, Facebook or PayPal first, but big data is quickly becoming a significant focus of many more traditional businesses as well. More of our personal data and spending habits are being collected as we browse online or shop in-store, and it is being used to personalize our shopping experiences — whether through targeted advertising, product recommendations or price fluctuations. In addition, businesses are collecting more operational data to help optimize processes and run more efficiently.
Here are some real-world examples of how technology and big data have changed business administration.
American Express — Rather than rely on archival data to report on past behavior, American Express started extracting indicators that could help foresee customer loyalty, developed sophisticated predictive models to analyze transaction histories and forecasted potential account closures. The results of this analysis have led to more targeted loyalty efforts.
Fast Food — Gartner, the IT research and analysis company, worked with a fast food client to equip cameras and digital menus in drive-through lines with artificial intelligence. If the camera saw that the line was long, digital menus would automatically update to show items with a faster prep time. If the camera saw that the line was short, then the digital menus would automatically update to show items with higher price margins. This helps to create efficiency, keep customers happy and boost profits.
General Electric — The company is adding sensors in gas turbines, jet engines, MRIs and anything it calls “things that spin.” These sensors extract real-time data to proactively report on when the machines will need service — in fact, the sensors from one gas turbine alone produce more data per day than Twitter does in an entire week. This is especially important because GE earns half of its income from servicing its products. According to a 2014 article in the Harvard Business Review, these “digitally enabled, outcomes-based approaches helped GE generate more than $800 million in incremental income in 2013.” The article noted that the company expected that number to reach at least $1 billion in both 2014 and 2015.
Macy’s — The retailer adjusts pricing for its 73 million products in almost real-time based on factors like customer demand and current inventory. Technology from SAS Institute helps Macy’s to maximize profits and avoid supply problems.
Tesco — The supermarket chain collected 70 million data points from its refrigeration systems and analyzed them to monitor performance, predict when the systems might need to be serviced and do more proactive maintenance to trim energy costs.
Wal-Mart — Wal-Mart reported positive results after utilizing semantic data to improve its website search results through text analysis, machine learning and synonym mining. The multi-billion dollar company utilizes “semantic search technology to anticipate the intent of a shopper’s search,” a process that has led to a 10-15% increase in the number of shoppers actually completing a purchase. This is a significant increase, and it has occurred in the span of just a few months.
As big data continues to evolve and businesses become more sophisticated in its use, the Villanova School of Business is developing the data experts of tomorrow through its Master of Science in Analytics program. The program aims to equip students with the technical skills needed to collect and analyze data, as well as the business skills to translate it into the intelligence that can give businesses a competitive advantage.
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