This is extremely important to the retail business because it enables companies to avoid delivery problems and minimized storage costs. Blue Yonder software is programmed to learn more with each piece of new information it acquires, as well as to independently recognize relationships.
In this manner, Weiss and his employees discovered that in a specific branch of a supermarket chain, sales of milk, chocolate bars and apples shot up on certain days -- coinciding with the arrival of new school groups at the nearby youth hostel. The software now calculates, using data that includes school vacation schedules in the surrounding states, the probability of new busloads of students arriving at a given time.
Blue Yonder employees had a similar realization with sliced bread. "Children don't go to school on days preceding or following midweek holidays, and the demand for sliced bread goes down as a result," says Weiss. Inventory ordering systems are now adjusted automatically, he explains. "It's a relatively straightforward process."
Increasing Accuracy of Sales Forecasts The constant in-stream of new data has enabled Blue Yonder to develop something of an ad hoc market research system on buying behavior, which can also be used for other purposes. The drugstore chain dm has Weiss's team calculate optimal staffing levels for its stores, and it also provides sales forecasts for each store.
The data analyses are of similar interest to insurance companies. As a "future scenario," Weiss describes a car equipped with more than 1,000 sensors, which permanently monitors driving behavior. Drivers who provide their insurance companies with the data, which can easily be used to develop a risk profile, could in the future be enticed with especially low premiums, says Weiss. "Big Data is currently revamping our entire economy, and we are only at the beginning," says the head of Blue Yonder, for whom, of course, this is a positive development.
Important Big Data customers are also reporting the first measurable successes. A study IBM has compiled on a few "success stories" among its own customers reports increases in efficiency of about 20 percent. According to Blue Yonder customer Otto, the data experts' work has improved "the quality of sales forecasts for individual items by 20 to 40 percent." The mail order company is so enthusiastic that it is now using the method with corporate brands like German sporting goods retailer SportScheck, as well as acquiring a 50 percent stake in Blue Yonder.
Netflix, an American company that began its business with DVD rentals and now provides its 36 million customers with movies primarily through streaming video feed, is yet another example of the far-reaching possibilities of Big Data. Netflix recently achieved record viewership levels with the series "House of Cards," a political thriller starring Kevin Spacey. The show's success, though, was hardly by chance: Netflix used data analysis in its decision to buy the series. Netflix has the ideal qualifications to take such an approach. The company knows, on a day-by-day basis, which genres are doing well, when viewers are losing interest or which actors are especially popular. Based on such information, "House of Cards" corresponded precisely to the predicted tastes of Netflix viewers, and proved a success.