The explosion of data analytics tools is being spurred by a fundamental economic truth: the plunging cost of memory technologies. “Enterprise disk” refers to large storage drives used in data centers.
Sitting in the left-field upper deck to watch the San Francisco Giants play baseball on May 11 would cost you eight bucks if you’d bought the ticket in late April. If you wanted the same ticket for the May 21 game, though, you’d have to pay $45.50.
The capabilities of software have finally caught up with what scalpers have always known: ticket prices should depend on demand. With the help of a data analytics system from Qcue, a company in Austin, Texas, the Giants have adopted dynamic pricing, which enables ticket prices to change depending on circumstances that affect demand—even up to the last minute. The system quantified just how low prices would need to be in order to fill seats at a Wednesday-night game against the mediocre Arizona Diamondbacks, and how much more people would be likely to pay for a Saturday-afternoon game against the Giants’ cross-bay rivals, the Oakland A’s.
The Giants organization credits dynamic pricing with a 6 percent increase in ticket revenue last year over what the team could otherwise have expected from a winning season that culminated in a World Series victory. In fact, the Giants are now experimenting with other versions of dynamic pricing, like using weather data to figure out the optimal price for beer.
It’s but one example of a new generation of database and data analytics technologies offering new ways for companies to reach and—they hope—please their customers. This is the big idea that we will explore throughout May in Business Impact.
Databases are as old as computers and have been at the heart of most companies’ operations for decades, but the last few years have seen significant advances in both the hardware and the software involved. Pools of data are getting dramatically larger, and methods of analyzing it are getting dramatically faster.
That’s why dynamic pricing is moving beyond the airline industry and its mainframe computers. Yet even as the analysis can now be done on less sophisticated hardware, it is able to work in more complex situations like a ballpark, which can have thousands of seats in numerous pricing tiers. Because of this improved power of many kinds of data analysis, more businesses are likely to try to use it to squeeze improvements out of their operations, from attracting and keeping customers to figuring out which new products to introduce and how to price them.
These new technologies don’t yet have a catchy name, like “the cloud” for centrally located computing. They’re sometimes called “Big Data,” but that term is applicable only to some of the changes under way. Their magnitude was summed up in a March report by a team of Credit Suisse analysts, who said the IT world “stands at the cusp of the most significant revolution in database and application architectures in 20 years.”
Big tech companies such as IBM, Oracle, and Hewlett-Packard have spent billions of dollars to acquire companies that offer business analytics or database technologies. Data-related startups are also on the rise in Silicon Valley; most big VC firms now have a partner specializing in the field. The data being analyzed doesn’t even have to come in the form of transaction records or other numbers. For example, CalmSea, a startup formed in 2009 by several data industry veterans, sells a product that lets retailers glean useful insights from the vast amounts of information about them on social networks. The retailers might figure out that they should offer special deals to loyal customers, or launch finely tuned marketing efforts in response to changes in public sentiment.
Big consulting companies are also ramping up their data-related practices. “So much new data is out there,” says Brian McCarthy, director of strategy for analytics at Accenture. “Companies are trying to figure out how to extract value from all the noise.”
All of this is made possible by two separate strands of technology.
* Traditional database and business analytics tools are being reëngineered so that they no longer need to store data on a traditional disk drive. Instead, they can operate entirely in a computer’s onboard memory—the kind that’s not in a separate drive but hardwired into the heart of the machine. This “in-memory” approach would have been prohibitively expensive a few years ago but is now feasible because of the continually declining prices for flash memory, the same solid-state technology used in mobile phones and music players.