Big Data Demands Organizational Change
Aside from the advent of the Internet itself, big data is having the greatest technological impact on the economy, Andrew McAfee, principal research scientist at MIT's Center for Digital Business, told attendees during his keynote at the SAS Global Forum Executive Conference in late April.
"We have different ways to address common business challenges as a result of big data," he said, citing the airline industry's use of predictive patterning to determine potential flight delays and health insurance companies' ability to identify gaps in care as examples. However, he added, "I am not confident companies will do what is necessary to make the [internal] changes to address big data."
McAfee and others at the conference pointed out that many enterprises today still struggle to transition from sitting on a gold mine of big data to running analytical processes with that data, due to the sheer speed at which business moves. In addition, companies have struggled to redefine business rules as a result of channel evolution, changes in customer behavior due to the rise of social media and mobile devices, and economic events such as the Great Recession.
One of those evolving areas is revenue management, which in the past was all about selling the right product at the right time for the right price. Historically, when InterContinental Hotels Group relied on data and analytics for revenue management, "we looked at what happened on the property last year," said Craig Eister, its vice president of global revenue management, during a presentation. "Now, it's become muddy and challenging for us in several different categories. We're not just selling a room anymore. We're selling a view or the fact that the room is not near an elevator. The complexity around inventory is changing."
That's having a dramatic impact on the organizational chain of command. Now, before marketing teams at InterContinental deploy price-sensitive campaigns, they reach out to revenue management to discuss implications derived from data. The "old way of segmentation," such as classifying customers by business or leisure categories, no longer applies, Eister pointed out.
Similarly, Lenovo, a maker of computers, tablets, and other hardware, operates in a space "mired in data," said Ajit Sivadasan, its global vice president of sales and marketing. Between retail store operations, e-business channels, and customer conversations spanning Facebook to Skype, Lenovo has a growing need to measure cross-channel interactions to gauge the effectiveness of digital marketing and advertising initiatives. "The bottom line is, we have a lot of data, and we don't know what to do with it," Sivadasan said.
Lenovo was an early SAS user, drawing on advanced SAS Visual Analytics to optimize marketing and campaign spending in real time for the May launch of its IdeaPad Yoga 11S touch-screen device.
Another was JPMorgan Chase. "The new Visual Analytics change[s] how we are interacting as a business, and...how we look at solving business problems," said Chris Gifford, senior vice president of customer analytics at JPMorgan Chase, during a panel discussion.
SAS Visual Analytics was one of SAS' first products to integrate with the SAS 9.4 business analytics and visualization suite, available on-premises or as a hosted or cloud-based solution. Randy Guard, vice president of product management at SAS, noted that a large number of clients are deploying private clouds that they want to be able to scale quickly.
For companies looking to deploy advanced analytics and willing to commit to making fact-based decisions, Jim Davis, SAS' chief marketing officer, offers one bit of advice: "Everybody thinks you can just go out and buy a product, but organizational readiness is a big part of it," he said. "Go at it from a business angle, not just a technology perspective."
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