Peter Drucker and the Big Data Revolution
In 1955, Peter Drucker addressed a contingent of IBM executives, praising them for the company’s extraordinary ability to deliver in its accounting machine business “what the customer considers value.”
They “come to you because of the service you give” in “systems and procedures analysis, understanding of data processing and information gathering,” Drucker told the group, which was presided over by IBM’s president, Thomas Watson Jr., the man who over the next 15 years would drive explosive growth at Big Blue.
Then Drucker added, almost wistfully: “I wish you knew more about what to do with information once you get it, but that is a private wish.”
More than half a century later, Drucker’s wish is finally becoming reality, owing in part to the insights of a man who worked closely with another Watson.
Anant Jhingran spent more than 20 years at IBM, where he worked on technologies that were used in the Watson artificial intelligence computer,
Anant Jhingran (Photo credit: Sebastian Bergmann)
which in 2011 famously bested two former champions on the TV quiz show “Jeapordy.” He now works at a Silicon Valley company called Apigee, which offers an array of tools that aim to satisfy just what Drucker envisioned: helping companies figure out what to do with information once they get it.
The challenge, of course, is that there is ever more information to contend with. “Half a century after computers entered mainstream society, the data has begun to accumulate to the point where something new and special is taking place,” Viktor Mayer-Schonberger and Kenneth Cukier write in their new book Big Data: A Revolution That Will Transform How We Live, Work, and Think. “Not only is the world awash with more information than ever before, but that information is growing faster.”
The far more important shift, though, is that this surfeit of information is not simply piling up, like grain in a silo. It is being carefully sifted and sorted so that, in the words of Mayer-Schonberger and Cukier, we can now “extract new insights or create new forms of value, in ways that change markets, organizations” and much more.
Apigee is hardly the only company playing in the Big Data space. A legion of others, including IBM, are helping their corporate customers analyze and contextualize the ocean of information that they now have available. But Apigee is particularly intriguing because of its focus on harnessing the power of mobile apps—the way that increasing numbers of people are choosing to communicate, buy all kinds of things, share and socialize.
The connection between these apps—often developed by communities of independent, third-party programmers—and a company’s internal, backend IT system is known as an application programming interface, or API. Apigee specializes in providing API technology to companies such as Walgreens, eBay and AT&T, as well as to outside app developers. It then helps both camps make sense of the reams of data that get generated so that the best products and services can be delivered to end users as quickly as possible.
With the right sort of API, for example, software developers can quickly detect, diagnose and fix problems with their apps running on mobile devices—in real time.
Meanwhile, executives can swiftly spot consumer trends while pulling in information from a wider and wider variety of sources. The idea is for a company to understand not only what people are buying, but where and how they’re making these purchases—and then what they’re saying about the experience on social media. Armed with this wealth of information, a retailer might target customers with special promotions for items that the company already knows they’re interested in, just as their smartphones signal that they’ve stepped inside one of its stores.
The “API phenomenon” and “a passion for data” are what led Jhingran to Apigee, where he is vice president of products. He carries several lessons from his work at IBM with him. For one thing, he says, he and his fellow IBMers found that people needed to interact with Watson “in the most natural way” possible. Similarly, the data that results from APIs and apps must be presented in a form that is easy to digest. “It needs to be actionable for the business person,” Jhingran says, or it’s basically worthless.
For another thing, Watson taught him that it’s essential to concentrate on the quality of information, rather than the quantity. “A hundred gig of well-processed data is better than terabytes of unprocessed data,” Jhingran says.
Drucker pushed this notion much further, maintaining that “advanced data processing technology isn’t necessary to create an information-based organization.” He noted that “the British built just such an organization in India when ‘information technology’ meant the quill pen and barefoot runners were the communications system.”
But Drucker was also clear that as “advanced technology becomes more and more prevalent, we have to engage in analysis and diagnosis . . . even more intensively or risk being swamped by the data we generate.”
With Big Data, it seems, we are not only managing to avoid any such trap; businesses are taking what could have been a danger and turning it into a tremendous opportunity.
No comments:
Post a Comment