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The company had just under 8 million accounts, and the number was growing quickly as existing members invited their friends and colleagues to join.But users weren’t seeking out connections with the people who were already on the site at the rate executives had expected.So you just stand in the corner sipping your drink—and you probably leave early.” Goldman, a Ph D in physics from Stanford, was intrigued by the linking he did see going on and by the richness of the user profiles.

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Something was apparently missing in the social experience.As one Linked In manager put it, “It was like arriving at a conference reception and realizing you don’t know anyone.Greylock Partners, an early-stage venture firm that has backed companies such as Facebook, Linked In, Palo Alto Networks, and Workday, is worried enough about the tight labor pool that it has built its own specialized recruiting team to channel talent to businesses in its portfolio.“Once they have data,” says Dan Portillo, who leads that team, “they really need people who can manage it and find insights in it.” If capitalizing on big data depends on hiring scarce data scientists, then the challenge for managers is to learn how to identify that talent, attract it to an enterprise, and make it productive.But Linked In’s engineering team, caught up in the challenges of scaling up the site, seemed uninterested.

Some colleagues were openly dismissive of Goldman’s ideas.Within days it was obvious that something remarkable was taking place.The click-through rate on those ads was the highest ever seen.Why would users need Linked In to figure out their networks for them?The site already had an address book importer that could pull in all a member’s connections.He began forming theories, testing hunches, and finding patterns that allowed him to predict whose networks a given profile would land in.