A confession: I don't know my Klout score.
A second confession: I don't want to know my Klout score.
A third confession: I'm a hypocrite. I'm almost always looking for ways to meaningfully assess how influential — positively and negatively — my colleagues, collaborators and co-workers are.
"Influence" increasingly is the coin of the organizational realm. Influence defies title, credential and seniority. Somebody may be smart, talented and hardworking but do they have influence? Are they perceived as people who can move collegial hearts and minds? Employees with influence — or with reputations for influence — enjoy understandable competitive advantages in the organizational marketplace. But who decides who has influence? And who decides how to measure it?
Klout-ish services are simply logical and inevitable initiatives to measure that competitive advantage. Social media provide both the raw and the cooked material allowing algorithmic innovators to bring a bit of digital dazzle to "influencer metrics." Decades ago in more analog times, Eugene Garfield and his Institute of Scientific Information pioneered "citations" as the way to quantitatively assess the influence of scientific papers (and their authors) on a discipline. Today, we have Klout, Peerindex, Twitalyzer and other "influence analytics" to give people — and their employers — the power to neurotically obsess over how influential the numbers say they are.
Memes that Klout scores can cost you a job — or at least a job interview — have already gone viral on social media. Not unlike recommendation engines, influence scores seem destined to become one of those low-cost, high-impact online presences that will cast virtual shadows of disproportionate length and darkness. You think that Facebook photo of you puking at the frat party is going to come back to haunt you? Perhaps it's your single-digit — and falling — Klout score that should keep you up at night...
Of course, the Klouts and Twitalyzers are first-generation analytics that live web-wide in the digisphere. The real enterprise future of "influencer analytics" will soon be found inside the firewalls. With a few exceptions (salespeople, thought-leaders, marketers), most organizations don't care about employee IQ — Influence Quotient — outside the enterprise. They're more concerned with how influential employees are inside the organization. Do their colleagues and subordinates "cite" and reference them? Are their comments and contributions appropriately acknowledged? Are they — forgive the cliché — "team players" and appropriately influential as such?
If you're running IBM, Siemens, Toyota, Exxon-Mobil, CNOOC or any Fortune 2000 global enterprise, you are going to invest in an internal Klout or Peerindex to assess your internal influence marketplace. Quantitative assessments of influence will — and must — become part of job and performance reviews, as well as indicators of leadership potential. This is part of the "googlefication" tide raised in an earlier post. Technology executives can talk about the "consumerization of IT" all they want but the real impact or — please excuse — "influence" is coming from the internalization of social media services. Enterprise social media services such as Jive, Sharepoint, Yammer and Socialtext — not to mention instant messaging and repurposed email — provide all the material necessary for importing a more enterprise-appropriate generation of Kloutish influencer metrics.
More sophisticated managements will make sure their enterprise analytics go beyond the Klout paradigm to identify "bad" influences and influencers. After all, if a business unit leader is as much a "bad" influence in some sectors as a "good" one in others, top management needs to know. Indeed, the future of influencer analytics may be in novel ways of identifying and categorizing the ratio between "positive" and "negative" influence impact inside the enterprise. How do you rate and rank an employee who is a positive influencer with customers and suppliers but a negative influence on colleagues and subordinates?
Quantifying influence removes these questions from the realm of the hypothetical. The new reality is that enterprise social media may come into the enterprise with the promise of promoting better communication, coordination and collaboration but will ultimately perform as the algorithmic arbiter of influence — good and bad. In other words, these metrics will enjoy enormous influence.
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