The best way to understand the trajectory of your high performance career tomorrow is to look at what's happening to college undergraduates today. The Amazonified, Googlefied and Big Data-soaked — enriched? — nature of educational advice and assessment will increasingly define how you and your colleagues get hired, fired and promoted. Even if — perhaps especially if — you work at a smaller, entrepreneurial organization, you'll find your professional relationships algorithmically evaluated to help assure you really are worth that retention bonus or extra training investment.
Judgment and personal experience will matter less. Statistical context will matter more. America is now training a next generation workforce that accepts a prominent and dominant role for predictive analytics in performance assessment. At one community college, for example, a straightforward data-mining application allowed researchers to find "that by the eighth day of class they could predict, with 70 percent accuracy, whether a student would score a "C" or better." As the New York Times observed, "The new breed of software can predict how well students will do before they even set foot in the classroom. It recommends courses, Netflix-style, based on students' academic records." That represents a cultural revolution. Today, America; tomorrow, the world.
Of course, global giants like IBM, Amazon and Google have already begun importing predictive performance analytics to manage their human capital portfolios. Their efforts are arguably more sophisticated than these new college tries. But, understandably, they bring their own proprietary business biases into their designs. These collegiate and university initiatives, on the other hand, tend to be more open, transparent and experimental. It's easier to see what's going on and why. In the spirit of the "open source" and "open innovation" movements, that gives them greater power and influence. Many eyes, shallow bugs.
No great leaps of imagination are required to see how organizations large and small will look to import what they see cheaply and effectively working in college. This can be as technically straightforward as pre-hire assessment and on-boarding (admissions testing) or as challenging as mid-career professional development (new majors with high probability for high performance success). Recommendations engines can also allow companies to make all kinds of assessment-based improvements, especially where it lowers costs or liabilities: Analysis of field reports by sales representatives suggests that your team needs to initiate more support sessions with client; a review of your calendar and meetings says that you're spending too much time with your direct reports; analysis of your emails for the past six months confirms that you need to take an online course in "gender sensitivity."
In what will likely be a difficult job environment for several years, smarter and savvier employers are going to look for ways to get more useful and useable value from the data their employees are generating anyway. After all, they've already got the iPads, tablets and cloud-enabled technologies to digitally monitor individual performance.
This big data-driven "recommendation engine" reality mirrors the "self-quantification" movement that's already taken such firm root with so many improvement-oriented individuals worldwide. Novel devices like Fitbit and Nike Fuelband to personally monitor caloric intake and exercise intensity already enjoy pop culture success. Who doesn't look to Amazon and/or Netflix for behaviorally-informed suggestions on what to buy, watch or read? All the ingredients for innovatively fusing these techniques and technologies into cost-effective assessment services businesses have been around for over a decade. I wouldn't have guessed that colleges and universities would have been the most vibrant test-beds and vectors for human capital transformation but, upon reflection, it makes perfect sense. Between higher costs, debt, greater competitions, quality concerns and accusations of a "higher education bubble," deploying tools that can dramatically inform institutional and individual efficacy seems a smart investment.
Where ambitious project managers, team leaders and business unit heads once visited their alma maters to interview top talent, they'll increasingly be going back to check out their school's attitude/aptitude/high-performance assessment algorithms. Where organizations once demanded student transcripts, they'll now demand access to schools' "advisory engine" software. Ironically, the biggest impact America's higher education system may have on business is less about the students they educate than the tools and technologies they use to manage them.
What's happening in higher education assessment today will increasingly define the job and performance reviews of tomorrow. It barely took five years for the iPhone to displace the Blackberry as the corporate mobile device of executive choice. How long do you think it will be before the software used to assess college students will be entrepreneurially transformed into Amazonesque and Netflixed-like services "recommending" whether you deserve a raise or a promotion? Whether the economy improves quickly or sluggishly, the technologies of assessment are going to reshape both your compensation and your opportunities.
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