An Investor’s View: Analytics to Game-Change Hiring

Every entrepreneur knows that translating an inspired invention into a category-making business begins and ends with staffing. Business is a team sport. As trite as it is clichéd, it’s true. The employees we hire, like the team we put on the field, dictate whether we end up in the winner or loser column when the season ends.

It is ironic that in Silicon Valley, ground zero for companies employing next generation technologies, most employers remain remarkably old school in how they hire, often relying on academic brand attribution, gut instinct and tribal affinity in deciding who fills what roles on a team.

For sure, Application Tracking Systems add value by helping automate base hiring workflows, and some companies use algorithms to filter job applicants up or out. Platforms like LinkedIn leverage technology to connect jobseekers, recruiters, and hiring managers. Yet when it comes to urgent hiring choices, especially for businesses that are scaling quickly, most companies ultimately rely on a manager’s short cut decision-making style.

Compared to the cyber security world, many companies’ level of hiring sophistication is akin to manually uploading anti-virus software to our mainframes and crossing our fingers!

What’s been missing is a new generation of collaborative decision support software that enhances both the process and culture of corporate hiring and recruitment. Talk to any hiring manager and you will hear common frustrations: hiring takes too much time or “recruiters don’t get it.” Recruiters have parallel frustrations, given that hiring is not usually a manager’s core strength. In such a culture, hiring becomes a headache, a task to complete rather than the core metric that supersedes any quarterly financial metric.

Even as a new generation of big data analytic systems emerges, no hiring manager wants to outsource their decisions completely. Instead, we need solutions that couple the efficiencies of checklist automation with the power of human insight. In addition to improving efficiency, we can leverage decision-support technology to filter out hurried decision-making that defaults to subjective thinking and unconscious bias, and focus on what’s most relevant: hiring “A” players that best fit their designated roles.

We also need a new automated approach to radically compress the cycle time it takes to hire the best people: to build job descriptions that attract the most qualified applicants, develop evaluation criteria that drive better decision-making, and help managers deploy state-of-the-art best practices in hiring. Such enhancements promise to transform the dynamics among hiring managers, recruiters, HR and applicants.

Fortunately, companies like Unitive are applying big data and new decision-making algorithms to radically improve the efficacy of hiring. Unitive is beginning to demonstrate the impressive ROI that occurs when the latest Silicon Valley innovation is integrated with human insight and experience. It holds the potential to transform the most fundamental choice that businesses make.