The Nostradamus Effect: Seeing Into the Recruiting Future With Data Science.

futureIf you run a business or manage a team, then you’ve felt–or can imagine–the extreme stress of a talent deficit.

Experiencing a rapid-fire personnel change is comparable to being struck by a sudden earthquake. Unfortunately, in this situation, hiding under your desk isn’t a means to stay protected. If your company can’t access the right talent, it’s doomed.

Too often, when employees leave unexpectedly or a new need suddenly arises, companies aren’t prepared to fill the gap and the entire business is left flailing.

Other times, the company does anticipate the need, realizing that they’re growing and will need to hire, but isn’t prepared for the challenges they face in finding the right talent.

Either way, when crunch time comes around, most companies end up sprinting in circles, desperate to re-stabilize their workforce.

Currently, businesses are at the mercy of unforeseen employee turnover and random shifts in the labor market–and it sucks. However, new breakthroughs in data science mean that within the next ten years, our strategies for building our workforce will transform completely. And that’s something we desperately need, because acting reactively is holding us back.

The Biggest Problem with Living in the Present.

Retrofuturistic-Gadgets-Medical-Examination-MachineRight now, most hiring is reactive. When the market gets tight, we hustle to hire faster. When there’s less pressure, we slack off. Either way, we’re always playing catch up.

For a high profile public example, look at what happened at Twitter recently. The company lost its CEO and several key product executives, the stock tanked, and the board was left scrambling to fill the void. Obviously, an absence at the leadership level is going to create more chaos than the average departing employee, but the same general principle applies to any key team member.

Almost all companies realize the risk associated with losing an important employee (or several), but most resort to generic retention strategies like company perks as a solution.

That approach is useful, but also problematic. Of course, you want your employees to be happy and stay with your company, and you should certainly take measures to ensure they do so. But that’s simply not enough.

The fact of the matter is that people are going to leave. Maybe they have family issues that demand attention or want a career change, and there’s nothing you as a business can do to prevent those things. But you can anticipate them.

Imagine if Twitter’s Board of Directors had anticipated Dick Costolo’s resignation months before it happened based on warning signs in his digital footprint and had already sourced a new CEO to step in if and when necessary. Doing so would have saved the company a lot of turmoil (and probably a lot of money).

Maintaining a stable workforce isn’t about retention–it’s about prevention.

Hiring from here on out will revolve around using data wisely to stay one (or more) step ahead of the next vacancy. And the data we have access to, plus the capabilities that come with it, have HUGE implications for how companies of the future will manage their workforces.

Seeing the Future Through Data Science.

Brown,r_time_macine60In 2020, a business owner (let’s call her Martha) is facing a major talent deficit. Her company’s hoverboards are in high demand and the pool of hoverboard engineering talent is getting extremely competitive. Plus, three of her superstar employees are leaving to volunteer as settlers on Mars. Sounds pretty grim, doesn’t it?

From a hiring perspective, it shouldn’t. If businesses like Martha’s adopt new hiring technologies and implement data science, they’ll be fine even in a worst-case scenario. We can already write algorithms that track behavior patterns leading up to an employee leaving and alert us to warning signs before they ever give notice.

We can now run analyses on market trends and know which factors create a tougher hiring market, so we can strategize accordingly. We have all the capabilities we need–now we just need to use them.

The difference between hiring today and hiring ten years ago is the sheer wealth of data we have available. Repositories like GitHub, LinkedIn, and Quora as well as social media channels provide us more information about our current and future employees than ever before.

Many companies are already using that data to hire smarter, but we have the potential to significantly expand on this. As workers continue to develop a deeper and more distinct digital footprint, companies gain the ability to make more timely and savvy hiring decisions.

By marrying predictive analytics and machine learning with the massive online data sets available now, we can deploy programs to mine social media for keywords that indicate people’s dissatisfaction with their jobs or likelihood to leave.

Or, we can discover unlikely talent pools for future hires by cross-referencing skill sets and tracking career paths. We have the information we need to determine when we’ll need to hire, where we should hire from, and what we need to consider throughout the entire hiring process.

These capabilities will surface within the next decade or so, and when they do, hiring will look completely different for both workers and businesses. Instead of worrying about what is, we’ll be strategizing in anticipation of what will be.

foleyAbout The Author: Jonathan Foley is the VP of Science at Gild. Jonathan has always enjoyed working with interdisciplinary teams and applying technology to positively impact the world.

He holds a BS and PhD in Bioengineering from UC Berkeley and as an undergrad, Jonathan worked on a team building a low-cost microelectronic sensor for detecting infectious diseases in resource poor settings. His graduate work focused on the transcriptional regulation of HIV and HIV latency.

Follow Jonathan on Twitter @l337d474 or connect with him on LinkedIn.

 

Jonathan Foley


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