Big Data for Staffing?

Consider this scenario: a company was struggling to make the right hiring decisions.

Struggling because of the criteria they were using to find the best candidates. Struggling in the marketplace to compete with richer companies looking to source exactly the same kinds of talented people from a relatively small pool. This hiring manager found ways to utilize key pieces of data to evaluate candidates that others had relatively little interest in. 

Big data is everywhere - how are you using big data to improve your hiring process?Sound familiar? If so, you’ve likely seen the 2011 movie, Moneyball, starring Brad Pitt. Pitt plays real world Oakland A’s GM Billy Beane. In reality, Beane used a new-at-the-time statistical method called sabermetrics to objectively analyze players’ abilities and performance over time. This led to the Oakland A’s 20-game winning streak in 2002 – the longest winning streak in American League history. Since Beane’s introduction of sabermetrics, the technique has infiltrated the sport and is widely used by most franchises. Perhaps the most interesting thing is that Beane did it with less than half the budget of other competing teams. The A’s had a payroll of around $40 million at the time – a tiny sum, compared with the ‘Big League’ likes of the New York Yankees, who spent about $126 million on its players in the same year.

What’s this got to do with staffing?

Consider the similarities a hiring manager for almost any organization has today. Resources (salaries, benefits, recruiting budgets) are tighter than they have been in years. The candidate pool is small – and to make matters worse, there are candidates so desperate for a job that they’ll put anything on a resume. Add to this equation the so called “talent gap,” or the shrinking pool of candidates with the right skill sets available – and the high competition among different industries for the same skill sets. (See our article about software developers and user interface designers and the auto industry for just one example)

What is a hiring manager, HR professional or C-Suite exec to do in order to “level the playing field,” so to speak? Consider a staffing partner that doesn’t fall in line with the “old guard” of talent scouts and recruiters. Certainly, applying what Beane did to other industries has its challenges, but it’s definitely possible. Generally speaking, there are common factors that everyone is looking for, and the big one is getting the best performance one can in terms of the amount of investment made.

Using an objective analysis, including key performance indicators (KPIs), provides a consistent process to find the right people. Metrics like time-to-fill, the percentage of contractors that turn into permanent employees, projects completed early versus projects terminated early due to performance are just several examples of the metrics that one can track when it comes to staffing.

No matter the industry, hiring the right person can be a challenge. One recent study claims that employers are more focused on hiring someone they would like to hang out with, rather than a person who can best do the job. Relying on intuitions like this can increase the odds of a bad hire – which can be costly for any employer.

Atlanta-based management assessment firm ghSMART president Randy Street says that making a bad executive hire, on average costs about 15 times the individual’s base salary. This number includes salary, severance and possible legal fees. It also includes “soft costs” such as the account lost or customer not won. While the costs for hiring a line worker may be smaller, the costs for a C-Suite exec can be even more.

“The average or typical hiring manager hires the wrong person about half the time,” Street says.

Chances are, you’ve been hearing about “big data” for some time now. The term Big Data refers to a collection of large and complex data sets that companies can analyze to develop deep, actionable insights for their business. For this example, let’s talk about the staffing industry’s ability to collect, store, analyze and track metrics about candidates and their firm’s ability to get the job done. Big Data, and more importantly, the analytics that go into it, touches almost every industry today – even those where it has not previously played a role.

This idea is now starting to spread to the staffing industry as well. A recent survey by Staffing Industry Analysts shows that firms surveyed placed using internal data and analytics metrics as being among the top three things that “will very positively impact the performance” of staffing firms’ acquisition process.

Are you ready for the Big Data changes to your hiring process? It’s part of the Staffing Revolution and will almost certainly impact your hiring process in the near future. It may not be long before hiring managers are asked to show executive management how the data that added up that the individual was a good hiring decision.

Ready to join the Staffing Revolution? Start by downloading "The Anti-Staffing Agency Manifesto", or connect with me directly.

Until next time, I've gotta 'Lotta opinion about everything
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