3 Ways to Avoid Big-Data Blind Spots When Recruiting
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Tom Brady, arguably one of the top five quarterbacks in NFL history, was not drafted until the sixth round of the 2000 NFL Draft. With all the data in the hands of scouts that day, how was he missed?
Well, it starts and ends with two magic words -- big data. And just like big data is impacting how executives in the NFL build their teams, it is also changing the way we do business, tantalizing leaders from both Fortune 500 companies and start-ups alike.
A study published by MIT showed 91 percent of Fortune 1000 company executives are planning to use big data. However simply gathering data is not enough to make critical business decisions, especially those that impact talent acquisition efforts. It is necessary for leaders to understand how and when to use big data in their recruiting and the gaps that are created when it becomes an overly relied upon tool.
Initially, most companies invested in big data for their sales and marketing departments. This made sense as it empowered executives to more accurately forecast revenue generation in the short and long-term. However, more corporate leaders are starting to realize that implementing big data across their entire organization, even in "non-revenue’" generating groups such as HR, is going to be a critical factor in their ability to remain competitive in an economy that is increasingly global, mobile and social.
Given the enormous costs of bad hires, which this Career Builder study found costs business more than $50,000 each, we are seeing corporate leaders increase their investment in big data programs in the areas of recruiting and hiring as a way to further mitigate hiring risk. In fact, Deloitte predicts that global spending on integrated talent management systems will grow by 17 percent this year and the HR Service Delivery and Technology Survey, a global survey of 1,048 companies, found that one in three respondents plan to spend more on HR technology in the coming year.
As the CEO of Peak Sales Recruiting, we are working with world-class clients to incorporate big data into the recruiting process. While these investments will have enormous return on investment, we have also seen first-hand that an over reliance on big data comes with a myriad of risks and pitfalls.
As a result, we have identified three ways executives can avoid the ‘blind spots’ that are created by big data when recruiting:
1. Don’t rely entirely on technology.
When effectively used, big data has shown to lower the cost of each hire and reduce time-to-hire. In fact, an Accenture study found that 94 percent of talent executives report that they’ve successfully used big data to “moderately or extensively” identify new candidate sources. However, while big data functionality like predictive analytics, algorithms and key word searches can help recruiters avoid going through hundreds of unqualified resumes by hand, they can create blind spots that hinder a recruiter’s ability to identify great candidates. For example, a robot can’t determine what organizational culture a candidate is coming from, be that a large multinational corporation or a boutique firm, and how that impacts their suitability for the role.
2. Maintain "old school" recruiting techniques.
In order to avoid big data blind spots, it is critical for recruiters to continue to practice “old school” recruiting techniques. This means investing time in developing personal relationships with top performers in your industry, networking at industry events and even picking up the phone to invite a highly coveted candidate to lunch or a baseball game. Particularly when hiring senior executives, who have more to lose and often hide their online job searches to avoid detection, it is critical to build and maintain strong personal relationships with key industry leaders. Perhaps most importantly, you can’t call a robot that you have a personal relationship with to get the inside scoop on someone you are thinking of bringing in for an interview. Maintaining human connections is critical when trying to acquire the most talented candidates.
3. Don’t just collect data, learn how to analyze it.
According to IBM, 2.5 quintillion bytes of data are created every day but 90 percent of all data is never analyzed or utilized in business decision processes. As much as 60 percent of this data begins to lose value within milliseconds of being generated. The point is that this is not simply an arms race for what company can gather the most data, rather what company can best use that data to make more intelligent hiring decisions. It is therefore critical to invest in data analysts and you can start by watching big players in the market such as Amazon, SalesForce, Google, Microsoft, IBM and Facebook.
At the end of the day, it is undeniable how much technology is streamlining the recruiting process but at the same time there is a chasm that current technology is unable to fill. By implementing a half machine and half man approach, you can be closer to building your ideal team.