Here at Broadbean we’ve discussed the benefits of big data in detail. From asking what big data actually does and how to properly use big data, we’ve proven how big data affects every part of your company, including talent acquisition. Recently, however, there’s been some confusion about what big data actually is, and how it’s supposed to help businesses and people. Author and Forbes Contributor Howard Baldwin highlighted the confusion in February:
"I’ve especially noted this recently, with this month’s dual cultural lollapaloozas of both the Super Bowl and the Academy Awards. The attempts to predict the outcomes of these events beg the question: what is big data analysis really supposed to achieve? Can it really predict discrete outcomes? Or is it really designed to identify patterns and potential outcomes?” — Howard Baldwin (@HowardBaldwin), Forbes
Big data has enormous potential for growth, but Baldwin’s point speaks to how many still see big data as a deluge of numbers they don’t understand, and thus couldn’t benefit from. But from where we sit, the number-crunching of data is a means to an end. Much more interesting than the how of big data is the what, the results. What can big data help you accomplish? How can it help your recruiting and talent management? And what skills do you need to have in place to leverage the insights from data analysis on this large scale?
Data and Business, Coming Together
The numbers on big data in recent years have been promising. The industry has quadrupled in size in the last few years, going from a $7 billion to $29 billion from 2011 to 2014. If you’re in the business of gathering the data necessary to make the big data decisions, you’re making big bank. But what do all these numbers lead to? How do businesses make decisions based on this data? T-Mobile provides with an excellent example of how to use big data to please your customers and make headway in your business practices:
"T-Mobile looked at how their subscribers were connected together—who called who, basically—and attempted to figure out each caller’s effective level of influencerelative to other callers... T-Mobile also scrutinized data outside of their billing database, looking at dropped calls and other "non-billable" indicators of customer annoyance. Then they pulled all this together and began focusing efforts on proactively helping out higher-influencing customers—like offering a femtocell to a high-influencing customer who has moved to a new area with bad service to prevent that customer from leaving T-Mobile and taking their circle with them."
T-Mobile used big data to identify trends in their customer base and found trends in how people left their service, which allowed them to change their service to better serve them. These are kinds of real results numbers can give us, and big data can facilitate those changes.
Better Recruiting Through Number Knowledge
How can recruiters glean similar insights from big data? Use the same analytics to identify how candidates are applying, your company’s employer demographic (what kind of person is most likely to apply to your company?), and use those trends to up your recruiting prowess. Big data can even help candidates find their best career option. Companies could use this same data to filter candidates by their career aptitudes, and help better roles their current employees could fill. All of this from crunching a bunch of numbers. Data can affect tool usage, employee referrals, social adoption, recruitment and job board spend and career site changes.
If you don’t think your company needs these sorts of insights, just ask your HR staff. We built BDAS (Big Data Analytics Suite) for the 65% of managers who say a lack of data is one of their biggest issues. Despite how crucial this lack of data is for HR, only 14% of departments use analytics to help them find the data they need to make better decisions. We’re helping bridge that gap by providing the tools to gather data about your company, find the trends in hiring and work untraceable by human knowledge, and putting it all together in ways you can read.