Big data. We’ve all heard about it. And, I’m here to say don’t just hear about it. Immerse yourself in it. HR should be all in on big data for numerous reasons. But here are just 3:
- Better results
- Time savings
- And, most importantly, what I’m going to focus on today, because of what’s not even happened yet
Big data in its simplest definition refers to things that can be done at a large scale that cannot be done at a smaller scale. This allows companies, governments, and others to extract new meaning, insights, and value that can fundamentally change the way we understand things we thought we understood.
Big data is here. Many of use the output of big data and machine learning everyday but don’t realize it. No. Really. Everyday.
Big data has shown to be an invaluable tool in fields with extremely complex issues. For example big data and the computers that analyze it are handling 33,000 trades per second on the NYSE where sequence and accuracy are extremely important. And, when you start to comprehend the amount of data that we have today, and the machines available to store, process, and analyze it – it means that the data is going to continue to get bigger and bigger. In other words, data breeds more data when you are analyzing it. Your findings, insights, and values become more data to be analyzed.
We have seen big data play a role in HR already. Most of what I’ve read, though, about the use of big data analysis in HR has to do with one of two areas.
- Looking at information and analyzing past events for useful insights on how to make future sourcing and hiring decisions.
- Determining probable future outcomes of human capital decisions.
These primarily have to do with assessment tools, and where to place ads based on historical data. More recently, though, we’ve seen a shift to a Google style of sourcing which is encouraging.
Now, what’s around the corner? Let your mind go for a moment and imagine what the possibilities are.
In my nearly eight years of speaking with HR practitioners I’ve found there are two distinct groups. One is made up of those that want to stick with what they know. It’s comfortable. It’s produced “good enough” results. And, the second group is made up of early adopters always looking for what’s new on the market. This group is always willing to not only hear what comes their way, but also does their research on trends and the best new tools out there.
My suggestion on big data? Go all in. Take it a step further. Don’t just look for what’s new in the marketplace. Don’t just jump on something that says the newest catch-word or phrase. Look for what companies are not just looking and talking about the here and now, but what’s a year, 2, or 5 down the road. Imagine the competitive advantage you’ll have.
Here are some things I’ve heard cutting edge techies in the HR area talking about.
What if there was a way to know the exact number of candidates you needed in your funnel for each unique requisition to give yourself the best opportunity to make a hire?
Let’s assume the # is 37. In other words, statistical probability based on the data collected over years and year says if you don’t have 37 candidates in your funnel, you run the risk of not being able to hire the best candidate available at that time.
Then, what if there was a system that could tell you based on these applicants work history, experience, salary history, and the commute required for the job (combined with the compensation package you’re offering) which candidates were most likely to accept? Instead of reading resumes and shooting from the hip, this system could stack rank the candidates and tell you to ignore the top 9 and the bottom 15, and focus on 10 to 14. Again, the data collected for years and years can tell you that statistically you can ignore all but 5 of these candidates, first. The system isn’t saying these are the best candidates, but it’s saying these are the candidates most likely to accept.
How much time and energy would this save you and your teams?
Let’s take what we already have. Systems based on big data and machine learning that can tell you where to post your job ads for optimal performance and cost savings. Sourcing tools that can aggregate from all over the web, analyze, and present optimal candidates for you from one intuitive interface. And, assessment tools that can help your organization predict one’s performance.
Now you could have tools that take it even further and tell you when to start the screening process and where to focus your energy right off the bat.
What’s next in big data in HR could be beyond comprehension. My suggestion for the early adopters is don’t just be satisfied with what is. Ask what’s next. Get acquainted with as much as you can in this exploding arena. Find the companies that are talking about what’s coming, not just what they have now. I say this because you can ride this big data wave for a long, long time.