I recently tweeted an article relating to Gartner Hype Cycle, When buzz words and phrases enter the tech industry lexicon they become overused, misunderstood and over hyped which can result in a typical cycle.
The buzz phrase in question was "Big Data".
I received an interesting response from my community, with many asking what Big Data actually means and how will it help them.
Most businesses and recruiters set their strategy based on reflecting on the success or failure of their past strategy, normally over months / years. For recruitment consultants, many will specialise in a sector based on gut feel or where they have been successful. There has rarely been time in the recruitment cycle to review real time analytics (real time = now, not last month.)
At its simplest, Big Data is a tool for making more informed decisions with guidance. Using aggregated data sets (for example all advertised jobs and all applicant data) it allows businesses and individuals to review and reflect on what is happening right now through spotting trends and patterns.
How are recruiters currently using big data?
Twitter users can use the reports that tell them when it is best to tweet for maximum engagement. For example, according to equest.com, the best day to tweet jobs in USA is a Sunday (ie. the best day to get applications to your job is a Sunday). Consider though, that this is generalised information - in fact, each Twitter user will have their own dataset and systems like SocialBro will tell you when your followers are most likely to be online, and this data may help you decide on a tactic.
Another great example of Big Data at work is the launch of LinkedIn University Pages. Take 225 million profiles (Aug 2013) and analyse 2 data sets; University courses and career history. Now analyse the likelihood of someone's career based on the course they attended and where they attended it.
What trends and patterns can be identified between these 2 sets of data?
The assumption is that by attending course X at university Y will most likely provide a student with a number of most likely outcomes for Career Z.
What use is this?
- For the A-level student about to choose their Uni and course, this could help them identify the career they want.
- For the Universities, this is clearly great marketing collateral for the best courses, as well as their Alumni.
- For graduate recruitment companies, it might show the most likely candidates to network with, even before they're career has started.
- As a recruiter, how could you use that information? Don't just focus on the graduates, focus on where they're likely to end up, and then track back to begin your talent pooling / community building.
Other ways Big Data can Help Recruiters
I can think of the following ways that Big Data can help recruiters in their day to day roles:
- What job boards should I advertise on that will provide the best candidates based on job role or industry?
- Which LinkedIn Groups will provide me with the best engagement for my market sector?
- What are the growth industry sectors and which ones are declining?
- What companies are growing and require recruitment services?
- Which competitors are growing and what sectors they work in?
- What activities do I do, that provide me with the best outcomes?
But the big question is: does the tech exist to help you see through this data to the answer? I'm not convinced it does yet (not easily, anyway).
Big Data is at its Peak of Inflated Expectations
In relation to the Gartner Hype Cycle, I would suggest that we are heading towards the "Peak of Inflated Expectations" relating to Big Data, there's lots of talk and research projects on the go with some encouraging and useful results.
There are also a number of limitations that need to be overcome, before we hit the Slope of Enlightenment or cruise along the Plateau of Productivity, but the signs are encouraging that Big Data just might fulfil on its hype in providing recruiters with the tools to help them make more informed decisions.
What other questions would help you to make better and more informed decisions? What's your expectation of Big Data? What should it be able to do for you to make your life easier - isn't that what tech's about?
Thanks to the RecTecHub for publishing this blog.