Questioning "Big Data" in Talent Acquisition? #BigDataHR

This week on Blogging4Jobs, we are focusing on the theme Big Data sponsored by Jibe. Jibe provides cloud-based recruiting technology solutions that enable talent acquisition teams to strategically identify, attract and engage candidates. Join us April 10th 2014 at 3pm to talk Big Data on Twitter using the hashtag #BigDataHR and join our webinar, “What’s the Big Deal with Big Data in HR & Recruiting” on April 17th at 11a EST. Follow the week by bookmarking us

Big Data is a big deal and is fascinating: the amount of data created in 2012 was 2.8 zettabytes and this number will double again by 2015. However, to have a clear idea of what big data is about, you may want to read the very good Wikipedia article on the topic. It reminds us that “Big Data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process the data within a tolerable elapsed time.” Are we really faced with this problem in HR? Maybe not… and certainly not in talent acquisition, which is the area I focus on.

HR Data today — not that big after all…

Even if you have 10,000 job openings and get 100 candidates per job opening, we are only speaking of data related to one million candidates. If you are adding to the mix candidates you had over the last few years, you might be dealing with 5 million candidates. This is not that much. Capturing, curating or analyzing such data set doesn’t require rocket scientists. It’s not because the HR systems that you use rarely do a good job at it that you should jump to the conclusion that you have to buy expensive tools… You may just be adding a Rube Goldberg machine to a kludge… Also, anyway, the best analytics tools applied to irrelevant or mediocre data will give you mediocre results.

Yet, the marketing popularity of big data in HR has the positive effect side of urging people to realize their real and basic data problem: companies have a lot of data, yet very little information because this data is not sufficient or not actionable. The big data hype in HR should be the opportunity to keep your feet firmly on the ground, revisit the simple notion of business intelligence and start to think about to what it should be applied. Your need is not about statistically inferring laws from large data sets but about talent analytics and about leveraging descriptive statistics to measure actions, identify trends and define business goals.

Datafication of Talent Acquisition

Let’s not put the cart before the horse. How much data do you have in the first place? How do you to datafy talent acquisition in the first place? Here are two important areas that you should look at regarding 1) General SEO statistics and 2) Candidates’ behavior and activities.

General SEO Statistics

Here a select of typical information provided by DirectEmployers to its members:

  • Pages Indexed: Amount of unique pages that Google (or a search engine) sees from your site. The amount of unique pages that their bots crawl is the pages indexed for that site.
  • Impressions: How many times a .JOBS microsite was presented to a job seeker on Google, could be loosely defined as how many times did you rank well enough in a Google search to be seen.
  • Visits: How many people visited this site, if a person visits multiple times it counts towards the total
  • Conversions: How many people click apply on a job, click your talent network button, or click on one of your social media links at the bottom of the microsites.

In the same way, it’s important for you to identify your top referral sources, your best keywords, or candidates’ geographies.

Candidates’ Behavior and Activities

Talent acquisition is all about attracting, managing and pampering passive candidates. Here is a short list of what you should be measuring today:

  • Opt-ins (application driven/not application driven)
  • Drop-off and Opt-outs of your talent pools
  • Profile completion, additions, updates
  • Attendance to your webinars and events
  • Sharing of your job posts, your events, or your blog posts by passive candidates
  • Job matching results when you match a job against your talent pool
  • Follow up on your job and event notifications or on your mailings
  • Activity level of individual candidates or sets of candidates
  • Sign up to your circles
  • Etc…

In short, you can track a few hundred data point and actions about candidates, which gives you lots of combinations, of course. Yet, none of this is complicated when you use products that give you access to this data. You do not need to be a data geek, you just need to define your business objectives and look at the data to see if what you do is efficient. For example, does your talent pool provide you with enough candidates to fill the positions that planned by your company? If not, what can you do? Enhance your content marketing to attract more people? Change the title of your email campaigns to make it sound less salesy? Adjust your job description? Open up to different profiles? Be less dogmatic about existing skill sets and more open to identifying potential in candidates?

Of Course, No Datafication… if You Don’t Have Free Access to Your Data

Datafying human resources is not difficult and can be exciting. It’s what marketing started three decades ago. However the ability to identify the metrics and measures that will define success or efficiency and will enable you to define your continuous improvement strategy is predicated upon one single thing: the ability for you to have the data.

The number 1 problem in HR today is not big data, because it’s not big. It’s the ability for companies to have easy access to their own data as they wish, the way they want and as often as they want. True data analysis is predicated upon free open APIs. If you are serious about the datafication of your recruiting efforts, this should be your #1 demand from any vendor! The HR industry is one of the latest bastions of archaism where vendors lock clients by locking their data and forcing them into exorbitant integration/extraction fees each time they want to do something that might be out of their control.

So, free your data first from your vendors’ grip if you want the freedom to analyze what they mean and think of the ways you could improve your processes! Beware the Goldberg machines!

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Marylene Delbourg Delphis

Marylene Delbourg-Delphis (@mddelphis) is the co-founder and CEO of TalentCircles. One of the first European women to found a tech company in the Silicon Valley, she launched a bestselling relational database (4th Dimension) at ACIUS, co-founded with Guy Kawasaki. She later became the CEO of Exemplary Software, a lean supply chain management system (acquired by Persistent Systems) and Brixlogic, a platform for the native implementation of XML Schemas (acquired by Diebold). Throughout her career, Marylene has assisted about thirty young companies as a shadow CEO, board member, or investor. She has hired a lot of employees (and fired a few too!).


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