It’s Not Just AI That Matters in Recruiting, It’s the Complex List of Skills That Makes It Work

The use of AI is becoming de rigueur in recruiting technology. I love the fact that it’s there, but it’s hard to understand and hard to assess how well it’s working. I was taken with the approach of Kiev-based FourHires which, along with the requisite AI, is stressing the importance of their skills taxonomy for IT jobs (7,000 skills) in order to make precise recommendations when shortlisting candidates.

Taxonomies are an old technology that remain useful. Unlike AI, there is nothing obscure about a taxonomy; it’s easy to see and easy to understand. Easy to understand doesn’t mean easy to build; when I was writing Lead the Work with John Boudreau and Ravin Jesuthasan we spoke with IBM leaders and they discussed how hard they’d been working on building and updating skills taxonomies.  Taxonomies are not sexy and not simple, that means their value may be underappreciated.

As you might expect, put together AI and a comprehensive taxonomy and you’ve got a system capable of creating a good short list of candidates. From a recruiter’s point of view, getting that shortlist may seem to be the task that they were meant to accomplish. However, getting a good short list is only half the battle. The other half is convincing the hiring manager that you have the best possible short-list so that they don’t send you back on a futile hunt for someone better.

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A good shortlisting technology needs to provide not just a good shortlist, but a shortlist in a form that helps convince the hiring manager that the right talent is on the list.  So another tip of the hat to FourHires for emphasizing this part of the process; their report about the shortlisted candidates is aimed  at showing managers the quality of the shortlist.

What is interesting?

  • Everyone agrees that keyword searches are painful, but recruiters still rely on them enormously. Will they ever go away?
  • Having operations in Kiev has gone from sounding strange to being a bit of a secret weapon because of the quantity and caliber of IT talent there.

What is really important?

  • I’m intrigued with the idea that these HR tech vendors are not just selling software, but are selling the service of continually keeping the “smarts” of the software up-to-date. In the case of FourHires, they’ve got specialists to continually update the taxonomy; that’s something that is really hard for the average HR department to do on its own. It’s not just “software-as-a-service”, it’s “constantly-getting-smarter-as-a-service.”
  • The ability to convince the hiring manager you are doing a great job is almost as important as doing a great job; it’s nice to see that front and center in talent acquisition software.

David Creelman, CEO of Creelman Research, is a globally recognized thinker on people analytics and talent management. Some of his more interesting projects included:

  • Conducted workshops around the world on the practical aspects of people analytics
  • Took business leaders from Japan’s Recruit Co. on a tour of US tech companies (Recruit eventually bought for $1 billion)
  • Studied the relationship between Boards and HR (won Walker Award)
  • Spoke at the World Bank in Paris on HR reporting
  • Co-authored Lead the Work: Navigating a world beyond employment with John Boudreau and Ravin Jesuthasan. The book was endorsed by the CHROs of IBM, LinkedIn and Starbucks.
  • Worked with Dr. Wanda Wallace on “Leading when you are not the expert” which topped the “Most Popular List” on the Harvard Business Review’s blog.
  • Worked with Dr. Henry Mintzberg on peer coaching, David’s learning modules are among the most popular topics.

Currently David is helping organizations to get on-track with people analytics.

This work led to him being made a Fellow for the Centre of Evidence-based Management (Netherlands) for his contributions to the field.



1 Comment on “It’s Not Just AI That Matters in Recruiting, It’s the Complex List of Skills That Makes It Work

  1. Great article. We use taxonomies (among other techniques) at to match employees to internal roles and projects. But taxonomies are AI too. They’re a form of AI called “knowledge representation”. Google’s Knowledge Graph, which is its taxonomy, powers a lot of its AI. Deep learning and machine learning are the hot new AI techniques, but there are many others that have been in use for many years.

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