Human Resources secured an exclusive interview with Ross Sparkman, head of strategic workforce planning at Facebook, during his recent whirlwind visit to Hong Kong to deliver the keynote address at Talent Management Asia. He shares his thought-provoking insights in this extract from the interview – soon to be published in full.
- How can HR use data analytics to identify talent?
Where data analytics can really help in the identification of talent is to capture nuances or characteristics or patterns in large sets of data that indicate certain types of tendencies or characteristics that might not be easy to pick up on through the human eye.
So it’s really about finding patterns and key aspects that might not be as intuitive to us as human beings. So I wouldn’t recommend just using data to identify talent, but it’s a great way to use as a filter or a starting point in identifying talent.
- More broadly, how can data analytics be effectively employed in strategic workforce planning?
When I think about strategic workforce planning there are two or three elements. The first is understanding the current distribution of employee skills, location – what’s happening in the workforce today.
The second component is trying to understand what will happen in the future, or what could happen in the future or what should happen in the future. And so, how do you understand what’s happening today and what will happen tomorrow?
Again, it’s a combination of using analytics – data – and intuition. It’s the data piece that makes the planning component strategic. If we didn’t use data it would be fairly arbitrary and it wouldn’t be that strategic. The data provides the backbone for making more strategic decisions.
- One of China’s biggest online recruitment firms, Zhaopin, uses big data and powerful algorithms to match a candidate with a role. Do you think such an approach can lead to effective job matching?
There are certain things that machines and AI and machine learning can do very well, and that’s identifying patterns. Where there are some challenges though is in more of the subtleties around the things that humans do well, which is using judgment, flexibility and using intuition when it’s needed.
Again, it’s useful as a filter, but I think it would be dangerous to use these types of algorithms without the context behind them that people and leaders can identify.
If we’re thinking about the types of skills that will be around in the future, then a lot of those skills are something machines (can’t measure). Skills such as grit, flexibility and adaptability. Those are some of the core components of what is going to be required in the future and I don’t think we’re at a point where machines can say, ‘Hey, that person has grit. That person has a learning mindset’.
Machines will be good at understanding the qualifications and skills on the résumé, but there will still be challenges around these nuances that human beings are better at.
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