Job description best practices based on hiring data
Sep 17, 2018
Last week several Textios made the trip to Las Vegas for this year’s HR Tech conference. We hit the big stage as one of the most interesting companies in AI for HR Tech. We hosted our ongoing Talent Leadership dinner series. We won the Top Product award for the second year in a row. We even turned our booth into a movie studio and filmed a documentary about what makes good writing!
The great thing about HR Tech is how much of the industry is in the same place at the same time. I got to catch up with so many Textio customers and other talent thought leaders. It was fascinating to hear their take on the event this year.
Here are some themes that a few of them highlighted:
The AI hype cycle is at its peak.
Michael Krupa, a Senior Director in the Office of Inclusion and Collaboration at Cisco, observed that this year there was a big uptick in the number of conversations and solutions focused on AI.
In this climate, it’s hard not to get AI fatigue — with so many solutions focusing on the AI that they contain, it’s hard to understand how they differ. Practitioners would rather learn about the problem a vendor is solving, with real proof points, than hear yet another indistinguishable pitch about AI.
Increasingly, successful solutions are focused on using AI to solve real problems — not just in using the right buzzwords.
Takeaway: It’s time for providers to share the specific, measurable results they promise. The whole point of AI solutions is that they make predictions and promises you can count on. Savvy practitioners are growing weary of the hype and want real results.
Software is great, but great People work always has that human touch.
Felicia Jones, Senior Manager for HR Business Transformation at Capgemini, noted that there are just some parts of the hiring process where machines are simply beside the point. Maybe software can help you comb through a list of qualified applicants, but the best person to make the final hiring decision is, well, a person.
As HR leaders think through the many technologies available to them, this question of where software can support human decision-making comes up a lot. It’s safe to say this is still an open question for many practitioners.
Takeaway: It is simply not a foregone conclusion that anything a person can do, a machine can do better. We think about this a lot at Textio; a document created solely by a machine will never perform as well one created by a person with augmented writing support.
Companies no longer just want people who are great at their work. They want people who are great to work with.
Klaus Unger, Director of HR Technology for the Mayo Institute, shared that even in a tight employment market, talent leaders are placing increasing focus on soft skills. You may be great at your work, but if you’re not able to collaborate successfully with others, you won’t stay in role long.
The last couple of years have seen a major spike in technology solutions focused on assessing these soft skills as a part of role fit. It can feel like everyone on the showroom floor has their own propriety framework for figuring out candidate and employee personality, and for using that framework to predict someone’s success in role.
Takeaway: Most practitioners I spoke with this week agree wholeheartedly about the value of interpersonal skills in someone’s success on the job. They aren’t so sure about the ocean of software solutions that aim to help with the assessment and mapping of people’s personalities to roles.
It was a wonderful set of conversations over a great week. Thanks to everyone who shared the week with Textio in Las Vegas!
