- When done right, adopting AI in HR should increase collaboration among teams.
- Identifying a specific business use case — not solving for every problem — can streamline AI implementation.
- Gaining alignment from the entire HR team and adopting new mindsets is a must for success.
The key to getting workers comfortable with AI? Integrate it into daily business.
That’s the advice Eva Edelmueller, Head of Group Talent Attraction and Talent Management at MM Group, shared in the latest episode of The New Talent Code.
As a consumer packaging leader based in Europe, MM Group’s HR leaders knew they wanted to join the ranks of those testing talent intelligence but weren’t sure where to start — until the perfect opportunity emerged.
When MM Group acquired Essentra Packaging, which included onboarding 3,500 new employees, HR needed a more agile way to understand the needs of these new workers, so they developed a strategy for a successful integration. Talent leaders jumped right in with AI.
With AI-native talent intelligence, the company was able to integrate more than 20 work sites across 11 countries into its talent strategy.
Edelmueller shares how MM Group did it all while improving hiring times and finding more women candidates. Read on for essential advice from this talent leader.
Related content: Eva Edelmueller, Head of Group Talent Attraction and Talent Management at MM Group, talks about her organization’s success with a global roll out of talent intelligence.
Identify a specific business use case
To start, Edelmueller said her team knew they needed a strong business use case. They were lucky when one landed in their laps — onboarding colleagues from a newly acquired company.
“This was a really specific business case because when we planned to implement the new HR [SAP] SuccessFactors and Eightfold in recruiting, we didn’t yet know that we would acquire a new part of a company,” Edelmueller said. “The setup and objectives were actually different than it turned out in the end.”
The acquisition scaled the project to more sites and languages than originally planned. It also put Edelmueller and her team on a tight, fixed deadline.
But it was a challenge they were ready to tackle that led to some key learnings along the way.
Top learnings:
- People are essential to the process.
- Design a system that is useful and simple.
- Understand your minimum proposition value.
“You can have the best systems, but the system is worth nothing if you do not have people who operate the systems and the systems need to work for the people,” Edelmueller said.
Edelmueller added that it was key for the system and process to be useful and simple to get people to use it. If it made employees’ daily work lives more complicated, she said she knew the adoption rate would be low.
Finally, understanding the minimum needs required to get the system launched was essential to meeting the strict deadline.
“Done is better than perfect,” Edelmueller said. “This is also something we learned because the systems provide so many options, so many possibilities, but you need to focus on the basics in the end. If the recruitment process, the core recruitment process, is not working — if the colleagues cannot operate and use the system in a proper way — in the end, everything is not good.”
Related content: Edelmueller shares how managers can support their employees through use of talent intelligence at Cultivate Europe ’24.
Align on global practices
Starting from a place where everyone agreed on what the “big picture” was is critical for launching AI-native talent intelligence at the scale required.
That began with the HR team. Instead of repeating what they’d done, HR asked how they saw themselves fitting into the hiring process in an ideal world — then they made it happen.
“We want to be talent advisers to the candidates and hiring managers, meaning we operate on an eye level, give feedback, and provide a service,” Edelmueller said. “And if you have that understanding, the process follows by itself.”
MM Group talent leaders also allowed space for growth with defining processes. Edelmueller said that some countries launched with only 70% of processes defined and allowed for the rest to be completed as they moved forward.
They also reviewed whether their hiring practices aligned with the site’s local practices and the types of workers needed.
“Does having five interview rounds with a blue-collar worker make sense?” Edelmueller said. “For me, it was important that people understand why we do that, what is their role, and how they should act as the recruiter or talent adviser.”
Increasing cross-functional collaboration
Many of the changes MM Group made while implementing talent intelligence has helped foster a culture of collaboration.
“The topic of AI itself increased the collaboration among legal, IT, and HR,” Edelmueller said. “We’re in ongoing conversations about how we handle [things], what is our standard, and what we define [as] standards.”
It has also invited everyone into the conversation about how to use AI in the best way possible without creating a formal council or work team.
“I think this is enriching because everyone wants to have the systems because we see the value in them,” Edelmueller said. “This will be the future.”
How to update policies
The final area MM Group addressed with AI were policies — those affecting current employees and how they communicate privacy rights to candidates.
Edelmueller said MM Group’s HR teams already regularly updated their policies around tech. However, more action was needed in addition to putting it in writing.
“You need to talk about it,” she said. “If you just update and make the materials available once a year, OK, fine. You will fulfill some requirements, but the people who joined the company [since the update] do not know because you just talk about it once a year. That is not enough.”
To solve for that, MM Group introduced bi-weekly talent attraction calls dedicated to talking about HR systems. She likened it to holding office hours — a time to answer questions from recruiters, refresh training, and address challenges.
MM Group also started asking candidates for feedback and are working to finesse how they communicate their use of AI on their site.
“We try to be really transparent, so we say we work with AI in recruitment, but we also say that people decisions are always taken by the human,” Edelmueller said.
Best practical advice for implementing AI
Like all guests on The New Talent Code, Edelmueller closed out the episode by sharing her best practical advice for other HR professionals considering AI.
“Just try it,” she said. “It will not work right from the beginning for everybody, but it will work for this person and that person. And then with word of mouth and a bit of support, they will just try it and learn it.”
Listen to the full episode of The New Talent Code with Eva Edelmueller on our website or wherever you listen to podcasts.
