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So many in fact, that the recruitment volumes often exceed 5.000 applicants every month. A favorable position, no doubt, but it does present a few complications:
An employer brand of Hemfrid’s caliber takes years of hard work to obtain and is a competitive advantage in its truest sense. To retain this position, the majority of applicants interacting with the brand must take home a good impression. Traditionally, this means scaling up the recruitment team to keep up with the application influx and make sure every interaction is personal and respectful.
Large application volumes come at a cost: a massive screening process.
A broad intake of candidates is almost always a good thing as the odds of finding the perfect candidate increases. But when screening is done manually, a compromise is needed to balance benefits with costs.
Knock-out questions are an alternative often used in high-volume recruiting. But this is a very blunt tool that takes little consideration to peripheral factors which limit the screening capacity drastically.
Spending hours on end reading resumes and cover letters can have an impact on overall objectivity and introduce unconscious bias. Additionally, there’s no automated way of measuring important soft skills.
The idea behind Hubert is simple; leverage advanced AI to conduct interviews with all applicants and find out who the top candidates are — automatically.
Hubert’s involvement in the process triggers as soon as the application arrives in Hemfrid’s Applicant Tracking System, TeamTailor. The candidate receives an invitation to complete the next step in the recruitment process and initiate their interview with Hubert. When starting the conversation with Hubert, the candidate decides whether the interview should take place in English or Swedish.
The candidate completes a structured interview with Hubert measuring both hard- and soft skills, motivation, previous experience as well as resolving important questions such as working inconvenient hours, preferred start date, and most important: relevant competencies.
Hubert has been trained to ask competency-based questions and look for STAR (Situation, Task, Action Result)-responses to evaluate how well the candidate's competencies overlap those needed to perform well in the position.
Depending on the position, the next step is a case exercise that assesses the candidate’s ability to handle a realistic job scenario.
All responses are then automatically analyzed and compared to the job requirements in order to form a matching score.
Working closely with Hemfrid and the remarkable people who run the day-to-day recruitment operations gives insight into a culture where employer responsibility, professionalism, and intense focus on inclusion meet ambitious growth targets.
The pilot was set up to target cleaners in the Stockholm area, a position that regularly receives application volumes in the thousands in a typical month. Automating these kinds of positions was quickly identified as a key challenge in Hemfrid’s quest to further digitize the recruitment process.
Instead of scaling up the recruiting team to lower the number of candidates per recruiter, Hemfrid leveraged Hubert’s AI as a support to the existing recruiting team. Now, every candidate has a chance to make themselves heard and stand out from the crowd in a personalized interview with Hubert. About 70% of all applicants completed the interview with Hubert.
Large application volumes are no longer a problem after Hubert was deployed. Hemfrid has fully opened the applicant floodgates, but now they can use their time even more wisely by focusing on the highest qualified candidates at all times.
With Hubert, Hemfrid could add more weight to the individual drive and motivation than the candidate's formal prerequisites. By combining a wide spectrum of factors, the candidates with the highest probability of succeeding are automatically floated to the surface. The prediction accuracy was close to spot on and even exceeded the expectations.
”For us, it was very important to give all candidates a fair process free of bias and prejudice. All candidates are asked the same questions, in the same order, and are rated according to the exact same criteria. During the pilot, we have also carefully studied key figures such as C-NPS to maintain a high candidate experience, which has been shown to have the same good results as before We were amazed by how well Hubert handled the interviews. Continuing and expanding our partnership with Hubert was a no-brainer given the results.”
After the initial pilot, Hemfrid eagerly scaled up Hubert use-cases by adding new interviews for window cleaners and movers as well as scaling out the interviews to more locations.
Introducing Hubert’s AI screening into Hemfrid’s TA team has been challenging, fun, and very educational. And to top it off, Hubert has helped to personalize the candidate screening process by ensuring everyone has a fair chance which is exactly what we strive to achieve.