How Unilever Is Using Artificial Intelligence And Machine Learning In Their Recruitment

00:05:29
https://www.youtube.com/watch?v=Efo2ebnES_U

概要

TLDRUnilever, one of the largest consumer goods companies, uses artificial intelligence and machine learning to enhance its recruitment process. With 1.8 million applications yearly, it employs advanced technologies to make hiring more efficient and cost-effective. Particularly for the Future Leaders program, which attracts 250,000 applications, Unilever collaborates with companies like Pymetrics and HireVue. They developed online games that assess candidates' skills and attributes such as aptitude and risk appetite. Successful candidates proceed to AI-driven video interviews, where machine learning evaluates responses using natural language processing and machine vision. This narrows applicants from 250,000 to 3,500, who are then invited to assessment centers for final selection, ultimately choosing 800 recruits. This process not only saves 70,000 interviewing hours but also aims to remove biases, providing candidates with feedback on their application performance.

収穫

  • 🤖 AI improves recruitment efficiency at Unilever.
  • 🔗 Unilever partners with Pymetrics and HireVue for tech solutions.
  • 🕹️ Online games evaluate candidate skills like risk appetite.
  • 🎥 AI-driven video interviews analyze speech and body language.
  • ⌛ 70,000 hours saved in recruiting process at Unilever.
  • 🌐 AI aims to reduce bias in hiring.
  • 📊 Candidates receive feedback on application performance.
  • 🏆 800 final recruits chosen after comprehensive evaluation.
  • 📈 Enhancement in business performance through AI.
  • 🏢 Large scale implementation reflects on hiring process.

タイムライン

  • 00:00:00 - 00:05:29

    Unilever, a leading consumer goods company, aims to enhance their recruitment process through AI and machine learning. With 1.8 million annual job applications, the company seeks efficiency and cost-effectiveness, particularly in their Future Leaders program, which receives 250,000 applications for 800 positions. They collaborated with Pymetrics and HireVue, starting with online games to assess candidates' logical thinking, reasoning, and risk appetite through machine learning algorithms. This is followed by AI-driven online interviews, using natural language processing and machine vision to evaluate candidates. These methods reduce applications from 250,000 to 3,500 for final interviews with recruiters. Contrary to concerns, Unilever asserts that AI minimizes biases and provides feedback to applicants, improving their experience while saving 70,000 hours of processing time and enhancing business outcomes.

マインドマップ

Mind Map

よくある質問

  • How many applications does Unilever receive annually?

    Unilever receives around 1.8 million job applications annually.

  • How many candidates apply for Unilever's future Leaders program?

    About 250,000 candidates apply for the program.

  • What is the role of AI in Unilever’s recruitment?

    AI is used to improve efficiency, reduce bias, and provide feedback in the recruitment process.

  • Which companies did Unilever partner with to enhance recruitment?

    Unilever partnered with Pymetrics and HireVue.

  • What metrics are assessed through Unilever's online games?

    The online games assess aptitude, logical thinking, reasoning, and risk appetite.

  • How does Unilever use machine learning in interviews?

    Machine learning algorithms assess video interviews using speech and body language analysis.

  • How does Unilever ensure unbiased recruitment using AI?

    AI removes potential human biases by using standardized games and interview analysis.

  • What are the benefits for applicants using this AI recruitment process?

    Applicants receive feedback on their performance and reasons for selection or rejection.

  • How much interviewing time does Unilever save using AI?

    Unilever saves around 70,000 hours of interviewing time.

  • What is the final step in Unilever's recruitment process for the leadership program?

    The final step involves interaction with real recruiters at assessment centers.

ビデオをもっと見る

AIを活用したYouTubeの無料動画要約に即アクセス！
字幕
en
オートスクロール:
  • 00:00:00
    how Unilever uses artificial
  • 00:00:02
    intelligence in their recruitment
  • 00:00:04
    process Unilever is one of the world's
  • 00:00:12
    largest consumer goods companies with
  • 00:00:15
    over 400 brands they employ 170,000
  • 00:00:20
    people across lots of different
  • 00:00:23
    countries and they recruit around 30,000
  • 00:00:27
    people a year they actually get 1.8
  • 00:00:31
    million applications for jobs so this is
  • 00:00:35
    a massive operation going through all of
  • 00:00:37
    them coordinating this interviewing
  • 00:00:40
    people across all the locations
  • 00:00:42
    so what Unilever wanted to do is to use
  • 00:00:44
    AI artificial intelligence and machine
  • 00:00:47
    learning to streamline this process and
  • 00:00:49
    make it better and more cost effective
  • 00:00:52
    but better for them and for the people
  • 00:00:55
    applying to their jobs so they tried
  • 00:00:59
    this for their future Leaders program
  • 00:01:01
    and for this they recruit about 800
  • 00:01:06
    people and get around 250,000
  • 00:01:10
    applications so this is again a big job
  • 00:01:13
    going through this they partnered with
  • 00:01:15
    two companies pi metrics and hirevue to
  • 00:01:20
    make this a better process so the first
  • 00:01:23
    thing they designed was in a number of
  • 00:01:26
    online games so when someone replies to
  • 00:01:29
    their job you would play those games
  • 00:01:32
    from your on your own mobile on your
  • 00:01:35
    computer from home and this would assess
  • 00:01:38
    things like your aptitude your logical
  • 00:01:41
    thinking your reasoning but also your
  • 00:01:44
    appetite for risk for example and that
  • 00:01:47
    would be games like the ones you might
  • 00:01:50
    have seen before we have to blow up a
  • 00:01:51
    balloon and you almost like playing
  • 00:01:53
    blackjack we say okay I increase this I
  • 00:01:57
    hold I stick I twist and then some
  • 00:02:00
    people might blow this up really a lot
  • 00:02:02
    we think on this almost bursting let's
  • 00:02:04
    give them a really good idea about your
  • 00:02:05
    risk appetite
  • 00:02:07
    so machines machine learning algorithms
  • 00:02:10
    will then measure various aspects of
  • 00:02:14
    Canada this then leads to a second stage
  • 00:02:18
    where you would do an online interview
  • 00:02:22
    but instead of interviewing being
  • 00:02:24
    interviewed by a person you are being
  • 00:02:26
    interviewed by a machine learning
  • 00:02:28
    algorithm so again you go through a set
  • 00:02:31
    of questions you answer those questions
  • 00:02:34
    again in your own time recording
  • 00:02:36
    yourself on a cell phone or on your
  • 00:02:38
    laptop and again instead of a human
  • 00:02:42
    recruiter analyzing and assessing this
  • 00:02:45
    interview machine learning algorithms
  • 00:02:47
    will do this so they use a combination
  • 00:02:49
    of natural language processing where
  • 00:02:53
    they understand what you're saying as
  • 00:02:55
    well as machine vision where they look
  • 00:02:57
    at body language and all of this give
  • 00:03:00
    them an understanding of the sense of
  • 00:03:02
    purpose for example your business acumen
  • 00:03:06
    and and other aspects and those
  • 00:03:08
    processes narrow the applicator
  • 00:03:11
    applicants down from 250 thousand to
  • 00:03:14
    just three and a half thousand and those
  • 00:03:17
    three and a thousand then get invited to
  • 00:03:19
    assessment centers this is where they
  • 00:03:22
    for the first time get in contact with
  • 00:03:25
    real people real recruiters who then
  • 00:03:28
    make a choice and pick the 800 that will
  • 00:03:32
    ultimately be recruited for their
  • 00:03:35
    leadership program this is a fascinating
  • 00:03:39
    process and sometimes we think this is
  • 00:03:42
    vital to speak to machines I don't trust
  • 00:03:45
    this they might be biased
  • 00:03:47
    actually what Unilever believes is this
  • 00:03:49
    is taking out a lot of potential biases
  • 00:03:52
    because these games are completely
  • 00:03:55
    unbiased the video interviews are
  • 00:03:57
    completely unbiased and the other thing
  • 00:04:00
    is that it will give every individual
  • 00:04:03
    applicant some feedback so we'll then
  • 00:04:06
    assess these are the things that you've
  • 00:04:07
    done well these are the things that
  • 00:04:09
    didn't come across in your interview and
  • 00:04:11
    therefore these are the reasons
  • 00:04:13
    you were not selected so Unilever
  • 00:04:16
    believes that this is actually making it
  • 00:04:17
    a much better experience for all the
  • 00:04:20
    people that apply to their jobs and they
  • 00:04:22
    can learn from this and hopefully
  • 00:04:24
    improve and then become successful and
  • 00:04:27
    future applications from a business
  • 00:04:30
    perspective what this has helped them to
  • 00:04:32
    do is to cut about seventy thousand
  • 00:04:36
    hours of interviewing time and and
  • 00:04:41
    applications processing so a huge cost
  • 00:04:44
    saving and for me a fascinating case
  • 00:04:47
    study of really using leading-edge AI
  • 00:04:50
    and machine learning to not only deliver
  • 00:04:53
    better business business results but
  • 00:04:55
    make the whole process better for
  • 00:04:57
    everyone this is exactly what I do I
  • 00:04:59
    help clients understand what they can
  • 00:05:02
    now do with AI and big data what the
  • 00:05:05
    leading applications are and how they
  • 00:05:07
    can drive real business performance if
  • 00:05:10
    you would like to learn more head to my
  • 00:05:12
    website at Bernhard marcom we can find
  • 00:05:15
    tons of articles white papers and videos
  • 00:05:19
    that will give you a lot more insight
  • 00:05:21
    and real-world case studies and examples
タグ
  • Unilever
  • AI
  • Recruitment
  • Machine Learning
  • Bias Reduction
  • Efficiency
  • Pymetrics
  • HireVue
  • Assessment
  • Feedback