Is recruitment
industry ripe for
disruption?
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66% of Millennials
anticipate to leave their
jobs by 2020
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6
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BAD HIRE
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£2.2bn
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Crazy AI
Can I help?
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SOURCING
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SOURCING
Identifying the right pool of candidates
Shortlisting the best candidates
Scanning the social media
Engaging and screening candidates
Identifying candidates who are 30% more likely
to change jobs within 90 days
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SOURCING
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SOURCING
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SAVING TIME
INCREASING
ENGAGEMENT
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GOOD HIRE
Happy employees are 12% more
productive
Highly engagement business units are
21% more profitable than their peers
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BAD HIRE
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PROBLEM
‘I don’t like the company culture’
one of the top reasons of leaving work
89%
of the time employees fail due to their poor
attitude rather than skill, including:
• Coachability
• Motivation
• Temperament
(Murphy, 2012)
(Korn Ferry, 2017).
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BIAS
=
DEATH FOR DIVERSITY
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How do we find
the right candidate?
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In hiring, algorithms beat
instinct…
By 25% on average!
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52% of Talent Acquisition leaders
say the hardest part of recruitment
is screening candidates from a
large applicant pool
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• Quality of hire measurement
• Structured interviews
• Diversity and inclusion-friendly
• Quick and data-driven decision
making
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How can I add value to AI
growth?
Access to data
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£2.2bn
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Theory of planned behaviour
The performance of a behaviour is
determined by the individual’s intention to
engage in it
Martin Fishbein
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Should I use AI?
Companies that use AI are 30% more
profitable compared to those that
don’t use these tools.
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Creating a platform that helps businesses to build a
passionate workforce by leverage technology and data
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X
References
Anon, (2018). [online] Available at: http://www.hrreview.co.uk/hr-news/recruitment/it-costs-over-30k-
to-replace-a-staff-member/50677 [Accessed 22 Mar. 2018].
Baldoni, J., 2013. Employee Engagement Does More than Boost Productivity. [Online]
Available at: https://hbr.org/2013/07/employee-engagement-does-more
[Accessed 04 08 2017].
Cable, D. & Judge, T., 1997. Interviewers’ perceptions of person–organization fit and organizational
selection decisions. Journal of Applied Psychology, 82(4), pp. 546-561.
Casserly, M., 2012. Majority Of Americans Would Rather Fire their Boss Than Get A Raise. [Online]
Available at: https://www.forbes.com/sites/meghancasserly/2012/10/17/majority-of-americans-
would-rather-fire-their-boss-than-get-a-raise/#5dd475176610
[Accessed 09 06 2017].
“In hiring, Algorithms beat instinct.” Harvard Business Review, May 2014, Nathan Kuncel, Deniz
Ones, and David Klieger.
Chatman, J. A., Caldwell, D. F., O'Reilly, C. A. & Doerr, B., 2014. Parsing organizational culture:
How the norm for adaptability influences the relationship between culture consensus and financial

How AI can help the recruitment industry

Editor's Notes

  • #2 A startup set up by Michal Wisniewski straight after finishing the University in October 2018. The essence of the business is based on research conducted by Michal when he was at the University. Since October Michal managed to build a core team of 2 people, work with multiple web developers, enroll on Accelerate Me accelerator and Innovation Optimiser hosted by UMIP. Macawly is currently a revenue generating business looking for further investment to support its web development
  • #3 A startup set up by Michal Wisniewski straight after finishing the University in October 2018. The essence of the business is based on research conducted by Michal when he was at the University. Since October Michal managed to build a core team of 2 people, work with multiple web developers, enroll on Accelerate Me accelerator and Innovation Optimiser hosted by UMIP. Macawly is currently a revenue generating business looking for further investment to support its web development
  • #6 Currently we are experiencing a generartional change
  • #21 Say no to candidates with no validf reason whatsoever
  • #26 Natural language processing
  • #29 There is so much psychology theory and various methods of scientific recruitment whcihc were never implemented in the real-world. Now we have the tools (AI) to integrte it and compare the results using big data
  • #31 shorter
  • #32 shorter