This document summarizes a meetup event focused on HR technology assessments. It included discussions on:
1. An overview of different types of assessments including structured interviews, cognitive/psychometric tests, skills tests, and team fit. Examples of companies providing each type were presented.
2. A deep dive on cognitive/psychometric assessments, including examples of games and skills being assessed by companies like Arctic Shores and Pymetrics.
3. Observations that the right assessment depends on objectives, and that there is significant innovation in data, user experience, process, and integrating assessments into jobs platforms and learning. Performance data was noted as important for understanding where assessments are most effective.
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16. Assessment:
Think of some recruitment use cases
Graduate
Hiring
High Volume
Hiring
Developer
16
Call Centres
Retail Staff
Cabin Crew
Marketing
Sales
Finance
Executive
Manager
17. Assessment:
Think of some other use cases
Wellness
Team
Development
Performance
Management
17
Promotion
Transfer
Move function
Internal move
Coaching
Diagnostic
18. Trends driving new assessment
approaches
18
Changes in
global talent
market
Innovation in
Assessment
Metric-
driven HR
New talent pools
Diversity needs
Speed
People Analytics
ROI
Productivity
VC money
AI
Phones, Video
Source: Ian Newcombe (abridged)
19. Assessment:
Money pouring into HRTech including
assessment is really fueling pace of change.
$1.3bn YTD .
Source: Larocque 19
Quarterly Total HR Tech investment (2017-18)
20. Assessment:
The right assessment depends on
objective
Positive candidate
experience
Minimise
candidate effort
Promote diversity
Drive process
efficiency
Reduce recruiter
headcount
Hire high
performers
Reduce employee
attrition
Optimise
reporting
analytics
.. and more
Experience Type Efficiency
Source: Ian Newcombe
Outcome
Higher sales
Objectives for Assessment
20
21. Lets look at some Assessment solutions
This is not a comprehensive list at all
Chosen to illustrate what is out there
21
50. Assessment: Deep dive observation
1. The right assessment depends on
objective
Positive candidate
experience
Minimise
candidate effort
Promote diversity
Drive process
efficiency
Reduce recruiter
headcount
Hire high
performers
Reduce employee
attrition
Optimise
reporting
analytics
.. and more
Experience Type Efficiency
Source: Ian Newcombe
Outcome
Higher sales
Objectives for Assessment
50
51. Assessment: Deep dive observation
2. Huge amounts of innovation happening
which has to be a good thing
New
Data
Innovations in
User
experience
Process
On your mobile
Great UX
Games
Response times
Voice
AI
Rapid turnaround
Integrate via APIs
52. Assessment: Deep Dive observations
3. Assessment is integrating into jobs
platforms
52
Debut Indeed
53. Assessment: Deep Dive observations
4. Assessment is emerging in learning
platforms
53
Hacker Rank Piazza
54. Assessment: Deep dive observations
5. Performance data is the ingredient we need
more of
When and where does Assessment work?
Employees Employers
Good match to skills?
Good match to manager?
Good match to culture?
Productive?
Happy?
Better Performance?
More productive?
Lower attrition?
More efficient?
People Analytics
Challenges:
Data collection
Over time
Subjective measures
57. ThriveMap helps us to hire for cultural fit based on
real insight rather than a gut feeling. It makes
culture a tangible rather than nebulous concept
Jo Steel, HR & People Director
Belron International
Web: www.thrivemap.io
Email: nathan@thrivemap.io
Telephone: +44(0)207 193
8668
Our clients include
96. There is huge curiosity about where this
is all heading
Help me make sense of this
96
It all sounds a bit Big Brother
Is my job safe?
Really transforming things
98. The Perfect Job Match
A big improvement from employee point of
view...
Interests Boss CultureTeam Money
Skills Quick Efficient Learning Progression
98
Employee : Perfect from their point of view
A fit with what they like for
99. The Perfect Job Match
A big improvement from employer point of
view
High
performing
Cheaper Faster
99
Employer: More than 10x better than today
A fit with what they like for
100. A Perfect Match requires a lot of things to
be understood about employee and
employer
Interests
Boss CompanyTeam
Money
SkillsPersonality
Candidate
Commute
Intelligence
Preferences:
Performance
About the people and company:
Role
A lot of data.Culture
Environmen
t
The company:
106. Data
Challenges in at least four foundational
areas to deliver a world of Perfect
Matching
106
AI
Psych-
ology
Privacy
Over time
Voice
Job performance
Deep learning
Models
Match to
performance
Massive issues
Recording
conversations
OK?
108. Incredible what is possible over 10 years
2004
108
2005 20072006
Date of founding
2004 20051996
Time for a big new wave in HR?
2001 2002
2012
109. Everything is global..
but hubs still matter. London has great
assets
AI hub
109
HR Tech leadership
Psychology hub
Recruitment hub HR Tech & Tech hub
110. The world is working away already to
move us to the Perfect Match
110
but its going to take 20+ years rather
than 10 because of the hard to solve
problems
111. Enter
111
Perfect Match
To help get us quicker to the benefits of the world
of perfect job matching
by identifying the things that are difficult in perfect
job matching and
accelerate when they get solved by enabling a
community to solve them
112. Perfect Match:
Build a community
112
Gather people
Clarify the big problems
Meetups
News
See where it goes
113. Perfect Match:
Gather people: Meetups
113
Analysis: HR Tech News &
Perfect Match progress
Energy
Regular
Meet people
Learn things
Meetups that include: July Assessment
August Jobs Marketplaces
September ATS & CRM
October Blockchain
November Gaps
117. Perfect Match:
Member Baseball cards [an idea]
ENTJ
Bad fit
Extrovert
Poor concentration
Focused
Gets things done
20 years experience
117
Perfect Matcher
A
Perfect Matcher
B
118. Perfect Match:
Podcast [an idea]
118
Who wants to try co-presenting with me?
Has to be female. Diversity!
119. Perfect Match:
Sponsor for next time
Central London venue
50 people.
Food.
Drink.
5 minute Q&A with me
119