What is Big Data? And How Do We Use It in Recruitment? Combining Big Data and Online Assessments to form Actionable Insights Case studies from a Global Investment Bank and an International Technology Company

1. www.cut-e.com
Actionable Big Data Insights
in talent selection and
development
Through online measurement, psychometrics
and predictive analytics
Richard Justenhoven, Research Consultant, cut-e group

2. www.cut-e.com
cut-e – who we are
Predictive
analytics
Robust
psychometrics
Enabled by
web technology
Measurement solutions
for all target groups,
sectors and challenges
you might want to
assess.
Online assessment
products for all levels,
jobs and aspects you
might want to assess.
Unparalleled integration
expertise and truly
mobile solutions to
measure wherever you
want.
Powering your
Talent Strategy
Make evidence based
decisions rooted in data
to drive your talent
strategy and deliver a
truly tailored leadership
journey
35 Offices worldwide 12 million candidates per year 300 employees 70 countries 40+ languages

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Customers who trust in cut-e
Work across a number of countries
together to deliver validated
assessment processes for the
selection of interns, graduates and
experienced hires
Deliver Manager Effectiveness
Assessments across Europe and
furthermore provide assessments
for the hiring of staff across all
levels of seniority
Integrated assessment
processes delivered across
multiple brands for graduates,
intern, apprentice and volume
recruitment
Trusted Partner Within Finance & Banking;

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Innovative Assessment Tools
Mobile First Assessments

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Introducing ChatAssess
cut-e provides players that
 Simulate a real-time WhatsApp like
communication
 Task for candidate is to respond to incoming
messages from different people
 All item formats are supported: i.e. Logical
reasoning, verbal reasoning & numerical
reasoning, Situational Judgement
Innovative Players supporting multiple item formats

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Is this really Big Data?

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Then what is it?

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How can we use this data?
Probe Candidates on Areas
of Risk at Interview
Clear indicators of what
makes a good performer
for you
Early Identification of
development areas
Early roadmap of
performance potential
Create a model to assess
against
Early identification of high
potential performers
Efficient screening of
potential low performers
Know who to target
Identify where good
performers come from
Define an attraction
campaign
Attraction Screening
AssessmentOnboarding

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Linking Assessment To Big Data
Create a Success Model

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Predicting Performance at an
International Investment Bank

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Context
Global Financial Services Firm
Since 2011, cut-e have provided a final-stage
executive assessment service to the
organisation, for senior and specialist roles
We have tracked the careers of 982 of these
senior hires in the organisation over a 5-year
period
Process is recommended but not mandated,
so a good opportunity for a comparative study

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Findings
1. Combining assessment tools
 better prediction of job success than any one assessment tool by
itself;
 each assessment tool makes a unique value-added contribution to
predicting performance
2. The best predictor of job success is the deductive
logical reasoning test: working in a systematic way
with a rule-driven logical process
 Medium & High Scorers on this test have a performance rating that is, on
average, 33% higher than low scorers on the test

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Findings #2
The data (manager rating & questionnaire results) allowed us to
make accurate predictions about work behaviour
 Proactive employees tend to have a certain personality profile
 Role models tend to have another certain personality profile
The work style questionnaire also allows us to make accurate
predictions about the likelihood of leaving e.g.
Rating on Work-style Questionnaire Abandon Rate
(leave the organisation within two years)
Work style ‘low fit’ 71%
Work style ‘medium and high fit’ 18%

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What does this become?
We use this information to;
 Inform the final selection
decision
 Make better, more accurate
decisions
Based on high quality
predictions about whether a
candidate will be successful in
the job

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Driving sales productivity
through assessment & selection

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Cut-e & Dell – Background
The Beginnings
• Started working together in 2011
• Dell undergoing major transformation at the time
 New Skillsets were needed and subsequently a new hiring process!
 A standardized & validated process rooted in cut-e research was
introduced to predict performance in this new salesforce

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Path to Success
Proven set of
questions
shapes
questionnaire
Work relevant traits
(24 traits)
Directing
Persuasive
Socially confident
Sociable
Agreeable
Behavioural
etc. …
Our research
informed us
which of the
measured traits
are the most
important for
success in sales
in Dell

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What did this lead to?
What did we do;
Introduced shapes assessment with Bespoke Dell
Output report and Interview Guide
What did we find out in 2012;
 High Scorers generate, individually, on
average
36%
more than Low Scorers in Revenue terms
 High Scorers generate, individually, on
average
42%
more than Low Scorers in Profit terms

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2016 – Dell ran a follow-up
study using 4 years of data
What does this tell us;
• Hires cost more than simply acquisition cost
• New hires take time to get “good”
• Revenue producers actually take a lot of time
Problems:
1) Revenue producers at Dell have high
turnover and a long ramp up time
2) Their turnover impacts customers and
revenue
3) The culture of Dell cannot be changed easily
4) How do we identify talent that adapts to Dell

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Matching Performance Against
Shapes
We took Dell’s “Big Data” and
matched against our shapes
assessment scores
Now we know what personality traits
have a positive impact on
performance/tenure and what has a
negative impact

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What did this tell us?
Shapes Dimensions Impact
Achieving-and Imaginative Quickest time to proficiency and strongest revenue contribution in ISR Role
Achieving and Competitive
Achieving and Driven by Recognition
Highest contribution to revenue for AE Role
Systematic and Conscientious
Conscientious with Imaginative
Conscientious with Autonomous
Least likely to have voluntary termination within 10 month
Shapes Dimensions Impact
Agreeable and Need for Structure
Highest contribution to early voluntary termination and strongest detractor to
revenue
Agreeable and Work environment Strong detractor to revenue
Need for Structure and Working
Environment
Strong detractor to revenue and higher influence on early voluntary
termination
Dimensions with a Positive Impact
Dimensions with a Negative Impact

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What do we now know?
Research based on:
• 1775 hires in EMEA from 2012-2015
– 293 hired using cut-e psychometrics test
– 450 early terminations in 2014-2015 (25%) and we now understand the following
across a large population of hires:
Personality traits that positively impacts performance in terms of revenue and margin
Personality traits that negatively impacts performance in terms of revenue and margin
Productivity curve shows those who remain and become tenured have a productivity advantage of those
who leave of $ 2.4m per month or $30m per annum
We now understand what makes a good hire in Dell – each good hire adds $30m in revenue per annum

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Summary
Big Data is all about
• How you use it as well as
how much you have
• Good measurement that will
bring a lot added value to
your recruitment

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Thank you
cut-e UK
1 Quality Court
London WC2A 1HR
E-Mail: info.UK@cut-e.com
Web: www.cut-e.com/UK