actionable insights through innovative talent assessment – how big data is changing hr and...
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Actionable Big Data Insightsin talent selection anddevelopment
Through online measurement, psychometricsand predictive analyticsRichard Justenhoven, Research Consultant, cut-e group
www.cut-e.com
cut-e – who we are
Predictiveanalytics
Robustpsychometrics
Enabled byweb 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 yourTalent 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
www.cut-e.com
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 DataCreate 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
shapesquestionnaire
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
-2 0 2 4 6 8 10 12 14 16 18 20 22 24 26Months from Hire Date
Time to Proficiency Sales Total Revenue RegionAmericasAPJEMEA
Metric 1 NameNullAPOS Total MgnESG RevESG Rev SPMESG Solns RevEUC SW MgnIDM RevIDM RevenuePORTotal MarginTotal Rev SPMTotal Rev SPM No DFSTotal Rev w DFS EMEATotal RevenueTotal Revenue CSMRXDomain Revenue
Months until Term Date (..0-6 months
Did not Term
6-12 months
12-18 months
18-24 months
2-2.5 years
2.5-3 years
3.5-4 years
4.5-5 years
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 time2) Their turnover impacts customers and
revenue3) The culture of Dell cannot be changed easily4) 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
Trait-3 -2 -1 0 1 2 3
Avg. Score
-3 -2 -1 0 1 2 3Avg. Score
competitive
achieving
imaginative
autonomous
Robust
socially confident
Influencing
focused on results
Canny
Open
systematic
driven by recognition
behavioural
sociable
driven by financial reward
identification
agreeable
conscientious
need for support
driven by development opportunities
professional challenge
driven by security
need for structure
working environment
-2.865
-1.328
-2.213
-2.433
-3.000
-3.000
-3.000
-2.884
-2.731
2.085
0.975
1.015
2.195
1.895
1.159
1.559
1.629
2.428
2.949
1.818
2.859
1.108
0.627
2.223
2.377
1.723
0.457
1.043
1.453
1.637
1.073
1.640
3.000
3.0002.010
3.000
3.000
1.510
2.484
2.944
1.502
1.572
2.791
1.411
1.731
-0.135
-0.265
-0.269
-0.469
-0.739
-0.107
-0.287
-1.186
-0.070
-0.200
-0.610
-0.002
0.495
0.598
0.258
0.238
0.563
0.387
0.646
0.130
0.264
0.331
0.321
0.031
Dell Team Account Executive Scores(Each dot is a TM Score, Bar Plot is the Average)
Job TitleAccount Executive I
Account Executive II
Account Executive III
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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 RoleAchieving and CompetitiveAchieving and Driven by Recognition Highest contribution to revenue for AE Role
Systematic and ConscientiousConscientious 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 revenueNeed 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 youcut-e UK1 Quality CourtLondon WC2A 1HR
E-Mail: [email protected]: www.cut-e.com/UK